2026 Hiring Statistics: Challenges, Trends, and Lessons Learned

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

Introduction from Ahryun Moon

Hiring in 2026 is defined by both progress and pressure. While some teams are improving, the broader picture remains sobering: 90% of companies missed their hiring goals, and talent acquisition continues to operate under sustained structural strain. Nearly every organization now relies on AI, but this shift has introduced a new reality—fake or AI-generated candidates have emerged as the number one anticipated hiring threat for the year ahead.

At the same time, long-standing operational bottlenecks, especially scheduling, continue to slow hiring when speed matters most. The result is a market where authenticity, efficiency, and execution discipline are no longer differentiators; they are prerequisites.

Yet the teams that are outperforming the market tell a different story. They didn’t respond to pressure by simply adding headcount, or even by cutting it. Instead, they reorganized. Top-performing teams redesigned roles, workflows, and responsibilities around an AI-enabled reality, using automation to absorb operational load while elevating human judgment, coordination, and candidate connection.

These teams automate intentionally, standardize what should be repeatable, and leverage AI for insight—not just efficiency. In doing so, they protect the human touchpoints that define great hiring experiences, even as their processes become faster and more resilient.

I hope this year’s report inspires you to build toward that future—one where technology amplifies human connection rather than replaces it, and where hiring teams are structured to operate with confidence in an increasingly complex market.

Warm regards,

Ahryun Moon, CEO and Co-Founder, GoodTime

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Key findings at a glance

  • Fraudulent or AI-generated candidates have emerged as the #1 threat for 2026.
  • 90% of companies missed their hiring goals, and 1 in 3 missed by a wide margin.
  • 99.8% of TA teams use, pilot, or plan to use AI agents, making AI effectively mandatory.
  • Scheduling remains the biggest operational tax on hiring (38% of recruiter time).
  • 60% of organizations saw time-to-hire increase in 2025.
    • Only 1 in 9 companies succeeded in reducing time-to-hire.
  • Top-performing TA teams operate fundamentally differently. They were:
    • 74% more likely to keep headcount flat while reorganizing roles
    • 58% more likely to use a centralized platform for texting candidates
    • 20% more likely to use AI agents for interview scheduling
Key hiring trends for 2026
Source: 2026 Hiring Insights Report

Hiring goal attainment hits a five-year high but still signals a systemic struggle

At first glance, 2025 delivered a surprising headline: hiring goal attainment reached its highest point in five years. But a closer look reveals a more sobering truth. Performance remains dramatically below expectations, with most organizations continuing to fall short of their hiring targets.

More than a third of companies (34%) hit less than half of their hiring goals, and only a small fraction (10%) came close to achieving 90–100% of their targets. Most landed somewhere in the middle, filling between 50–74% of roles but still failing to meet organizational needs.

This paradox—the best year in five years, yet still deeply underperforming—reflects mounting competitive pressures, rising process complexity, and an increasing mismatch between talent acquisition teams’ capacity and the demands placed on them. For many organizations, hitting goals is no longer a matter of marginal improvement; it requires a structural transformation of how hiring operates.

“The headcount plan can often be a moving target. Criteria shift mid-search and teams are adjusting hiring priorities in response to changing business needs. When targets move often, it becomes almost impossible for TA teams to hit their goals. The quickest way to improve is early alignment between Executives, Finance, TA, and Hiring Managers, with clear priorities and expectations.”
-Shelby Wolpa, Founder, Shelby Wolpa Consulting

Top overall hiring challenges

This year’s data reveals a hiring environment defined not by a single dominant barrier, but by overlapping obstacles across skills, volume, technology, and candidate behavior.

The most widespread challenge was skills misalignment, cited by 28% of TA leaders. Even when candidate pipelines were strong, recruiters struggled to find applicants whose capabilities matched the expectations set on their résumés. This reflects a growing disconnect between what candidates present and what organizations need, a theme that resurfaces repeatedly throughout this year’s findings.

28% of organizations also reported a lack of qualified candidates, continuing a long-standing pain point for TA teams. Yet the data suggests this shortage is now being compounded by other dynamics, including shifting work models and compensation expectations.

Retention pressures persisted as well, with 27% of TA leaders citing retaining top talent as a major challenge. As skilled workers continue to command multiple offers and leverage competitive markets, companies face mounting pressure to deliver compelling experiences both before and after hire.

The emergence of fake or AI-assisted candidates, cited by 23% of leaders, marks one of the most notable new pressures. Although not the most common challenge this year, their rising prevalence signals an accelerating shift in candidate behavior and sets the stage for why fraudulent candidates become the top anticipated threat for the coming year.

“AI and generalized economic precarity across the globe has created the perfect storm which has deluged traditional hiring funnels with job applications. Recruiters and hiring managers alike are both now aware of the challenge of separating signal from noise. ID verification, background checks, fraud detection and cybersecurity are now becoming much more important elements of a recruiter’s job.”
-Hung Lee, Founder, Recruiting Brainfood

How the hiring landscape changed this year

The most widely felt change in the hiring landscape this year was the surge in candidate demands, with 45% of TA leaders reporting an increase in required touchpoints. An equal share said recruitment team turnover disrupted their ability to maintain steady candidate flow, adding operational strain at a time when processes were already stretched.

Competition for talent also intensified: 44% said the landscape has become more competitive due to increased demand, while 39% reported that building meaningful relationships with candidates has become more important. Speed of engagement rose in priority as well, with 38% noting the growing importance of connecting with candidates quickly.

At the same time, shifts in available talent created mixed conditions across industries. 38% said the landscape feels less competitive due to greater talent availability, while 34% now need more candidates in the funnel to meet hiring goals.

Overall, hiring in the past year became higher touch, higher urgency, and more operationally demanding—challenging TA teams to do more with less in an increasingly dynamic talent market.

Time-to-hire continues to worsen for most teams

The time-to-hire crisis shows no signs of easing.

  • 60% of companies reported that time-to-hire increased in 2025.
  • Only 12% managed to reduce it, an elite minority.

This means nearly nine out of ten organizations are either slowing down or treading water.

The year-over-year persistence of this trend reveals a deeper issue: technology adoption alone is not enough to create speed. Without disciplined workflows, streamlined communications, and clearer ownership across the hiring process, new tools often reinforce existing complexity instead of reducing it.

Just as important is what they didn’t do. Faster teams were:

  • 40% less likely to rely on sourcing bots
  • 56% less likely to use chatbots for early candidate engagement

These leaders focused on structural process improvement rather than volume-driven shortcuts. They modernized the internal mechanics of hiring instead of adding more candidates to an already strained system.

Scheduling remains the top operational burden in hiring

​​Despite advancements in hiring technology, scheduling remains the single most time-consuming and disruptive part of the process.

Talent teams report spending 38% of their time scheduling interviews, making scheduling the highest operational burden measured. And the ripple effect of scheduling-related bottlenecks shapes nearly every stage of the hiring process.

The most-cited scheduling bottlenecks include:

  • Scheduling delays (35%)
  • Limited interviewer pool (35%)
  • Cancellations/reschedules (32%)
  • Hiring manager availability (31%)

These are not isolated inconveniences. They are systemic blockers that lengthen hiring timelines, frustrate candidates, and increase the likelihood of losing talent to faster-moving competitors. Each cancellation can trigger multi-day delays, and each delayed response can push a qualified candidate toward another offer.

“If recruiters are still spending over a third of their time on scheduling, we’re not just missing hiring goals — we’re misusing talent. AI should handle at least 75% of the operational work so TA can focus on what humans do best: building trust, challenging bias, and hiring diverse teams that move the business.”
-Kobi Ampoma, Head of Talent Acquisition (NL), The HEINEKEN Company

Automated scheduling strongly correlates with higher goal attainment

The data has already made one thing clear: interview scheduling is not a side task, but the ultimate bottleneck. But understanding the problem is only half the equation. The more important question is whether fixing it actually changes outcomes.

This year’s data shows that it does.

Companies using automated or AI-driven scheduling were 1.6x more likely to achieve near-perfect hiring goal attainment (13% hitting 90–100%, compared with 8% of non-users). This marks scheduling automation not just as a time-saver, but as a meaningful operational advantage tied directly to hiring outcomes.

The correlation makes intuitive sense: when coordination delays, back-and-forth rescheduling, and interviewer bottlenecks are reduced, TA teams regain bandwidth to nurture candidates and make timely decisions. In contrast, organizations still relying on manual scheduling are struggling under operational weight that compounds with every requisition.

Current scheduling benchmarks

Scheduling speed is one of the clearest operational signals behind time to hire. While time-to-hire captures the outcome, scheduling metrics reveal where momentum is gained or lost—often days before delays show up in aggregate hiring data.

The benchmarks below reflect the three most important scheduling metrics TA teams should monitor to keep hiring moving efficiently.

AI’s role evolves: from basic automation to decision intelligence

AI adoption in talent acquisition reached near-universal levels in 2025, but how teams use AI has changed dramatically.

The top AI use case this year was analytics and reporting, with 45% of teams leveraging AI to surface insights, track funnel health, and identify inefficiencies. Scheduling (36%) and resume screening (36%) remain widely used but no longer dominate the narrative.

This signals a critical shift: AI is becoming the decision-making infrastructure behind hiring, not merely a way to automate repetitive tasks.

TA teams are increasingly relying on AI for:

  • Diagnostic visibility into bottlenecks
  • High-resolution quality-of-hire signals
  • Resource allocation insights
  • Predictive performance indicators

In other words, AI is expanding from “doing work” to “informing how work is done.”

“The goal isn’t just speed. It’s to free people to focus on what matters most. Our coordinators can now focus on the interactions that matter — guiding candidates, coaching hiring managers, and refining the experience instead of chasing calendars.”
-Tiffany Clark, Head of HR Strategy & Shared Services, S&P Global

How talent teams changedthis year

Talent teams underwent significant restructuring last year, driven by shifting hiring demands and evolving organizational priorities. More than half of companies (56%) grew their TA headcount, reflecting increased pressure to meet hiring goals and support more complex workflows. Another 24% kept headcount steady but reorganized roles, often redistributing responsibilities to adapt to new tools, expectations, or process requirements. Meanwhile, 19% reported reducing TA headcount, forcing smaller teams to manage the same or greater workload with fewer resources.

AI played an increasingly influential role in these changes. As AI automated scheduling, screening, and reporting tasks, many organizations reevaluated coordinator responsibilities, expanded recruiter support roles, or shifted bandwidth toward candidate experience and strategic partnership activities.

Collectively, these adjustments reflect a larger transition: TA teams are not simply shrinking or growing—they are transforming.

Roles are being redesigned to align with an AI-enabled hiring ecosystem where operational work is streamlined and human expertise is focused on higher-value decision-making and engagement.

Candidate communication trends: texting becomes central—and centralized

Texting has become a core part of candidate communication, but how teams manage it varies widely. 40% of organizations now use a centralized company platform or texting software, the most common approach and the one most associated with consistency and compliance.

Another 36% text candidates using company-issued phones, while 24% still rely on recruiters’ personal cell phones, introducing risks around tracking, data security, and uneven candidate experience. Notably, 0% of respondents say they avoid SMS or WhatsApp altogether, underscoring how essential mobile communication has become in the hiring process.

