Recap: An Executive Panel on 2026 Talent Acquisition Trends

At our recent Executive Panel on 2026 Talent Acquisition Trends, Dr. Andrew Monroe put into words what many TA leaders have been feeling: 2026 won’t be defined by a single disruption. It’ll be defined by several colliding at once, leaving leaders without a clear playbook for what comes next.

AI has moved from experimentation to infrastructure. Budget pressure has become a constant. Hiring volumes are uneven (and largely down). And yet, the pressure on TA hasn’t let up, in part because business leaders still want scarce, future-critical skills, and they want it yesterday. 

Together, these conditions raise a more fundamental question for the function: What is Talent Acquisition’s value when success isn’t defined by filling requisitions?

Increasingly, the answer points beyond execution. TA is being asked to balance automation with trust, speed with governance, and short-term efficiency with long-term workforce capability.

To explore how this shift is playing out in practice, we convened senior TA leaders for a candid executive panel moderated by Jacynta Smith. Panelists included Jill Lacy Green (State Farm), Fred Roneker (Procter & Gamble), Ron Wages (Duke Energy Corporation), and Dr. Andrew Monroe (Veris Insights).

Below are the key insights and takeaways from the conversation, starting with the automation arms race and the unintended trust gap it’s creating.

Watch the full panel discussion here →

The automation arms race is turning candidate experience into a trust problem

As AI becomes embedded on both sides of hiring, with candidates applying at scale and recruiters screening at scale, Talent Acquisition faces a widening trust gap.

Dr. Andrew Monroe described this dynamic as a potential “race to the bottom.” The more candidates feel processed by machines, the more they try to game the system with automation. The more recruiters experience low-signal volume, the more they automate in response. In the worst case, an AI applicant and an AI recruiter end up “talking” to each other while humans lose visibility and trust in the process.

The panel was clear, however, that the answer isn’t abandoning automation. The efficiency gains are too real, and TA is still being asked to do more with less. Instead, winning organizations are making two deliberate moves.

1. Radical transparency: Candidates already assume automation is present in the hiring process. What they want isn’t less AI; it’s clarity. Being explicit about where AI is used, why it’s used, and where human judgment enters the process can actually strengthen trust rather than erode it.
2. Selective, high-impact human moments: Candidate experience doesn’t require human involvement at every step, but it does require it at the moments that matter most. Jill Lacy Green shared how State Farm has defined non-negotiable human touchpoints: closing the loop with candidates, providing context around decisions, and communicating respectfully throughout the process. These moments function as employer brand signals, not just transactions. One example: making job offers face-to-face over video to create genuine connection and share in the excitement.

 

Ron Wages offered a complementary perspective from Duke Energy, describing small but intentional workflow changes to reduce the “uncanny valley” effect of automation. One example: avoiding near-instant automated responses that can feel impersonal or jarring while speeding up time-to-disposition because sometimes candidates simply want to know the answer quickly.

Fred Roneker captured the broader shift in mindset well: 

The question is no longer “Where do we put AI in our process?” It’s increasingly, “Where do we choose not to put AI?” 

In other words, a deliberately human candidate experience can become a competitive advantage precisely because it’s one of the few things automation can’t replicate well.

The Key Takeaway: In 2026, automation isn’t the risk. Unmanaged automation is. The best TA functions will deliberately design where human touch protects trust then automate the rest.

Get the automation playbook for TA leaders →

AI is moving from “tool” to “infrastructure” for pipeline intelligence

AI is no longer showing up in Talent Acquisition as a point solution or productivity hack. Increasingly, it’s becoming infrastructure embedded in how TA functions manage volume and monitor pipeline health.

When organizations receive hundreds or thousands of applications per role (read more about the Application Avalanche), the efficiency gains offered by automation are just too compelling to ignore. Certain tasks, like drafting and sending candidate communications, simply can’t scale manually. But the panel emphasized that the real shift isn’t task automation. It’s insight automation.

Ron Wages framed Duke Energy’s approach using the “three S’s”: sourcing, screening, and support.

