Hiring Has a Coordination Problem — and It Costs More Than We Think

For years, talent acquisition has been framed as a pipeline problem. When hiring slows down, the instinct is to look upstream: sourcing strategies, employer branding, top-of-funnel conversion.

But inside most enterprise hiring organizations, a different constraint is becoming harder to ignore — and it has less to do with attracting candidates, and more to do with what happens after they enter the process.

It’s here that a new kind of solution is starting to emerge. Not another feature, or workflow tool, but something closer to a digital teammate — an AI agent designed to take ownership of the coordination work that keeps hiring moving.

GoodTime calls this agent Cori.

To understand why Cori matters, it helps to first understand the problem she’s designed to solve.

The operational bottleneck hiding in plain sight

In large, distributed organizations, interview scheduling is no longer a simple administrative task. It is a multi-variable coordination challenge involving time zones, interviewer availability, candidate preferences, role-specific requirements, and frequent last-minute changes.

The result is a level of operational friction that is both pervasive and underestimated.

Recruiters and coordinators spend a disproportionate amount of their time managing logistics rather than engaging with candidates or influencing hiring decisions. Even well-resourced teams find themselves constrained by the sheer volume of coordination required to move candidates through the process.

What makes this particularly challenging is that the work is essential but invisible. When it goes well, it’s unnoticed. When it breaks down, the impact is immediate: delays, candidate drop-off, and internal frustration.

As Shauna Geraghty, Senior Vice President, Global Head of People at Talkdesk, describes it:

“There’s no longer a back-and-forth exchange between the candidate and our coordination team. [Cori] works behind the scenes to automate the scheduling process end to end.”

That “back-and-forth exchange” is more than an inconvenience — it is a structural inefficiency that compounds at scale.

Why incremental improvements haven’t solved the problem

Over the past decade, recruiting technology has made meaningful progress in digitizing and streamlining parts of the hiring process. Scheduling links, workflow automation, and conversational interfaces have all reduced friction in specific moments.

However, these innovations have largely operated within the same underlying model: coordination remains a human responsibility, supported by tools that require input, oversight, and intervention.

This model works reasonably well in simple hiring environments. It breaks down in complex ones.

Enterprise hiring is defined by variability — across roles, regions, stakeholders, and processes. In that context, coordination is not a series of discrete tasks. It is a continuous, dynamic system that requires constant adjustment.

Static automation and reactive tools are not designed to manage that level of complexity. They reduce effort, but they do not remove ownership of the problem.

A different approach: coordination as a system, not a task

What’s beginning to change is not just the technology itself, but the way coordination is conceptualized.

Rather than treating scheduling and communication as tasks to be executed, leading teams are starting to treat them as a system that needs to be continuously managed and optimized.

This is where the emergence of AI agents introduces a fundamentally different model.

Cori, GoodTime’s AI agent, is designed around this premise. Instead of assisting with individual actions, she takes ownership of the coordination layer across the hiring process — managing scheduling, rescheduling, communication, and workflow execution as an integrated whole.

This distinction is important. Cori does not wait for prompts or rely on predefined rules alone. She operates continuously, adapting to changes as they occur and ensuring that the process remains aligned without requiring constant human intervention.

In practice, this translates into measurable outcomes. As Jeff Moore, VP of TA Operations and Workspaces at Toast, notes:

“We’ve seen 50% faster interview scheduling and 55% fewer cancellations. What’s great about that is we’re getting people scheduled faster with less internal friction.”

The reduction in friction is not simply a matter of efficiency. It changes how the entire hiring system behaves — increasing speed, improving reliability, and reducing the likelihood of breakdowns.

Reclaiming time for higher-value work

One of the more persistent concerns surrounding AI in talent acquisition is the potential erosion of the human element. In practice, the opposite effect is often observed when coordination is effectively automated.

By removing the operational burden, teams are able to reallocate time and attention to the aspects of hiring that require human judgment and interaction: building relationships, assessing candidates, and making informed decisions.

Jenn Walker, Global Talent Acquisition Coordination Manager at HubSpot, captures this shift clearly:

“Cori isn’t replacing the human side of hiring — she’s giving us more space to actually focus on it.”

This aligns with a broader movement toward human-centric AI — an approach that emphasizes augmentation rather than replacement, and outcomes rather than features.

Why this shift matters now

Several macro trends are converging to make coordination a critical focus area for talent leaders.

First, hiring complexity continues to increase. Global teams, hybrid work models, and more specialized roles introduce additional variables into an already intricate process.

Second, resource constraints are tightening. Many organizations are being asked to maintain or increase hiring output with smaller teams, placing additional pressure on efficiency.

Finally, expectations around candidate experience have evolved. Delays and disorganization are no longer tolerated in a competitive talent market, particularly for high-value roles.

Taken together, these dynamics expose the limitations of traditional coordination models. They also create an opportunity to rethink how hiring operations are structured.

Toward a more resilient hiring system

If the past era of recruiting technology focused on digitizing workflows, the next phase is likely to focus on operational resilience — ensuring that hiring processes can adapt and continue functioning effectively under real-world conditions.

This requires more than incremental improvements. It requires a shift in ownership.

By introducing an AI agent that is responsible for coordination end-to-end, organizations can move from a model where humans manage the system to one where the system actively supports humans.

Cori represents one implementation of this approach, but the broader implication is more significant. It signals a move toward treating coordination as core infrastructure rather than administrative overhead.

For talent leaders, this raises an important question: if coordination is the connective tissue of hiring, should it remain one of the most manual and fragile parts of the process?

Redefining where hiring gets stuck — and how it moves forward

The narrative around hiring challenges is starting to evolve. While sourcing and employer branding remain critical, they are no longer sufficient to ensure success.

Execution — the ability to move candidates efficiently, consistently, and thoughtfully through the process — is emerging as a defining capability.

Organizations that address coordination at a systemic level are likely to see not only faster hiring, but more predictable outcomes, stronger candidate experiences, and more sustainable workloads for their teams.

In that context, Cori is less about introducing another tool and more about redefining how hiring work gets done.

And for many enterprise teams, that shift is long overdue.