More layoffs than we’ve seen in four years

Layoffs surged sharply over the past 12 months, marking one of the most turbulent periods for talent teams in recent years. 75% of companies conducted layoffs in 2025, the highest level in the past four years, and a steep rise from 2024 and 2023. The scale of these reductions signals widespread organizational restructuring and heightened economic uncertainty.

The severity of layoffs also increased. While the majority of organizations kept reductions relatively limited, the distribution reveals escalating pressure across the workforce:

The end of the RTO debate: Office-first becomes the dominant reality

The pendulum has swung decisively. Here’s the current status of workforce distribution:

  • 55% fully in office
  • 42% mostly in office
  • Only 3% mostly remote
  • None were fully remote

Despite media narratives about remote stability, the data shows a nearly universal return to office-first operating models.

This shift adds complexity for TA teams who must now navigate redefined candidate expectations, changing geographic recruiting strategies, and evolving internal policies.

A year defined by pressure, and by clarity

2025 exposed deep operational friction across the hiring lifecycle, from scheduling bottlenecks to rising time-to-hire, increasing candidate misrepresentation, and mounting organizational expectations. Yet it also delivered clarity: the organizations making meaningful progress are those that have embraced AI-driven decision-making, standardized workflows, and disciplined process improvement.

The path forward is no longer ambiguous.

To succeed in 2026, talent acquisition must become more efficient, more insight-driven, and more resilient, all while safeguarding authenticity in a rapidly evolving talent landscape.

What Top-Performing Talent Acquisition Teams Do Differently

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

In a year when 90% of companies missed their hiring goals, a small cohort broke through the noise. These top-performing TA teams—the organizations that achieved 75% or more of their hiring goals—didn’t simply work harder. They operated differently. Their strategies, tools, and organizational environments show a level of operational maturity that stands in stark contrast to the broader hiring market.

Where many teams struggled with worsening time-to-hire, growing candidate demands, and rising workflow complexity, top performers built uncompromising systems around efficiency, automation, and quality. Their advantage was not incremental; it was structural.

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“The best Talent teams aren’t ‘adding AI’ — they’re re-architecting how hiring works. Simply layering AI tools onto broken or inefficient processes won’t drive impact. The real opportunity lies in auditing the end-to-end hiring journey, starting with the problem to solve, and intentionally redesigning it.”
-Manjuri Sinha, VP HR & Global Head of GTM Org Success & People Partners, Miro

The signature behaviors that set top performers apart

Top-performing TA teams—the small group that met at least 75% of their hiring goals—share a set of behaviors that consistently separate them from the rest of the market.

They are 20% more likely to use AI agents for interview scheduling, and the payoff is measurable: teams that use automated scheduling are 1.6x more likely to achieve near-perfect hiring goal attainment (13% hitting 90–100%, compared with 8% of non-users).

On the surface, these choices can appear operational. In practice, they signal something far more consequential. While many organizations still rely on manual coordination to move candidates through the process, top performers have automated the most failure-prone part of hiring: scheduling.

By reducing back-and-forth, delays, and rescheduling cascades, these teams protect candidate momentum and recruiter bandwidth. The result isn’t just faster movement through the funnel, but a hiring process that is more predictable, more resilient, and easier to scale under pressure.

Their advantage isn’t simply tool adoption; it’s that they invest in automation where it directly improves outcomes.

Who top performers are, and the conditions that enable them

What distinguishes these teams isn’t budget or headcount. It’s the environment they operate in and the discipline with which they design their processes.

Top-performing teams are more likely to work within stable organizational structures. They were almost twice as likely to report no layoffs in the past year and 74% more likely to have reorganized roles without reducing headcount, a sign that their organizations protected continuity rather than resetting workflows amid turbulence. Stability doesn’t guarantee performance, but it creates the conditions for it: clearer ownership, less churn, and systems that don’t need to be rebuilt every quarter.

They also operate with flexibility where it matters. Compared to the broader market’s sharp return to office-first models, top performers were significantly more likely to operate in hybrid environments. That flexibility has practical implications: distributed teams tend to rely more heavily on standardized tools, centralized communication, and automated coordination, all of which reduce bottlenecks and improve execution.

Together, these conditions allow top performers to focus less on firefighting and more on system design.

How top performers operate differently than everyone else

Automation is replacing headcount growth as the path to hiring success

One of the most striking findings in the 2026 data isn’t about tools or tactics—it’s about how top-performing teams scale.

Despite operating in the same market conditions as everyone else, top-performing TA teams are less likely to grow headcount, even as they achieve significantly higher hiring goal attainment. Instead of expanding teams to absorb rising complexity, they modernize their infrastructure to remove it. While 60% of underperforming teams grew headcount over the past year, fewer than half of top performers did the same. Instead, top performers were far more likely to keep headcount stable while reorganizing roles, signaling a deliberate shift away from logistics-heavy work and toward higher-leverage responsibilities.

This pattern reflects a fundamentally different operating model. Top-performing teams lean into automation, AI-powered scheduling, and workflow orchestration to eliminate the manual coordination that slows hiring down. By reducing scheduling drag, communication friction, and process noise, they increase throughput without increasing staffing.

The result is not just efficiency—it’s resilience. These teams hit hiring goals at a higher rate and avoid the cycle of constant headcount expansion that many organizations rely on to keep pace.

In 2026, the strongest TA organizations aren’t scaling by hiring more recruiters. They’re scaling by building systems that make recruiters more effective.

Top performers thoughtfully embraceAI agents

While AI agent adoption is widespread across talent acquisition, how teams deploy AI clearly separates top performers from everyone else.

Top-performing TA teams are significantly more likely to use AI agents for core workflow mechanics and decision support, not just surface-level automation. Their highest adoption areas, analytics and reporting (43%) and interview scheduling (42%), map directly to the two biggest operational levers in hiring: visibility and speed. By contrast, teams that underperform are less likely to apply AI in these system-level functions, limiting its impact on overall hiring outcomes.

Notably, top performers also lean more heavily into structured evaluation tools, including scorecard analysis and interview intelligence. This suggests a more mature use of AI, one focused on improving signal quality and consistency, not just reducing manual work.

Where top-performing teams don’t over-invest is equally telling. They are less differentiated in areas like candidate sourcing and conversational AI, reinforcing a broader theme from this year’s data: automation at the top of the funnel is not what drives results. Instead, gains come from tightening execution in the middle of the hiring process, where delays, cancellations, and poor coordination most often derail outcomes.

In short, top-performing teams treat AI as infrastructure, not experimentation. They deploy it where it compounds—speeding scheduling, improving insight, and reinforcing hiring discipline—while others remain stuck using AI tactically rather than transformationally.

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AI-powered scheduling as a coreoperating mechanism

For top performers, AI scheduling isn’t a convenience feature — it’s foundational.

Top-performing teams were:

  • 20% more likely to use AI agents for interview scheduling
  • 16% more likely to run a fast, streamlined interview process
  • 18% more likely to offer automated scheduling options directly to candidates

These investments matter because scheduling remains the single largest operational tax in hiring, consuming 38% of recruiter time across the industry. By automating the handoffs, coordination, and rebooking workflows that drain bandwidth, top performers free their teams to focus on higher-value work, while delivering a faster, more consistent candidate experience.

Where others still rely on people to move calendars, top performers use systems.

“The fastest teams don’t work ‘harder’; they design hiring like a product and think with the candidate in mind. They front load clarity: tight intake meetings, clear success profiles, scorecards, and aligned decision makers before the role goes live. They treat time-to-hire as a system metric, not a TA-only KPI.”
-Kobi Ampoma, Head of Talent Acquisition (NL), The HEINEKEN Company

Centralized, structured communication,not ad hoc messaging

The second major investment area—and one of the strongest differentiators for 2026—is communication discipline.

Top performers were 58% more likely to use a centralized texting platform This shift away from personal phones and fragmented messaging channels does more than tidy up communications. It fundamentally reshapes hiring operations by enabling:

  • Faster response times
  • Consistent candidate messaging
  • Better compliance and documentation
  • Reduced candidate drop-off
  • Clearer accountability across the team

In a year when candidate expectations accelerated and fraud concerns grew, standardized communication became both a performance driver and a risk mitigator.

Top performers treated communication not as a task, but as a system that needed governance.

How top performersmeasure success

Top-performing TA teams distinguish themselves not only by how they work, but by what they choose to measure. In a year where candidate fraud increased, time-to-hire worsened for most organizations, and AI reshaped the mechanics of hiring, the most successful teams gravitated toward the metrics that actually predict meaningful outcomes, not just activity.

Their measurement philosophy is sharper, more sophisticated, and far more focused on downstream impact than their peers.

Quality of hire is the anchor metric

Among all metrics measured in 2026, quality of hire stands out as the signature of top-performing teams.

Top performers were:

  • 22%more likely to track quality of hire
  • 42% more likely to select it astheir top hiring metric

This focus is especially meaningful in a year where fake or fraudulent candidates rose to the top of anticipated challenges. Rather than respond by adding more assessments or slowing the process, top performers rebuilt measurement systems around outcomes—ensuring every hire meets performance expectations and aligns with long-term needs.

Where many teams still lean on volume-based or speed-based measures, top performers look at what happens after the hire.

“AI has raised the bar on what ‘verification’ actually means. A single background check at the end of the process isn’t enough anymore. TA teams now have to confirm identity and authenticity at multiple points – starting at application, continuing through assessments and interviews, and carrying all the way through onboarding.”
-Becky McCullough, VP, Talent Acquisition & Mobility, HubSpot

Funnel health takes priority over funnel volume

Another clear differentiator: top performers track funnel health, not just funnel size. They were significantly more likely to measure application completion rates (23% more likely). This matters because application completion, unlike raw applicant volume, reveals:

  • Where friction exists in the early funnel
  • Whether job postings and processes are aligned with candidate expectations
  • How effectively the system converts interest into engagement

By watching the health of the funnel rather than the size of it, top performers avoid the trap of chasing more candidates when the real issue lies in process breakdowns.

It’s a more mature, more diagnostic approach, one that strengthens every downstream stage of hiring.

Less emphasis on cost-per-hire

In contrast to many organizations still under budget pressure, top performers were 21% less likely to treat cost-per-hire as a central metric.

The reason is simple: Cost metrics don’t predict hiring outcomes. Quality, velocity, and funnel integrity do.

This doesn’t mean cost doesn’t matter. It means top performers refuse to optimize for short-term savings at the expense of long-term hiring effectiveness.

A measurement system designed for clarity, not complexity

Together, these choices reflect a coherent philosophy:

  • Measure performance, not activity
  • Track what influences outcomes, not what’s easiest to quantify
  • Use data to surface friction, not justify the status quo
  • Prioritize metrics that support speed and quality in an environment of rising candidate misrepresentation

“We’re not just looking at metrics like quality of hire now. We’re also reassessing where our bar is for things like time-to-fill and time-to-hire. What GoodTime is really good at is enabling us to quantify how much we can improve metrics and whether those improvements are within our control.”
-Robbie Simpson, Head of Talent Acquisition, Glovo

In short, top performers don’t just use better tools—they use better metrics. And those metrics allow them to see the hiring system clearly enough to fix what others can’t.

Top performers’ prioritiesfor 2026

Looking ahead to 2026, top-performing TA teams are doubling down on the same structural advantages that fueled their success in 2025. Their priorities reflect a clear understanding of where hiring is headed: toward greater automation, tighter workflow discipline, and a candidate experience defined by speed and clarity rather than personalization alone.