Sourcing: High applicant volume means organizations are already sitting on a large population of “warm leads.” That is, candidates who may not have been right for one role but may be strong fits for another. AI creates an opportunity to identify those matches, re-engage candidates proactively, and strengthen internal mobility. Instead of treating each requisition as a closed loop, pipeline intelligence allows TA to think systemically about talent already in motion.

Screening: This remains the most sensitive application of AI. Ron emphasized a common pattern among leading organizations: using AI first for prioritization, not final decisions. Until explainability, transparency, and legal defensibility are firmly established, many teams are intentionally avoiding fully automated screening outcomes.

Fred reinforced this point with insight from conversations with Early Career candidates. Many already assume AI is being used more aggressively than it actually is. Their request isn’t “don’t use AI,” but “be honest about where you’re using it, how it works, and why.” Once again, transparency emerged as foundational to trust.

Support: The final “S” focused on candidate-facing support often through chat-based tools or automated guidance. Here, the same principle applied: automation should be intentional, governed, and clear. When designed well, these tools can improve responsiveness and consistency without creating confusion or detachment.

The Key Takeaway: In 2026, AI isn’t just accelerating tasks. It’s reshaping how TA monitors pipeline health and re-engages talent, but only if screening is disciplined and transparency is central to design.

Compliance and fraud are forcing TA to become fluent in legal

As AI adoption accelerates, Talent Acquisition leaders are spending more time navigating compliance, regulation, and fraud risk than ever before. This is no longer peripheral. It’s becoming a core leadership competency.

Andrew framed the challenge as pressure coming from two directions.

• Top-down: from a volatile regulatory environment impacting AI usage, H-1B visas, and compliance expectations
• Bottom-up: from escalating fraud risk, including candidates using AI during interviews or assessments, even when explicitly prohibited

 

The result is a new expectation: TA leaders must learn to “speak legal.” Not to become lawyers, but to understand what is truly prohibited versus what constitutes managed risk. Several panelists described moving away from treating Legal as a checkpoint and toward embedding Legal, InfoSec, and even Physical Security as partners as TA grapples with risks like identity misrepresentation. 

For example, Fred shared a use case of running cross-functional tabletop exercises—scenario-based drills designed to stress-test how fraud could make it through the hiring process—and using those insights to strengthen controls.

The Key Takeaway: In 2026, compliance and fraud aren’t edge cases. The strongest TA leaders will treat Legal and security partners as collaborators, not last-minute gatekeepers.

Avoiding the short-term ROI trap

The panel closed with a clear warning for TA leaders heading into 2026: short-term savings often come at the expense of long-term talent capability.

During periods of economic pressure, organizations naturally focus on immediate returns. That often leads to cutting investments whose value is diffuse and/or delayed, e.g., employer brand, Early Career hiring, pipeline development, and strategic partnerships. The result isn’t savings so much as deferred cost.

Drawing on Veris Insights’ research into the Great Recession, Andrew noted that many Fortune 500 companies that sharply reduced Early Career hiring in 2008 later faced higher agency spend, weaker internal mobility, damaged campus brands, and persistent mid-level talent gaps. In many cases, it took three to five years to rebuild lost capability.

Read: What to Prioritize During Talent Acquisition Budget Cuts

What stood out in the discussion was not a rejection of financial discipline, but a more strategic interpretation of it. The panelists emphasized that sustaining long-term investments requires making the “invisible” visible: using forecasting, pipeline health data, and historical examples to show senior leadership how short-term cuts translate into long-term cost and risk.

As Ron noted, sustained investment in early talent and pipelines isn’t just a growth strategy. It’s a form of risk mitigation.

What 2026 demands from Talent Acquisition leaders

As the conversation closed, one theme cut across every trend: TA’s value is no longer defined by speed, volume, or cost alone.

In 2026, impact will be measured by whether Talent Acquisition can help the business:

• Understand how work itself is changing as AI reshapes roles
• Build and surface skills intelligence, not just fill pipelines
• Balance efficiency with trust by scaling automation thoughtfully and deploying humans where it matters most
• Advocate for long-term capability in an environment fixated on short-term ROI

 

For TA leaders, the opportunity ahead is significant, but so is the risk. Some organizations will make the shift from delivery engine to strategic capability. Others will not.

The difference will come down to how deliberately leaders navigate automation, transparency, compliance, and long-term investment.