William Chichester and Patrick Payne don’t shy away from the tough conversations about hiring. In this spotlight, they cut through the hype around AI to share what’s actually changing, what’s staying the same, and why relationships still matter more than ever in today’s job market.
Give us the short version of your career story. How did you each find your way into talent acquisition, and what’s kept you in the game all these years?
William: I found my way into talent acquisition nearly 20 years ago through a passion for connecting opportunity with potential—especially for students and early-career talent who just needed the right door opened. Since then, I’ve led emerging talent and university recruiting programs at companies like Microsoft, Peloton, and Capital One, building scalable, data-driven strategies that strengthen pipelines and fuel business growth. What’s kept me in the game is the impact: creating equitable access, shaping future leaders, and helping organizations innovate through talent. Today, as Head of Emerging Talent at Claritev, I’m building the company’s first early-career function from the ground up—work that brings together purpose, strategy, and the chance to pay forward the opportunities that changed my own life as a first-generation college graduate.
Patrick: Similar to William, I found my way into talent acquisition early in my career through campus recruiting, and what started as an entry point quickly turned into a long-term path. I’ve spent over 25 years building and scaling recruiting teams across some very different environments, from consulting and global services firms to Amazon, Vail Resorts, adidas, and high-growth tech companies.
What’s kept me in the game is that recruiting is never static. The problems change, the technology changes, and the expectations from candidates and businesses keep rising. I’ve stayed because talent acquisition sits at the center of how companies grow, and when it’s done well, it drives real business outcomes. Today, through PopCandi and PopCandi.ai, I’m focused on reimagining how hiring works by combining human judgment with smarter, more personalized technology.
You’ve seen a lot of talent acquisition trends come and go. What shifts have really stuck and how does today’s AI moment stack up against past “big changes”?
William: I’ve seen a lot of trends come and go over the years, from the early days of job boards to social recruiting, employer branding, and increasingly sophisticated tech stacks. The shifts that actually stuck were the ones that changed how we think about the work, not just the tools we used. Moving toward data-informed decision making, focusing on skills over pedigree, and raising the bar on candidate experience all fundamentally changed expectations for talent teams and for candidates.
This current AI moment feels bigger in scope, but not entirely new in spirit. I remember similar excitement when ATS platforms became mainstream and when LinkedIn reshaped sourcing. What feels different now is the speed and the scale. AI has the potential to take a lot of transactional work off recruiters’ plates, which creates space to focus on strategy, relationships, and building more equitable pipelines. Like every major shift before it, the impact will depend on how thoughtfully it’s applied. Used well, AI can help us hire better and more fairly. Used poorly, it just accelerates the same problems we’ve always had.
Patrick: I started in this field when sourcing literally meant flipping through phone books, so I’ve lived through more ‘game-changing’ moments than I can count. What experience teaches you is that most trends fade, but mindset shifts stick.
The changes that lasted weren’t tools. They were philosophical. We stopped relying purely on instinct and started holding ourselves accountable to data. We moved from unstructured interviews to more disciplined, skills-based evaluation. And we finally recognized that candidate experience isn’t a nice-to-have, it’s part of the hiring outcome.
When I look at the current AI moment through that lens, I don’t see it as a break from the past. I see it as an accelerator. Like job boards or LinkedIn, AI will reshape how work gets done, but its real impact will depend on whether teams use it to make better decisions or just faster ones. The organizations that succeed will be the ones that combine new capability with mature judgment.
AI is everywhere in hiring right now. From where you sit, what’s it actually changing for employers and candidates and where do people tend to get it wrong?
William: From where I sit, AI is already changing hiring in some very real ways. For employers, it’s helping teams move faster, spot patterns in their data they couldn’t see before, and take a more consistent approach to screening and matching talent. For candidates, when it’s done well, it can mean clearer communication, faster feedback, and a process that feels more transparent instead of like a black box.
Where people get it wrong is assuming AI is a silver bullet. Technology doesn’t fix broken hiring practices, it just scales them. If the inputs are biased or the process isn’t designed thoughtfully, AI will reinforce that at speed. Another common mistake is using AI to create distance from candidates instead of connection. The best teams are using it to reduce busy work so recruiters can spend more time building relationships, coaching hiring managers, and making better decisions. At its best, AI should make hiring more human, not less.
Patrick: From where I sit, AI is becoming the starting point for hiring, not the finish line. It’s incredibly good at getting you to a first draft faster, whether that’s sourcing a market, defining a role, or narrowing a long list to something manageable.
For employers, that changes how quickly they can get oriented and make progress, but it doesn’t remove the need for judgment. The best teams are using AI to inform decisions, not outsource them.
For candidates, the upside is clearer alignment and fewer wasted cycles. The risk is when companies treat AI output as final truth instead of a hypothesis that still needs context and human review.
Where people get it wrong is trying to use AI for everything and anything. When you treat it like an answer machine, you end up with shallow decisions and generic experiences. Used well, AI should help humans ask better questions, not stop asking them.
Looking ahead to your February 19 session, what’s one “bald truth” about AI and hiring that might surprise people or spark a lively debate?
William: The bald truth is that candidates often see AI as the enemy screening them out, when the real challenge is the macroeconomic reality we’re in. There are simply more qualified candidates competing for fewer roles, and that pressure would exist with or without AI. Technology gets blamed, but it isn’t the root cause.
What actually makes the difference in this market is human relationships. Referrals, real conversations, and advocates inside an organization matter more than ever. AI may help employers manage volume, but it doesn’t replace trust, context, or someone willing to vouch for your potential. In a tight market, relationships are still the most powerful signal a candidate can have, and that’s often the hardest truth to hear.
Patrick: The bald truth for me is that AI is making hiring decisions feel too easy. It gives companies a way to avoid the hard questions, to stop digging, and to rely on technology instead of doing the real work themselves.
When models produce biased shortlists or rankings that are only surface-level deep, companies aren’t getting the best talent. Over time, that creates sameness, reduces diversity, and ultimately hurts quality of hire.
The truth is, AI is good, but it isn’t that good yet. The companies and candidates that will win are the ones that challenge the output, pressure-test the results, and stay actively involved instead of adopting it blindly.