In contrast to organizations that are still reacting to rising fraud, worsening time-to-hire, and increased operational strain, top performers are proactively strengthening the systems that drove their gains. Their 2026 priorities read less like a wishlist and more like a continuation of a proven strategy.

Improving overall efficiency

Efficiency is the top priority for high-performing teams entering 2026. And this time, it’s not shorthand for cost-cutting or incremental process fixes. Top performers are focused on:

  • Removing friction from every stage of the funnel
  • Reducing coordination load
  • Increasing workflow reliability
  • Streamlining decision paths

Improving time-to-hire

While the majority of companies saw time-to-hire worsen, top performers were far more likely to prioritize and protect speed as a strategic capability.

Their focus reflects an understanding that speed is no longer a nice-to-have, it is:

  • A defense against candidate dropout
  • A competitive differentiator in a market with heightened candidate expectations
  • A requirement for maintaining internal trust in TA

Top performers treat time-to-hire as a system-level output, not an isolated metric.

Upgrading hiring technology

For top performers, tech modernization is not about adding more tools; it’s about replacing brittle, manual steps with systems that can scale.

In 2026, they are more likely to invest in:

  • AI-driven scheduling
  • Automated communication workflows
  • Centralized texting platforms
  • Analytics and bottleneck diagnostics

These upgrades reflect a broader shift: top performers invest in technology that governs the workflow, not just supplements it.

Enhancing the candidate experience through speed, clarity, and flexibility

Where many organizations still equate candidate experience with personalization, top performers have moved toward a more modern definition rooted in:

  • Fast interview-to-offer timelines
  • Clear, automated communication
  • Self-scheduling and self-rescheduling
  • Reduced ambiguity and fewer touchpoints

This shift is especially important in a landscape where candidate expectations have risen and patience has dropped. Top performers have recognized that the most valuable form of personalization is removing the friction that slows candidates down.

The blueprint: what others can learn from top performers

Across every data point, from AI usage to workflow design, communication discipline, and measurement,  top-performing TA teams reveal the same underlying truth: they win by building systems that remove friction and amplify signal. Their results aren’t the product of luck or lighter workloads. They are the consequence of intentional design decisions that compound across the entire hiring lifecycle.

The blueprint they offer is not abstract. It’s practical and immediately actionable:

1. Treat scheduling as a strategic system, not an administrative task.
Top performers automate coordination end-to-end, enabling faster movement and freeing teams from the single largest operational burden.

2. Centralize communication to eliminate inconsistency and reduce dropout.
By consolidating texting and candidate outreach, they create a predictable, timely communication rhythm that keeps candidates engaged and reduces risk.

3. Deploy AI where it improves judgment and workflow reliability.
Instead of concentrating automation at the top of the funnel, they weave AI into screening, question generation, analytics, and reporting, the areas that shape quality, velocity, and decision-making.

4. Anchor measurement in quality and funnel health.
Top performers track the metrics that actually forecast hiring success: quality of hire, completion rates, conversion patterns, and downstream outcomes. And they deprioritize metrics, like cost-per-hire, that create false efficiency.

5. Cultivate organizational stability and role clarity.
Reorganizations, not reductions, give teams the stability to adopt new tools and refine workflows. Flexibility in work models enables faster coordination and stronger adoption of modern technology.

6. Build candidate experiences around speed, clarity, and flexibility.
Top performers understand that today’s candidates value momentum more than polish. Self-service, automation, and transparent updates create the experience candidates now expect and competitors struggle to match.

Together, these practices form a coherent operating system for modern hiring, one that is resilient to fraud, capable of sustaining speed, and grounded in metrics that matter. The path forward for TA teams is not about working harder or adding more volume. It’s about adopting the structural advantages that top performers have already proven to work.

Healthcare Hiring Trends: Stats, Challenges, and Strategies for 2026

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

Healthcare hiring teams enter 2026 facing intensified pressure across both talent supply and execution. The data shows that finding qualified candidates is the most significant challenge healthcare organizations experienced, outweighing all other issues by a clear margin. At the same time, process-related strain continues to slow hiring cycles, particularly in interviewing and decision-making.

Hiring outcomes deteriorated year over year, with healthcare organizations achieving a smaller share of their hiring goals in 2025 than in 2024. This decline sits alongside rising time-to-hire and persistent candidate drop-off, indicating that healthcare teams are not simply dealing with demand shocks, but with systems that struggle to convert interest into hires.

Looking ahead, healthcare leaders are prioritizing efficiency, speed, and process reliability. Technology investment and selective use of AI are increasingly viewed as necessary infrastructure to stabilize hiring operations rather than optional enhancements.

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2025 performance review

Healthcare hiring performance weakened in 2025. The data shows that organizations achieved a lower portion of their hiring goals than the year prior, reversing earlier progress and reinforcing how fragile gains in this sector can be.

This decline occurred alongside broader signs of strain. Time-to-hire increased for many healthcare teams, and competitive pressure remained high. Together, these signals suggest that hiring shortfalls were driven less by lack of effort and more by constraints in converting available candidates into completed hires.

Rather than pointing to a cyclical dip, the performance results indicate a structural challenge. When qualified talent is scarce and internal processes are slow or inconsistent, even modest disruptions can materially reduce hiring output.

Key challenges

Healthcare leaders are unequivocal about their primary challenge. A lack of qualified candidates stands clearly at the top of the list, reported more frequently than any other issue.

Just below that top concern is a dense cluster of related problems: skills that do not align with resumes, too many applicants to effectively screen, and candidates dropping out during the process. This combination signals that healthcare hiring teams are dealing with both scarcity and noise at the same time.

Execution and workload pressures form the next layer. Unmanageable recruiter workload, candidates holding multiple offers, and rising compensation expectations all contribute to instability, but they do not rival talent availability in prominence.

Scheduling and communication bottlenecks

Hiring slowdowns in healthcare are driven primarily by interviewer capacity and follow-through, not by sourcing alone. The most frequently cited bottleneck is a limited pool of available interviewers, which constrains throughput even when candidates are ready to move forward.

Closely following are delays in completing scorecards and the volume of applications requiring review. These responses point to pressure in the middle of the funnel, where decisions depend on busy clinicians and managers who are balancing hiring responsibilities with core operational work.

Scheduling delays and interview cancellations also feature prominently. However, the data suggests these are symptoms of a broader coordination problem rather than isolated failures. When interviewer availability is inconsistent and feedback cycles stall, scheduling becomes fragile and candidates wait longer than they are willing to tolerate.

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Candidate engagement dynamics

Candidate disengagement is a recurring theme in healthcare hiring. Dropout during the hiring process ranks among the most commonly experienced challenges, and it remains one of the most anticipated issues for the year ahead.

This pattern aligns with the bottleneck data. Candidates are most likely to disengage when interviews are delayed, rescheduled, or followed by long periods of silence. Engagement, in this context, is not primarily about personalization or employer branding. It is about momentum and clarity.

Healthcare candidates appear willing to enter the process, but far less willing to remain in it when progress slows or expectations are unclear.

Technology adoption and the role of AI in healthcare hiring

Healthcare organizations are applying automation and AI where it reduces ambiguity and manual effort in the hiring process. The strongest adoption appears in analytics and reporting and interview-related preparation, including generating interview questions.

A second tier of adoption supports interview execution, such as scheduling and interview analysis. These use cases reflect where healthcare teams feel the most operational pain: coordinating interviews, standardizing evaluation, and maintaining visibility into progress.

More candidate-facing automation, including chatbots and automated communications, appears lower in use. This suggests a cautious approach to automating interactions in a high-stakes hiring environment where trust and clarity matter.

Overall, AI is being positioned as supporting infrastructure, not as a substitute for clinical or managerial judgment.

Metrics healthcare teams prioritize

Healthcare hiring teams focus measurement on cost, stability, and outcomes. The most emphasized metrics include cost-per-hire and employee turnover, reflecting concern about the downstream impact of hiring decisions.

Quality of hire and time-based measures such as time-to-hire and time-to-fill also feature strongly. These metrics help teams assess whether hiring processes are producing durable results at a sustainable pace.

Candidate experience and conversion indicators are tracked, but they carry less weight than cost and retention-oriented measures. This suggests that healthcare organizations are primarily trying to control the operational and financial consequences of hiring instability.

2026 healthcare hiring outlook

Healthcare leaders expect the same core pressures to persist into 2026. Candidate preferences for fully remote work and continued dropout during the hiring process rise to the top of anticipated challenges.

Lack of qualified candidates and misalignment between skills and resumes remain close behind, indicating little expectation of relief on the supply side. Limitations of existing hiring technology also feature prominently, reinforcing concerns about whether current systems can support faster, more reliable execution.

The outlook reflects caution rather than optimism. Healthcare organizations are preparing for continued friction rather than a return to equilibrium.

2026 priorities

Healthcare hiring priorities for 2026 center on making hiring work more efficiently. Improving overall efficiency leads clearly, followed by reducing time-to-hire and improving offer acceptance.

Cost control and process standardization form the next tier of priorities, reinforcing the focus on repeatability and predictability. Optimizing automation and using AI to improve efficiency appear as enabling strategies rather than headline goals.

Candidate experience and relationship-building are present but secondary. The data suggests that healthcare leaders view experience improvements as the result of faster, more reliable processes, not as standalone initiatives.

Broad intent to invest further in hiring technology underscores this approach. For healthcare teams, modernization is increasingly seen as a prerequisite for maintaining hiring capacity under sustained pressure.

Final thoughts and key takeaways for healthcare hiring leaders

Address talent scarcity and signal quality at the same time
A lack of qualified candidates is the defining challenge in healthcare hiring, but it is compounded by skills mismatch, high applicant volume, and mid-process dropout. Screening rigor and process speed must improve together. Solving only one side of the equation will not materially improve outcomes.

Protect interviewer capacity and decision follow-through.
Limited interviewer availability and delayed scorecard completion are the most consistent brakes on hiring speed. Healthcare teams gain more by clarifying interviewer expectations, standardizing feedback workflows, and reducing cognitive load than by adding more candidates to the funnel.

Treat scheduling and coordination as operational infrastructure.
Scheduling delays and reschedules are not isolated issues. They reflect fragile coordination across busy clinical stakeholders. Reliable, structured scheduling workflows reduce downstream delays and directly lower candidate dropout.

Use AI to stabilize interviewing and visibility, not to automate judgment.
Healthcare teams see the most value from AI when it supports analytics, interview preparation, and coordination. These uses improve consistency and transparency without undermining trust in high-stakes hiring decisions.

Measure outcomes that reflect durability, not just speed.
Cost-per-hire, turnover, quality of hire, and time-based metrics dominate healthcare measurement for a reason. They reveal whether hiring decisions hold up under operational pressure. Experience metrics matter, but they follow from reliable execution.

Efficiency is the strategy for 2026.
Healthcare leaders are prioritizing efficiency, time-to-hire, and offer acceptance because the system cannot absorb additional friction. Technology modernization and process standardization are increasingly prerequisites for maintaining hiring capacity.

The path forward
Healthcare hiring success in 2026 will depend less on market relief and more on operational discipline. Teams that strengthen interviewer readiness, stabilize scheduling, deploy AI for insight, and align metrics with real outcomes will be best positioned to hire consistently in an environment where every delay carries real cost.

Tech Hiring Trends in 2026: AI, Automation, and Candidate Experience Rule

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

Technology hiring teams enter 2026 operating in a high-expectation, high-friction environment. While demand for technical talent remains strong and AI adoption is widespread, execution challenges continue to limit results. Extended time-to-hire, coordination breakdowns, and declining signal reliability have made it harder for teams to move quickly with confidence.

Despite deep familiarity with hiring technology, most tech organizations have not translated tooling into speed. Scheduling delays, interviewer availability, and inconsistent hiring manager readiness continue to slow progress, particularly in competitive roles where candidates often hold multiple offers. At the same time, skills misalignment and AI-assisted candidate misrepresentation have increased the cost of poor or rushed decisions.

The data shows that success in technology hiring now depends less on adding tools and more on operational discipline. AI delivers the greatest value when applied to analytics, reporting, and scheduling—areas that improve visibility, reduce coordination friction, and support faster decision-making. Teams that focus automation on workflow reliability outperform those that concentrate solely on top-of-funnel activity.

Candidate experience expectations in technology have also narrowed. Speed, transparency, and predictable momentum now matter more than additional touchpoints. Delays in scheduling, feedback, or decisions quickly erode trust and increase drop-off, regardless of employer brand strength.

Looking ahead, technology hiring performance in 2026 will be defined by execution quality. Teams that standardize workflows, strengthen interviewer readiness, modernize scheduling, and use AI as infrastructure, not experimentation, will be best positioned to compete for scarce technical talent.

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2025 performance review

Technology hiring momentum stalled after a brief rebound. In 2023, technology organizations achieved 58% of their hiring goals, the strongest result in the four-year trend. That progress reversed in 2024, with attainment falling to 50% and holding steady in 2025.

The plateau highlights a persistent execution problem. Despite deep familiarity with hiring technology and widespread AI usage, many teams continue to struggle with extended time-to-hire, scheduling delays, and interviewer readiness. These factors compound in competitive technical roles, where candidates often move quickly and disengage when processes slow.

At the same time, skills misalignment and fraudulent candidate profiles have made evaluation more complex, increasing the risk of both false positives and prolonged decision-making. The result is a hiring system that is well tooled, but insufficiently coordinated to translate capability into consistent outcomes.

Core hiring challenges for technology teams

The tech sector’s hiring challenges in 2025 reflect execution friction more than talent scarcity. The most commonly cited challenge was limitations of current hiring technology, signaling that even tech-forward organizations feel constrained by tools that don’t fully support speed, coordination, or decision-making at scale.

Close behind were candidates holding multiple offers and skills misalignment between resumes and actual capability, reinforcing a central tension for technology teams: candidates are moving faster, while signal is becoming harder to trust. Together, these dynamics force teams to slow evaluation and add steps at the very point where speed is most critical.

Brand and funnel quality issues continue to surface as secondary pressures. Suboptimal employer branding and difficulty attracting truly qualified candidates persist, while high applicant volume adds noise rather than relief. More candidates have not translated into better candidates, increasing screening effort and recruiter load.

Operational strain further compounds these challenges. Recruiter workload, interviewer readiness, and internal policy changes all contribute to delays across scheduling, feedback, and decision-making. The result is a hiring process that is well resourced on paper, but increasingly fragile in execution.

“The teams that are pulling ahead treat AI as both a tooling shift and a behavioral one. They set clear principles for how they’ll use AI, build tight operating norms around quality and consistency, and invest in upskilling so people feel confident adopting new workflows.”
-Becky McCullough, VP, Talent Acquisition & Mobility, HubSpot

Time-to-hire pressures continue to intensify

Time-to-hire remains a major constraint for technology hiring teams. A clear majority of leaders report longer hiring timelines over the past year, while only a very small share have managed to speed up.

In a sector where candidates often hold multiple offers, these delays are especially costly. Even minor friction in scheduling, feedback, or decision-making can derail otherwise strong candidates.

The takeaway is straightforward: technology teams are not losing talent because of low demand, but because processes are moving too slowly. Reducing time-to-hire will require eliminating coordination friction and improving scheduling and decision velocity across the hiring workflow.

Scheduling and coordination bottlenecks slow tech hiring

The primary bottlenecks in technology hiring are operational, not strategic. Scheduling delays emerged as the most common constraint, closely followed by interview cancellations and reschedules, interviewer availability, and poor communication with candidates. Together, these issues point to coordination breakdowns rather than gaps in intent or effort.

Volume adds friction rather than velocity. Many technology teams report reviewing too many applications, which increases screening time without improving candidate quality. This overload slows progress through the funnel and contributes to delayed feedback and decision-making.

Candidate-side fallout is a direct result. Withdrawals remain common as hiring timelines stretch, while limited interviewer capacity and underprepared interviewers further disrupt momentum. Even when qualified candidates are identified, delays in scorecard completion and hiring manager decisions extend cycles unnecessarily.

Taken together, the data shows that technology hiring is being slowed by workflow mechanics. Without more reliable scheduling, clearer ownership, and faster handoffs between recruiters and interviewers, improvements elsewhere in the process struggle to translate into faster or better outcomes.

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How technology teams are using AI and automation

AI and automation are deeply embedded in tech hiring, but usage patterns reveal a shift from experimentation to practicality. The most common applications center on candidate-facing automation, sourcing, and insight generation, reflecting the sector’s need to move faster while managing increasing complexity.

Technology teams are applying AI across nearly every stage of the hiring lifecycle, from screening and interview preparation to communications and scheduling. Notably, analytics and reporting rank among the top use cases, signaling a growing emphasis on visibility and decision support rather than automation alone.

At the same time, adoption is not limited to back-office tasks. Candidate-facing tools, including conversational AI and automated communications, are widely used to maintain engagement as timelines stretch. Interview intelligence, question generation, and scheduling automation further support consistency in evaluation and reduce manual coordination.

What stands out is not how much AI technology teams are using, but where they are using it. The focus is shifting toward workflow reliability, signal clarity, and faster handoffs between stages. For technology leaders, the takeaway is clear: AI delivers the most value when it strengthens execution and insight, not when it simply adds more activity to the top of the funnel.

The hiring metrics technology teams prioritize

Technology hiring teams continue to track a broad mix of volume, efficiency, and outcome metrics, reflecting the sector’s need to balance speed with signal quality. At the top of the list are funnel visibility measures, including source of hire and applicants per role, underscoring the ongoing effort to understand where candidates are coming from and how demand is shaping pipelines.

At the same time, quality and speed metrics are nearly as prevalent. Quality of hire and time-to-hire are both widely measured, reinforcing how closely technology teams link hiring success to both execution pace and downstream performance. In technical roles, where mis-hires are costly and skills are difficult to validate, these metrics serve as critical checks on decision-making.

Offer acceptance rate and employee turnover rate further reflect the sector’s focus on outcomes beyond the offer stage. Together, these measures help teams assess whether candidates are both choosing the organization and staying once hired, especially in a market where competing offers are common.

Candidate interview experience is tracked by a meaningful share of technology organizations, though it trails operational metrics. Rather than treating experience as a standalone goal, many teams appear to assess it indirectly through funnel conversion and completion rates, using those signals to diagnose friction in the process.

Overall, the metrics landscape in technology hiring suggests a shift toward system-level insight. The most effective teams are using metrics not just to report activity, but to understand where hiring slows, where signal breaks down, and where process improvements will have the greatest impact.

What technology hiring teams expect in 2026

Technology hiring leaders expect internal execution challenges to be the biggest constraint in 2026. Inefficient or underprepared hiring managers and interviewers rank as the most anticipated issue, underscoring how internal readiness continues to slow hiring outcomes.

Concerns around candidate signal and trust are rising. Fake or fraudulent candidates, including those using AI to misrepresent qualifications, are now a top expected challenge, adding pressure to evaluation processes that are already strained by speed requirements.

Work model friction remains unresolved. Candidate preference for fully remote work and ongoing difficulty adapting interviews to remote or hybrid environments continue to complicate coordination and expectation-setting in an increasingly office-first landscape.

Despite years of investment, many leaders still expect limitations in current hiring technology to persist, alongside recruiter workload strain and skills misalignment. Together, these pressures point to a 2026 hiring environment where success will depend less on new tools and more on improving execution, rigor, and workflow reliability.

Where technology teams are focusing in 2026

Technology hiring priorities for 2026 center squarely on execution and efficiency. Improving overall efficiency is the top focus area, signaling broad recognition that existing processes are not scaling effectively in a fast-moving, high-signal-noise environment.

Speed remains a close second. Improving time-to-hire and optimizing automation rank near the top, reinforcing how deeply technology teams feel the cost of slow coordination and delayed decisions. Rather than chasing speed in isolation, leaders are prioritizing changes that reduce friction across the hiring workflow.

Candidate experience continues to matter, but it is increasingly defined by clarity, responsiveness, and momentum. Improving experience and increasing personalization remain important, though they trail efficiency-focused initiatives. This suggests that tech teams see experience as an outcome of better execution, not a standalone effort.

Technology modernization remains a meaningful, but not dominant, priority. Upgrading hiring technology and using AI to make hiring more efficient both rank mid-pack, reflecting a shift from acquiring tools to extracting more value from what teams already have. Standardization and time-to-schedule improvements appear lower on the list, but still reinforce the broader emphasis on workflow discipline.

Taken together, the priorities signal a pragmatic reset. Technology hiring teams are not chasing transformation for its own sake. In 2026, they are focused on tightening systems, moving faster with confidence, and making existing technology work harder to deliver consistent results.

Final thoughts and key takeaways for technology hiring leaders

Execution, not access to tools, is the defining challenge for technology hiring.
Despite widespread AI adoption and strong familiarity with hiring technology, most tech teams continue to struggle with speed, coordination, and decision confidence. The gap is no longer about capability; it is about how reliably hiring systems operate under pressure.

Treat scheduling as core infrastructure.
Scheduling delays, cancellations, and interviewer availability issues are the most consistent drivers of extended time-to-hire and candidate drop-off in tech. Automating coordination and reducing manual handoffs unlocks more speed than adding candidates or sourcing tools.

Strengthen signal validation without slowing the process.
Skills misalignment and AI-assisted candidate misrepresentation are now central risks. Technology teams must reinforce structured interviews, clearer scorecards, and consistent evaluation standards while maintaining momentum for candidates with multiple options.

Use AI where it improves visibility and workflow reliability.
The strongest impact comes from AI applied to analytics, reporting, and scheduling. These uses surface bottlenecks, improve decision-making, and reduce coordination load. Automation that only increases top-of-funnel activity does not address core constraints.

Redefine candidate experience around speed and clarity.
For tech candidates, experience is shaped less by personalization and more by responsiveness, transparency, and predictable movement through the process. Fast scheduling, timely communication, and clear next steps matter more than added touchpoints.

Measure the system, not just the activity.
Technology leaders are increasingly anchoring on quality of hire, time-to-hire, offer acceptance, and funnel health metrics. These measures reveal where execution breaks down and whether hiring outcomes hold up after the offer stage.

The path forward

Technology hiring teams that standardize workflows, modernize scheduling, deploy AI as operational infrastructure, and align metrics with execution reality will be best positioned to compete in 2026. In tech, hiring advantage now comes from discipline, reliability, and speed with confidence—not from adding more tools to an already complex system.

Manufacturing Recruiting in 2026: Key Stats and Trends

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

Manufacturing hiring teams enter 2026 with improved outcomes but rising operational strain. Hiring goal achievement increased in 2025, reaching the strongest level shown in the multi-year trend. However, this improvement occurred alongside mounting execution challenges that threaten sustainability.

The most prominent pressure point is recruitment team turnover, which leads all reported changes affecting candidate flow. At the same time, manufacturing leaders describe a fragmented talent market, with some roles becoming more competitive while others see increased availability. This split environment makes consistency harder to maintain and places greater demand on hiring systems and recruiter capacity.

Across the process, leaders report higher candidate demands, more required touchpoints, and increased dropout, signaling that speed and coordination now play a larger role in conversion. In response, manufacturing organizations are prioritizing efficiency, personalization, and technology upgrades as foundational capabilities for 2026.

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2025 performance review

Manufacturing hiring performance strengthened in 2025. The data shows a clear year-over-year increase in hiring goal achievement, reversing the prior year’s decline and marking the strongest result in the period shown.

This improvement is notable, but it does not signal reduced complexity. Instead, the performance gains appear to have been achieved under more demanding conditions, with teams absorbing higher workload, more variability in candidate quality, and greater internal disruption.

The takeaway is not that manufacturing hiring became easier, but that teams pushed harder and adapted, even as the operating environment grew more fragile.

Manufacturing hiring became harder to run, even as conditions diverged

Over the past year, manufacturing hiring has been shaped less by a single market shift and more by internal instability and rising execution demands. The most widely reported change is increased recruitment team turnover, which has directly affected teams’ ability to manage candidate flow. This stands above all other shifts and signals a loss of continuity at the exact moment hiring processes require more coordination and speed.

At the same time, the talent market itself has fractured. Nearly as many leaders say hiring became more competitive due to increased demand as those who say it became less competitive because more talent is available. Rather than moving in one direction, manufacturing hiring conditions now vary by role, location, and skill set, forcing teams to operate in multiple modes at once.

Candidate-side expectations have risen in parallel. Building meaningful relationships and connecting with candidates quickly both increased in importance, alongside growing candidate demands and the need for more touchpoints throughout the process. These pressures point to higher engagement requirements rather than easier access to committed talent.

The cumulative effect is visible in hiring speed. Time-to-hire lengthened for most manufacturing organizations, while only a small minority saw improvement. This slowdown aligns with the broader picture the data paints: manufacturing teams are managing more complexity with less stability, and even incremental delays now have outsized impact on outcomes.

Together, these signals describe a hiring environment where process resilience matters more than market timing. Manufacturing hiring has not simply become more competitive or less competitive. It has become harder to execute consistently under mixed conditions, higher expectations, and ongoing internal disruption.

Coordination breakdowns, not sourcing alone, slow manufacturing hiring

Manufacturing hiring bottlenecks concentrate in the interview and decision stages, where coordination breaks down most often. Interview cancellations and reschedules lead the list, followed closely by delays in hiring-manager decisions and a limited pool of available interviewers. These signals point to fragile handoffs and heavy reliance on busy stakeholders.

Lack of qualified candidates remains a meaningful constraint, but it sits alongside conversion issues such as candidate withdrawals and delayed scorecard completion. This indicates that hiring slows not only at the top of the funnel, but as candidates move through the process.

Scheduling delays, high application volume, and poor communication with candidates further compound these issues, increasing the risk of disengagement. Taken together, the data shows a hiring system strained by multiple dependencies, where improving reliability and follow-through is as important as expanding access to talent.

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Manufacturing teams apply AI where it reduces coordination and manual work

Automation and AI use in manufacturing centers on improving visibility, coordination, and consistency, rather than fully automating hiring decisions. Analytics and reporting lead all use cases, signaling a focus on understanding where hiring slows and how work is distributed.

Interview scheduling sits near the top, reflecting the operational pressure to reduce back-and-forth coordination. Content-related tasks follow closely, including writing job descriptions and creating interview questions, suggesting teams are using automation to standardize inputs and reduce preparation time.

Screening and sourcing applications form a broad middle tier. These uses help manage volume, but they do not dominate adoption in the same way operational tasks do. Interview intelligence and analysis also appear at similar levels, indicating growing interest in extracting insight from interviews, even if adoption is still uneven.

Candidate-facing automation and drafting candidate communications trail the rest, while screener interviews appear lowest. Overall, the pattern shows manufacturing teams using AI as workflow infrastructure, prioritizing time savings and process stability over high-risk automation of candidate interactions.

Manufacturing teams measure outcomes that reflect durability and conversion

Manufacturing hiring teams focus measurement on whether hires stick and offers convert, rather than on early-stage activity alone. Quality of hire leads all tracked metrics, indicating a strong emphasis on long-term fit and performance. Cost-per-hire, offer acceptance rate, and time-to-hire form the next tier, reflecting the dual pressure to control cost while moving quickly in a competitive environment. These measures sit at the intersection of efficiency and effectiveness, reinforcing that speed without conversion is not sufficient.

Diversity of candidates and employee turnover also appear prominently, signaling attention to workforce stability and composition beyond immediate hiring volume. Time-to-fill and application completion follow, suggesting growing but secondary interest in funnel mechanics.

Candidate interview experience and applicants per role trail the core outcome metrics, while source of hire appears lowest. Overall, the pattern shows manufacturing teams prioritizing results and sustainability over activity tracking, using metrics to evaluate whether hiring efforts produce durable outcomes rather than just throughput.

Manufacturing leaders expect volume, verification, and retention pressure in 2026

Looking ahead to 2026, manufacturing leaders anticipate a hiring environment defined by volume and complexity rather than pure scarcity. The most frequently expected challenge is an overwhelming number of applicants, signaling continued pressure on screening capacity and funnel management.

Just behind that top concern is a cluster of risk and retention issues. Retaining top talent and managing fake or fraudulent candidates rank at the same level, alongside skills that do not match resumes. Together, these responses point to growing concern about signal quality and trust in the hiring process.

Execution challenges remain prominent. New hires failing to show up, candidates dropping out mid-process, and limitations of current hiring technology all feature strongly, reinforcing that conversion and follow-through are expected to remain fragile.

A lack of qualified candidates appears, but it no longer stands alone as the dominant expected issue. Instead, it sits among a broader set of operational and verification challenges. Hybrid work complexity, recruiter workload, and internal policy changes round out the list, suggesting that 2026 risk is distributed across many points in the system, rather than concentrated in a single bottleneck.

Overall, manufacturing leaders appear to be preparing for a year where managing volume, validating candidates, and retaining talent will require as much attention as sourcing itself.

Priorities for 2026 center on conversion, automation, and technology investment

Manufacturing leaders are entering 2026 with a clear improvement agenda focused on converting candidates more reliably and reducing friction across the hiring process. The top area of focus is increasing offer acceptance, signaling that getting candidates across the finish line is a bigger concern than generating initial interest.

Automation and technology upgrades sit immediately behind that top priority. Optimizing automation, upgrading hiring technology, and using AI to improve efficiency all rank near the top, indicating that manufacturing teams view tooling as a necessary lever to handle volume, speed, and coordination challenges.

Candidate experience and time-to-hire also feature prominently, reinforcing that engagement and speed are tightly linked. Standardizing the hiring process and increasing personalization follow, suggesting a push toward consistency without fully sacrificing flexibility.

Cost reduction and scheduling-specific improvements appear lower, indicating that manufacturing teams are prioritizing effectiveness before efficiency gains at the margins.

That prioritization is reinforced by investment intent. Most manufacturing organizations indicate they are likely or very likely to invest in additional hiring technology to increase efficiency in 2026. Neutral or negative sentiment is minimal, underscoring a broad consensus that existing systems are insufficient for the demands ahead.

Together, these signals point to a sector that is not experimenting cautiously, but actively preparing to modernize hiring operations to support higher expectations, heavier volume, and more complex decision-making.

Final thoughts and key takeaways for manufacturing hiring leaders

Stability matters as much as talent access.
Recruitment team turnover is the most disruptive force shaping manufacturing hiring today. Even as hiring outcomes improved in 2025, instability inside TA teams makes it harder to sustain progress. Process reliability and knowledge continuity are now strategic assets.

Fragmented markets demand flexible execution.
Manufacturing hiring is no longer uniformly competitive or relaxed. Leaders report both increased competition and increased talent availability, depending on role and location. Teams that rely on a single hiring motion struggle; those that can adapt speed, screening rigor, and engagement by role are better positioned to convert candidates.

Coordination failures are the biggest drag on speed.
Interview cancellations, limited interviewer availability, and delayed decisions outweigh sourcing alone as bottlenecks. Improving follow-through in the interview stage unlocks more value than expanding the top of the funnel.

Engagement is about momentum, not messaging.
Candidates require faster connection, more touchpoints, and clearer progress signals. Dropout rises when coordination falters. Manufacturing teams see better engagement when they remove delays rather than add personalization.

Use AI to harden workflows, not replace judgment.
Manufacturing teams are applying AI most effectively where it improves visibility, scheduling, preparation, and consistency. These uses reduce recruiter load and stabilize execution without introducing risk into candidate-facing decisions.

Measure what holds up over time.
Quality of hire, offer acceptance, time-to-hire, and turnover dominate manufacturing measurement for a reason. These metrics reveal whether hiring decisions convert and endure, not just whether activity occurred.

Modernization is no longer optional.
Manufacturing leaders are prioritizing automation, technology upgrades, and efficiency improvements because existing systems cannot absorb higher volume, verification risk, and execution complexity. Investment intent is strong because operational strain is real.

The path forward

Manufacturing hiring success in 2026 will depend less on market relief and more on system design. Teams that protect recruiter continuity, stabilize interview coordination, deploy AI as workflow infrastructure, and align metrics with durable outcomes will be best positioned to hire consistently in a fragmented, high-pressure environment.

Financial Services Hiring Trends and Stats for 2026: What Leaders Need to Know

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

Financial services hiring teams enter 2026 under sustained pressure from execution complexity, rising candidate risk, and tighter timelines. While hiring outcomes improved in 2025, the sector’s core challenge is no longer demand alone—it is moving candidates through a slow, risk-sensitive hiring process without sacrificing quality or credibility.

Time-to-hire continues to worsen for most organizations, driven by fragile coordination in the middle of the funnel. Scheduling delays, inconsistent interviewer readiness, and slow decision cycles compound quickly in a sector where candidates often juggle multiple offers and prolonged timelines increase both drop-off and compliance risk. Even with better goal attainment, execution speed has not stabilized—leaving recent gains exposed.

At the same time, the threat landscape is shifting. Fraudulent or AI-assisted candidate misrepresentation has become a material concern, forcing teams to apply greater scrutiny while still moving faster. This tension between speed and rigor now defines financial services hiring.

In response, leaders are prioritizing efficiency-first modernization. AI adoption is widespread, but impact depends on deployment. The most effective teams use AI as infrastructure—strengthening analytics, interview quality, and workflow reliability—rather than chasing speed through surface-level automation. Scheduling, despite being a primary source of delay, remains under-automated and represents one of the clearest opportunities for 2026.

The data points to a widening divide. Teams that modernize scheduling, standardize communication, and align AI with core workflow mechanics are better positioned to compete, regardless of market conditions. Those that rely on manual coordination and fragmented processes continue to absorb delay, risk, and candidate loss.

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2025 performance review: Financial services hiring shows improvement, but remains fragile

Financial services hiring performance improved in 2025, with organizations achieving 60% of hiring goals, the sector’s strongest result in four years. After declining to 49% in 2024, this rebound signals meaningful progress and places financial services ahead of several other industries still struggling to regain momentum.

Yet even with this improvement, performance remains structurally constrained. At 60% attainment, financial services organizations are still leaving a significant share of planned roles unfilled — a notable risk in a sector that depends on specialized skills, regulatory rigor, and consistent execution.

The volatility of recent years underscores the challenge. Hiring goal attainment rose in 2023, slipped in 2024, and then rebounded sharply in 2025, reflecting how sensitive outcomes are to execution quality. When scheduling breaks down, interviewer readiness falters, or decisions slow, performance regresses quickly.

The 2025 rebound appears driven less by easing market conditions and more by incremental operational gains. As this chapter will show, organizations that improved scheduling discipline, tightened communication, and invested in AI-supported workflows were better positioned to convert candidate interest into completed hires.

The implication for 2026 is clear: financial services hiring is improving, but not yet durable. Sustaining progress will require continued focus on execution systems (not just demand conditions) to prevent recent gains from proving temporary.

Time-to-hire continues to constrain financial services hiring

Even as hiring outcomes improved in 2025, time-to-hire remains a structural constraint for financial services teams.

The data shows that hiring speed continues to move in the wrong direction for many organizations, with only a minority managing to meaningfully accelerate their processes. For most teams, hiring either slowed or failed to improve, reinforcing that execution challenges remain unresolved beneath the surface of better goal attainment.

This matters acutely in financial services, where hiring processes are often layered, risk-sensitive, and dependent on senior stakeholder availability. When interview coordination falters or feedback loops stall, delays compound quickly, increasing candidate drop-off and weakening competitive position.

The gap between improving outcomes and lagging execution speed suggests that recent gains are fragile. Some organizations are clearly finding ways to stabilize and accelerate hiring, but they remain the exception rather than the rule.

Where hiring execution breaks down

The most common breakdowns occur in the middle of the hiring process, where scheduling delays, slow decision-making from hiring managers, and interviewer availability issues converge. These are not isolated frictions; they compound. When calendars don’t align or feedback stalls, candidates wait, withdraw, or accept competing offers.

Candidate-side challenges remain present, including a lack of qualified applicants and rising withdrawals mid-process. But the data suggests these issues are often downstream effects of internal delays rather than primary causes. As timelines stretch, even strong candidates disengage.

Interviewer readiness is another critical fault line. Limited interviewer pools, untrained or underprepared interviewers, and delays in completing scorecards all contribute to uneven evaluation and slower movement. In a sector that values rigor and risk management, these inconsistencies create both speed and quality concerns.

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AI adoption emphasizes insight over speed in financial services

Financial services hiring teams are applying AI primarily to strengthen evaluation and decision-making, not simply to accelerate volume.

Adoption is strongest in interview intelligence, analytics, and interview preparation, areas where consistency, rigor, and defensibility matter most. This reflects the sector’s need to balance faster hiring with careful signal validation in a high-stakes environment.

More transactional use cases, such as sourcing, screening, and candidate-facing automation, are used more selectively. Notably, scheduling shows lower AI adoption than evaluative tasks, despite being a major source of delay elsewhere in the data.

The pattern points to a mature but incomplete AI strategy. Financial services teams are using AI to improve judgment, but many have yet to fully extend it to the workflow mechanics, especially scheduling, where it could deliver meaningful speed without sacrificing quality.

What financial services teams choose to measure

The metrics financial services teams prioritize reveal a balanced but still evolving measurement strategy.

Quality of hire sits clearly at the center of measurement, reflecting the sector’s emphasis on long-term performance, risk mitigation, and defensible hiring decisions. This focus aligns with growing concern about candidate misrepresentation and reinforces why evaluation rigor remains non-negotiable.

Alongside quality, teams track a mix of efficiency and cost signals. Application completion and cost-per-hire point to awareness of funnel friction and budget pressure, while time-based metrics such as time-to-hire and time-to-fill indicate continued concern about execution speed, even if improvement has been uneven.

Operational stability also features prominently. Metrics tied to employee turnover and source of hire suggest that financial services leaders are watching not just how hires are made, but whether they stick and perform over time.

Overall, the data shows a sector that measures what it feels accountable for: quality, cost, and stability. The opportunity for 2026 is to more tightly connect these metrics to execution drivers, using funnel health and experience signals as earlier indicators, not just retrospective checks.

2026 outlook: Faster hiring, higher risk, and tighter margins for error

Financial services leaders expect 2026 to be defined by speed under pressure.

The dominant shift is the growing importance of connecting with candidates quickly. As competition for specialized talent remains intense, slow engagement is increasingly viewed as a direct cause of lost hires. Speed is no longer just an efficiency goal; it is a competitive requirement.

At the same time, leaders anticipate rising internal strain. Recruiter turnover, expanding candidate demands, and a growing number of required touchpoints are expected to make candidate flow harder to manage. These pressures compound existing execution challenges, particularly around scheduling, interviewer readiness, and decision follow-through.

The expected challenges reinforce this tension. Alongside familiar issues like talent availability and candidates holding multiple offers, candidate fraud and AI-assisted misrepresentation stand out as a growing concern. This adds a new layer of risk, forcing teams to balance faster movement with stronger signal validation. Inefficient or untrained interviewers and limitations in current hiring technology further threaten consistency at scale.

Notably, the outlook reflects a fragmented market. Some leaders expect competition to intensify, while others anticipate easing conditions due to increased talent availability. The implication is clear: market conditions will vary, but execution quality will determine outcomes.

For financial services teams, 2026 will reward those that can move faster without sacrificing rigor:  modernizing workflows, stabilizing coordination, and reinforcing trust at every stage of the hiring process.

Where financial services leaders are investing for 2026

Financial services hiring priorities for 2026 reflect a clear shift toward execution discipline powered by technology.

Leaders are focused first on making hiring more efficient through AI and automation. Rather than experimenting at the margins, teams are looking to apply AI more deliberately to improve how work gets done, reducing manual coordination, stabilizing workflows, and enabling faster, more consistent decision-making. This emphasis reinforces a theme seen throughout the chapter: efficiency gains are no longer optional, but foundational.

Candidate experience remains a close second, with personalization, speed, and reliability at the center. Importantly, these goals are not positioned as soft initiatives. Improving experience is tightly linked to improving time-to-hire, offer acceptance, and candidate follow-through, especially in a market where top talent has leverage.

Standardization also rises as a priority. Financial services leaders are signaling the need to reduce variability across interviewers, processes, and timelines, particularly as concerns around candidate misrepresentation and interviewer readiness grow. Standardized processes are increasingly viewed as a safeguard for both speed and quality.

These priorities are backed by strong intent to invest. Financial services organizations overwhelmingly expect to increase technology investment to support hiring efficiency, reinforcing that modernization efforts in 2026 will be resourced—not aspirational.

Taken together, the direction is clear. Financial services teams are moving away from fragmented, people-dependent execution toward system-led hiring operations. Those that successfully align AI, automation, and standardized workflows will be best positioned to hire faster, manage risk, and sustain the gains achieved in 2025.

Key takeaways for financial services leaders

Financial services hiring is improving, but the margin for error is shrinking. The data points to a sector that can no longer rely on incremental gains or favorable market shifts to meet hiring needs. Execution quality now determines outcomes.

Speed is the new baseline, not a differentiator.
Candidates expect rapid movement, clear timelines, and minimal friction. Teams that cannot coordinate interviews, feedback, and decisions quickly will continue to lose qualified talent, regardless of brand or compensation.

Efficiency must be designed into the system.
Manual scheduling, inconsistent interviewer readiness, and fragmented communication are structural liabilities. Leaders should prioritize workflow modernization that reduces coordination work and stabilizes execution across roles and regions.

AI delivers the most value when it strengthens judgment.
Financial services teams are right to focus AI on evaluation, analytics, and consistency. The next opportunity is extending those gains to operational mechanics where AI can accelerate hiring without compromising rigor.

Standardization protects both speed and quality.
As concerns about candidate misrepresentation grow, standardized interviews, clearer scorecards, and disciplined processes become essential. Consistency is no longer just an efficiency play. It’s a risk-management strategy.

Candidate experience follows execution health.
Personalization and relationship-building matter, but they cannot compensate for slow or unreliable processes. Improving experience in financial services starts with predictable timelines, transparent communication, and momentum.

2026 will reward disciplined operators.
Market conditions may fluctuate, but teams that invest in technology, reinforce execution discipline, and align speed with scrutiny will be best positioned to sustain hiring gains and build resilient talent pipelines.

The path forward

For financial services leaders, the next phase of hiring advantage will come from operational precision. Teams that modernize scheduling and communication, apply AI to strengthen—not replace—human judgment, and enforce consistent standards across regions will move faster without increasing risk. In a sector where trust and execution are inseparable, disciplined systems will be the difference between incremental improvement and durable hiring performance.

Retail Recruiting in 2026: Key Trends, Challenges, and Insights

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

Retail hiring teams enter 2026 under sustained operational pressure. Across the retail hiring lifecycle, delays compound quickly. Limited interviewer availability, heavy recruiter and manager workload, and coordination breakdowns continue to slow hiring cycles and increase candidate drop-off. At the same time, signal-quality issues, such as skills misalignment and candidate misrepresentation, make it harder to confidently assess fit at scale.

Retail leaders are responding with a sharper focus on efficiency. Improving overall efficiency leads 2026 priorities, followed closely by upgrading hiring technology and optimizing automation. AI adoption is pragmatic and execution-driven, concentrated in analytics, reporting, scheduling, and screening—areas that improve visibility and speed without replacing human judgment.

How retail teams measure success reflects this mindset. Leaders prioritize metrics that reveal funnel friction and downstream outcomes, including application completion rate, quality of hire, offer acceptance, turnover, and time-to-hire. Looking ahead, continued capacity strain and rising complexity mean retail hiring success in 2026 will depend on strengthening workflow resilience rather than adding more volume.

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2025 performance review

Retail hiring performance continued to lag behind organizational needs. Despite incremental improvements in tooling and automation, most retail teams still missed hiring goals, reflecting how difficult it has become to sustain hiring velocity at scale.

Extended time-to-hire emerged as a defining issue. As hiring cycles lengthened, retail teams faced compounding consequences: higher candidate drop-off, lost seasonal talent, and added pressure on store leaders to operate understaffed locations. In an industry where speed directly impacts revenue and customer experience, slow hiring has become a material business risk.

Key challenges: Candidate scarcity, misrepresentation, and execution strain

Retail hiring challenges are increasingly driven by signal quality and volume, not just talent availability.

The most common issue retail leaders report is skills misalignment (applicants whose capabilities don’t match their resumes) followed closely by a lack of qualified candidates. High application volume compounds the problem, forcing recruiters to filter more noise while still struggling to identify job-ready talent. Ongoing retention pressure keeps teams in near-constant backfill mode, limiting stability.

Execution strain adds another layer. Fake or misrepresented candidates, limitations in hiring technology, and policy changes slow decision-making and reduce predictability. Candidates juggling multiple offers, no-shows, and drop-off further increase friction when processes stall.

Overall, the chart shows that retail hiring is constrained less by sourcing reach and more by signal clarity, execution discipline, and system reliability.

Scheduling and communication bottlenecks

Retail’s bottlenecks are first and foremost capacity bottlenecks, then coordination bottlenecks.

The top constraint retail leaders cite is a limited pool of available interviewers, which makes it difficult to move candidates through the funnel quickly, especially when store operations compete for the same time. Just behind that, retail teams are dealing with candidate-side and volume pressures: a lack of qualified candidates and too many applications to review. That combination forces recruiters to sift through more noise while still struggling to find true fit.

Communication and coordination issues still matter, but they show up as the next layer of friction. Poor communication with candidates ranks among the top bottlenecks, and downstream execution blockers, like delays in completing scorecards, interview cancellations or reschedules, and scheduling delays, compound the impact of limited interviewer capacity. Availability continues to be a theme: interviewer/hiring manager availability and delays from hiring managers in making decisions (26%) both reinforce how easily retail hiring stalls when the process depends on busy, distributed stakeholders.

The takeaway is clear: in retail, speed breaks down less because of a single scheduling tool gap, and more because interviewer capacity and decision follow-through can’t keep up with volume. The most effective fixes pair structured availability and scheduling workflows with clear accountability for feedback and decisions, so candidates aren’t left waiting long enough to withdraw.

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Technology adoption and the role of AI in retail hiring

Retail hiring teams are using AI most heavily where it helps them see and move the process faster—not necessarily where it replaces human judgment.

The strongest adoption shows up in analytics and reporting, signaling that retail leaders are increasingly relying on AI to understand funnel health, spot slowdowns, and manage high-volume hiring more effectively. Close behind are interview-related use cases, including generating interview questions and coordinating interview scheduling, reflecting how much of retail hiring pressure sits in the middle of the funnel rather than at sourcing alone.

Retail teams are also applying AI to resume review, screening, and interview intelligence, indicating a growing focus on improving signal quality and consistency when volume is high. Candidate-facing automation, such as conversational AI and drafting communications, appears more selectively adopted, suggesting that many retail organizations are cautious about automating direct candidate interaction too aggressively.

Overall, the data reflects a pragmatic approach to AI in retail. Teams are using technology first as workflow infrastructure and decision support, not as a wholesale replacement for recruiters or hiring managers. The retail organizations seeing the most value are those aligning AI investment with their core realities like speed, volume, and limited recruiter bandwidth, while keeping human oversight where it matters most.

Metrics retail teams prioritize

Retail hiring teams are measuring what helps them manage volume, quality, and funnel health—not just cost control.

The most commonly tracked metrics focus on early-funnel effectiveness and downstream outcomes. Application completion rate sits at the top, reflecting how critical it is for retail teams to understand where candidates drop out in a high-volume environment. Close behind is quality of hire, signaling that even in fast-paced retail hiring, teams are prioritizing long-term fit and performance rather than speed alone.

A second tier of metrics centers on conversion and stability. Offer acceptance rate, applicants per role, employee turnover, and time-to-hire are all widely measured, underscoring how retail leaders are trying to balance hiring velocity with retention and workforce continuity. These metrics help teams diagnose whether hiring slowdowns stem from candidate hesitation, role attractiveness, or internal execution issues.

Candidate experience metrics and cost-per-hire appear less dominant, suggesting that while experience and cost matter, they are often viewed as supporting indicators rather than primary decision drivers. Time-to-fill trails further behind, reinforcing that retail teams are more focused on keeping the funnel moving than on measuring the full end-to-end vacancy window.

Overall, the chart shows a pragmatic measurement strategy. Retail teams are tracking the metrics that reveal friction, drop-off, and hire quality across a large funnel, prioritizing operational visibility over purely financial optimization.

2026 outlook for retail hiring

Retail leaders expect 2026 to be defined by execution complexity and operating-model strain, rather than a single dominant hiring obstacle.

The most frequently anticipated challenges cluster around how retail hiring is run day to day. Difficulty adapting hiring processes to remote or distributed environments and unmanageable recruiter workloads rise to the top, signaling continued pressure on team capacity and process design. These concerns sit alongside persistent signal-quality issues, including applicants whose skills do not match their resumes and an ongoing lack of qualified candidates.

Brand and infrastructure limitations also feature prominently. Many retail leaders anticipate challenges tied to employer branding and limitations in their current hiring technology, suggesting that existing systems may struggle to support hiring at the required speed and scale. At the same time, concern about fake or misrepresented candidates points to a growing need to verify authenticity without adding friction to already stretched processes.

Overall, the outlook reflects a retail hiring environment where success in 2026 will hinge on process resilience, recruiter capacity, and execution discipline across the funnel.

2026 priorities: technology upgrades remain the top focus

Retail hiring priorities for 2026 are tightly centered on making hiring work better at scale.

Improving overall efficiency clearly leads the agenda, reinforcing that retail teams see speed, throughput, and reduced friction as the most urgent needs. Upgrading hiring technology and optimizing automation follow closely, signaling that leaders view tech investment as a primary lever for achieving those efficiency gains,not as a secondary support.

Cost control and smarter use of AI also feature prominently, reflecting pressure to do more with constrained recruiter capacity while improving consistency across high-volume roles. At the same time, personalization, standardization, and incremental time-to-hire improvements appear as meaningful but secondary priorities, suggesting that retail teams are balancing flexibility with the need for repeatable, reliable processes.

Nearly all retail organizations expect to invest in additional hiring technology in 2026, underscoring broad confidence that modernization, particularly around efficiency, automation, and workflow support, will be central to staying competitive in the year ahead.

Final thoughts and key takeaways for retail hiring leaders

Focus on capacity before volume. Limited interviewer availability and recruiter workload are the primary constraints in retail hiring. Protecting hiring time, clarifying interviewer accountability, and structuring availability unlock more value than adding applicants.

Treat scheduling as a system, not a task. Interview coordination remains one of the biggest drivers of delay and candidate drop-off. Automated scheduling, self-service rescheduling, and standardized availability are now foundational capabilities for retail teams.

Use AI to improve visibility and speed—not to replace judgment. Retail teams see the greatest gains when AI supports analytics, reporting, scheduling, and screening. These use cases strengthen decision-making and execution without eroding human oversight.

Measure funnel health and outcomes, not just activity. Application completion, quality of hire, offer acceptance, turnover, and time-to-hire provide earlier and more actionable signals than cost or raw volume metrics.

Modernize communication to reduce drop-off and risk. Centralized, consistent candidate communication improves response times, reduces confusion, and mitigates compliance risk in a mobile-first hiring environment.

Strengthen defenses against candidate misrepresentation. As AI-assisted or misrepresented candidates become more common, retail teams must reinforce skill validation and structured evaluation without slowing the process.

The path forward

Retail teams that modernize scheduling, centralize communication, deploy AI as workflow infrastructure, and align measurement with quality and funnel health will be best positioned to hire reliably in 2026. In retail, hiring success is no longer about doing more; it is about building systems that hold up under pressure.

TA Leaders Reveal How to Win Top Talent in 2026

Editor’s note: The article below is an excerpt from GoodTime’s 2026 Hiring Insights Report. The entire report is available to view online for free here.

As talent teams look toward 2026, the path to winning top talent is defined less by sourcing volume and more by operational discipline. Rising candidate expectations, concerns about authenticity, and persistent workflow bottlenecks have pushed organizations to rethink how hiring should function. And after a year marked by strain, leaders enter 2026 with remarkable alignment on what must change.

The data shows that modernization is no longer optional. 91% of TA leaders plan to invest in additional hiring technology, and AI adoption has reached a pivotal threshold: 99% of teams now use, pilot, or plan to use AI agents. With this shift, hiring is entering an era where speed, clarity, and system-level intelligence determine competitive advantage.

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New pressures redefine how teams compete in 2026

Fake and fraudulent candidates become the #1 anticipated challenge

For the first time, TA leaders say fake or AI-misrepresented candidates pose the single biggest threat to hiring this year. 27% expect fraudulent candidates to be a top challenge, narrowly edging out the 26% who cite a lack of qualified talent.

This shift signals a profound change in the hiring environment. As generative AI raises the floor of resume quality and candidate presentation, teams must increase their focus on skill validation, structured interviews, and identity assurance. The challenge is no longer just finding talent—it’s confirming authenticity.

“Resumes, answers to application questions, even online portfolios—core data points in assessing candidate quality not so long ago —have all lost value in the era of GenAI. It’s one of the most urgent tasks of TA teams today to find methods of assessment which are suitable for this era. We’re seeing much greater use of synchronous assessments for skills, traits and behaviours, as well as (somewhat ironically) the return of in-person interviews.”
-Hung Lee, Founder, Recruiting Brainfood

Why tech limitations persist despite widespread adoption

Despite near-universal adoption of hiring technology, 26% of leaders still expect tech limitations to be a major barrier in the coming year. The issue isn’t access to tools—it’s how those tools function in practice.

Many organizations now rely on fragmented tech stacks made up of point solutions that don’t work together cleanly. Instead of reducing effort, these systems introduce more handoffs, data silos, and manual coordination. Automation often exists in pieces, but recruiters are still left to connect workflows, manage scheduling, chase feedback, and maintain candidate communication across platforms.

Compounding this, limited visibility into bottlenecks makes it harder to diagnose and fix delays before they escalate. When technology doesn’t clearly surface where hiring slows down, teams end up reacting to problems rather than preventing them.

In short, tech becomes a constraint when it adds complexity instead of removing it, especially as hiring speed and candidate expectations continue to rise.

“To successfully leverage AI, you need individuals who dare to disrupt and challenge your existing hiring processes. You can no longer achieve great results by adhering to rigid legacy processes — you need innovators who understand the rules well enough to know how to break them.”
-Anastasia Pshegodskaya, Global Director, Talent Acquisition, Remote

Rising candidate expectations and dropout risks intensify

Candidates expect immediate responses, flexible scheduling, and mobile-friendly communication. When teams fall behind, dropout rates spike. Leaders anticipate these pressures increasing, making responsiveness and process clarity key differentiators in 2026.

Recruiter turnover threatens continuity

Turnover within TA teams is expected to disrupt candidate flow and reduce operational stability. As workloads fluctuate and hiring needs rise, teams must build systems that maintain consistency even when people transition.

TA leaders anticipate uneven hiring conditions in 2026

One of the clearest signals in the 2026 data is not consensus, but contextual divergence in how hiring conditions are expected to evolve.

While 45% of TA leaders expect the hiring landscape to become more competitive due to increased demand for talent, nearly as many (41%) believe it will become less competitive as talent availability increases. Rather than signaling confusion or contradiction, this split reflects the reality that hiring conditions are increasingly uneven across roles, skills, and labor pools.

In practice, this suggests that competition in 2026 will be more situational than universal. Some teams, particularly those hiring for scarce, high-impact, or specialized roles, are likely to face intense competition and sustained pressure on speed. Others will contend with larger candidate pools that still require careful screening, faster decision-making, and stronger process discipline to convert interest into hires.

The takeaway is not that the hiring market is moving in two directions at once, but that there is no single hiring market anymore. Conditions will vary meaningfully depending on what roles organizations are hiring for, where those roles sit, and how efficiently teams can move candidates through the process.

As a result, speed, clarity, and execution discipline matter regardless of whether talent is scarce or abundant. Teams that move slowly or inconsistently risk losing candidates either to faster competitors or to disengagement.

What TA teams are prioritizingin 2026

The priorities for the year ahead reveal a discipline-focused mindset. Leaders are no longer trying to “add more candidates” to the top of the funnel. Instead, they are focused on fixing the entire system.

Improving efficiency is the top priority

Organizations overwhelmingly cite efficiency as their top focus for 2026. Speed is no longer just a metric; it’s a core capability. The teams that move fast are the ones that will win candidates who often hold multiple offers.

Upgrading hiring technology

With 91% planning new tech investments, modernization is accelerating. Teams are prioritizing:

  • Automated scheduling
  • Centralized communication
  • Analytics and bottleneck detection

In other words, the age of patchwork workflows is ending and end-to-end connected systems will take their place.

“When you think about how we translate that hospitality mindset into our candidate interviewing, having a really rock-solid scheduling platform and tools is really important to deliver the experience we’re looking for.”
-Jeff Moore
VP of TA Operations and Workspaces, Toast

Elevating the candidate experience through speed and flexibility

Candidate experience has evolved. Personal touches matter, but not as much as frictionless movement through the process. The top features companies offered to improve the candidate experience included:

  • Self-scheduling and self-rescheduling
  • Transparent, automated updates
  • Fast interview-to-offer timelines
  • Mobile-first communication

Today’s candidates judge employers largely on whether the hiring process feels modern, predictable, and respectful of their time.

Speed becomes the primary differentiator

Fast interview-to-offer processes are now one of the strongest predictors of acceptance. Teams that can move candidates forward without delay create a competitive advantage.

Self-service scheduling becomes standard

With 53% offering self-rescheduling and 41% using automated scheduling, candidates expect flexibility and control. These capabilities reduce friction and lower dropout rates across the funnel.

Transparency drives trust

More than ever, candidates expect real-time visibility into where they stand. Automated updates reduce uncertainty—and demonstrate operational maturity.

Mobile-first communication is universal

Texting and WhatsApp are now part of every team’s communication toolkit. What differentiates organizations is whether those channels are centralized, compliant, and consistent.

AI’s ever-expanding role in talent acquisition

One of the more interesting signals in the data is where AI adoption has concentrated, and where it hasn’t.

TA teams are most likely to apply AI to tasks where value is clear, risk is low, and outputs are easy to validate. Analytics and reporting (45%), interview question generation (42%), and interview intelligence (39%) all rank at the top, use cases where AI augments decision-making without replacing human judgment.

By contrast, even some of the most operationally straightforward uses of AI remain under-adopted. Interview scheduling stands out as the clearest missed opportunity: it’s widely understood, low-risk, and directly tied to the biggest bottlenecks teams face today. Scheduling is often the best place to start with automation because it delivers immediate efficiency gains without introducing new decision-making risk.

“AI agents handle orchestration, not just execution — leveraging data and insights to make more informed decisions. We’ve been able to cut our scheduling time from 30 minutes to five.”
-Tiffany Clark, Head of HR Strategy & Shared Services, S&P Global

The pattern is telling: teams are embracing AI fastest where it provides insight without requiring structural change, and moving more cautiously where adoption would force deeper workflow redesign. As AI becomes infrastructure rather than experimentation, the next wave of differentiation will come from teams willing to rebuild processes, not just layer intelligence on top of them.

AI-powered scheduling gains strategic importance

With scheduling still the largest operational tax in hiring, AI-powered coordination continues to differentiate faster teams from slower ones. Automated scheduling (already a strong predictor of higher goal attainment) is becoming a core mechanism for reducing delays, protecting candidate engagement, and supporting faster interview-to-offer decisions in the year ahead.

“Recruiters aren’t slow—scheduling is. Until companies adopt systems that absorb complexity instead of pushing it onto humans, scheduling will remain the single biggest bottleneck in hiring.”
-Shelby Wolpa, Founder, Shelby Wolpa Consulting

The metrics that matter in 2026

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Quality of hire leads all metrics

Quality of hire is now the most tracked metric at 42%, and the most prioritized, with 22% naming it their top measure of success. As candidate authenticity becomes harder to assess, quality signals become more vital.

“The real competitive advantage will be applying AI in ways that drive quality: quality of process and hire. By quality of hire, we mean improving the rigor of our assessment, accuracy of our decision making, and ultimately, the success of the hires that we make relative to historical benchmarks.”
-Ben Sesser, Co-Founder, BrightHire

Efficiency metrics gain momentum

Teams are still prioritizing key efficiency measures:

  • Time-to-hire (37%)
  • Offer acceptance rate (36%)
  • Application completion rate (38%)

These metrics give leaders earlier warnings and clearer insight into when slowdowns or gaps begin to form.

The bottom line: How teams will win talent in 2026

The data reveals a clear blueprint for success:

1. Build AI-first workflows

AI should orchestrate scheduling, detect delays, surface insights, and simplify complexity throughout the hiring process.

2. Modernize scheduling and remove manual coordination

Automation must replace back-and-forth messaging, fragmented calendars, and human bottlenecks.

3. Strengthen verification and assessment

With fake candidates on the rise, structured interviews, skills tests, and identity protocols are essential.

4. Standardize processes for consistency and scale

Standardization reduces confusion, speeds decision-making, and improves measurement.

5. Redesign TA roles to maximize human value

Free teams from administrative burden and shift focus toward relationships, advisory work, and better hiring decisions.

The takeaway

Winning top talent in 2026 requires precision, speed, and a new level of operational discipline. As candidate authenticity becomes harder to evaluate and expectations rise across the funnel, competitive advantage shifts toward teams that automate intelligently, measure what matters, and eliminate friction at every step.

Organizations that modernize now—adopting AI-driven workflows, upgrading communication systems, and prioritizing quality of hire—will be the ones best positioned to hire confidently in a challenging and rapidly evolving hiring landscape.

Retail Sector Overcomes Hiring Hurdles with AI, GoodTime Report Shows

The 2024 Hiring Insights Report: Retail Edition by GoodTime highlights the retail sector’s strategic use of AI and automation to enhance hiring efficiency and candidate experience in a competitive market.

San Francisco – April 4, 2024

Today, GoodTime released its 2024 Hiring Insights Report: Retail Edition, providing an in-depth look at how retail talent acquisition (TA) teams leveraged technology to navigate hiring challenges.

Despite a competitive landscape and evolving work models, retail businesses achieved a 23% lift in hiring goal attainment in 2023. The report, sourced from 105 HR and TA professionals in the sector, illustrates a shift towards technology to streamline hiring processes and improve the overall candidate experience.

Key findings from the report:

  • 99% of retail TA teams have integrated automation or AI into their hiring processes.
  • Retail hiring goal attainment jumped up to 57.7% in 2023 (versus 46.8% the year prior), ranking among the highest of all sectors.
  • Major challenges include talent retention, adapting to hybrid work models, and managing compensation expectations.
  • 91% of retail TA leaders plan to increase investment in hiring technology in 2024.

Retail’s strategic response:

Facing a shortage of workers and struggles with talent retention, the sector’s TA leaders have:

  • Enhanced use of AI for tasks like application screening and interview scheduling.
  • Focused efforts on improving candidate experiences and streamlining interview processes.
  • Standardized hiring processes to ensure efficiency and fairness.

“In retail, where companies need to hire quality workers at a high volume, adapting processes is not just a necessity but an art,” said Ahryun Moon, CEO & Co-Founder of GoodTime. “This year’s report illuminates how a sector deeply impacted by shifting consumer behaviors and the digital revolution is ingeniously harnessing AI and automation. These tools are not only being used to accelerate the pace of hiring, but also to refine the art of identifying and nurturing talent that meets the needs of today’s fast-paced, customer-centric world.”

To download the full report, visit goodtime.io.

About GoodTime

GoodTime helps talent acquisition teams hire up to 50% faster by automating interview scheduling, candidate communications, and more. Hundreds of the world’s leading companies including Slack, Sony Interactive Entertainment, Lyft, Shopify, and HubSpot trust GoodTime to accelerate their hiring process while maintaining a best-in-class candidate experience.

With advanced features like multi-day and panel interview scheduling, SMS and WhatsApp communication, workflow automation, intelligent interviewer selection, and powerful data and benchmarking reports, we’re helping enterprise companies cut their time-to-hire in half.

Learn more at goodtime.io.

Media Contact

For more information or to arrange an interview with Ahryun Moon, please contact:

Jake Link

press@goodtime.io

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Manufacturers Fight Hiring Challenges with AI, Finds GoodTime Report

The 2024 Hiring Insights Report: Manufacturing Edition from GoodTime highlights how the sector is embracing AI and automation to navigate a hiring landscape marked by labor shortages, a surge in specialized talent needs, and evolving work models.

San Francisco – March 26, 2024

Today, GoodTime released its 2024 Hiring Insights Report: Manufacturing Edition, revealing how talent acquisition (TA) teams in the manufacturing sector have turned to technology to counter hiring challenges.

Amidst a surge in specialized talent demands, particularly for roles like software engineers, the manufacturing sector achieved 44.3% of their hiring goals on average in 2023. The report, based on insights from 105 HR and TA professionals in the sector, shows a shift towards embracing technology to optimize hiring efficiency and improve candidate experience.

Key findings from the report:

  • 100% of manufacturing TA teams surveyed used some form of automation or AI.
  • 86% of TA leaders in the sector plan to invest in more hiring technology in 2024.
  • Persistent challenges include adapting to remote work, managing compensation expectations, and talent retention.
  • 38% of manufacturing companies reported layoffs in 2023.

Manufacturing’s strategic response:

In the face of massive hiring hurdles, the sector’s TA leaders have:

  • Integrated AI and automation in areas like resume screening and interview scheduling.
  • Enhanced the candidate experience and interview scheduling process.
  • Standardized hiring processes for improved efficiency and fairness.

“Manufacturing companies are not just adapting, but innovating at an impressive rate,” said Ahryun Moon, CEO & Co-Founder of GoodTime. “It’s a sector where balancing technological advancements with the human element isn’t just a strategy – it’s a necessity. This pivot towards AI and smarter hiring processes isn’t just about keeping pace; it’s about setting a new standard for how we approach talent acquisition in an industry known for its resilience and ingenuity.”

To download the full report, visit goodtime.io.

About GoodTime

GoodTime helps talent acquisition teams hire up to 50% faster by automating interview scheduling, candidate communications, and more. Hundreds of the world’s leading companies including Slack, Sony Interactive Entertainment, Lyft, Shopify, and HubSpot trust GoodTime to accelerate their hiring process while maintaining a best-in-class candidate experience.

With advanced features like multi-day and panel interview scheduling, SMS and WhatsApp communication, workflow automation, intelligent interviewer selection, and powerful data and benchmarking reports, we’re helping enterprise companies cut their time-to-hire in half.

Learn more at goodtime.io.

Media Contact

For more information or to arrange an interview with Ahryun Moon, please contact:

Jake Link

press@goodtime.io

Unlock manufacturing’s top hiring strategies in 2024

Our study of 105 manufacturing TA leaders reveals how to hit your hiring goals in a challenging market.

2025 Hiring Insights Report