Kerri Smith

A Leap of Faith in Tampa

Like most people in the profession, Smith did not plan her way in. After graduating college she left New Jersey for Florida on little more than instinct and a desire to try something different. In the Tampa area she found an RPO that was willing to hire people who knew nothing at all about recruiting, then train and develop them in what the industry would now call a sourcer role. She took the leap, and she fell in love with the work.

The RPO environment turned out to be an unusually rich classroom. Fast paced by nature, it exposed her to many different talent acquisition worlds at once, because every client was a different world: global footprints, multiple industries, and a parade of technologies and systems she would otherwise have needed a decade to encounter. That last piece is what redirected her. Rather than staying on the pure requisition side, she became fascinated by the nuts and bolts behind the scenes. How do these pieces fit together? How do you make a recruiter's day more efficient and more impactful? How do you make the experience better from the candidate's side of the glass? The back half of her career has been spent answering those questions.

Past the Era of Fancy Automation

Smith's read on AI in recruiting is that of someone who has spent years looking under the hood of vendor claims. For a long stretch, she says, talent acquisition sat in a holding pattern: plenty of tools marketed as artificial intelligence that turned out, on inspection, to be fancy automation. That left TA leaders in an uncomfortable position, unable to articulate to business leaders what the net benefit of adoption would actually be. The past year, in her view, has produced the most significant strides the function has seen.

She also names a tension few discuss openly. Every business sets its own threshold for how much AI involvement it will accept inside a TA organization, and that threshold rarely matches what the market and candidates themselves are expecting, wanting and frankly ready for. Balancing those two realities has been the central work of the last twelve months.

Her framework is a segmentation exercise rather than a wholesale replacement. Map the process, decide which steps genuinely require human judgment and differentiation, identify where AI can do the work and sometimes do it better, and then design deliberately across both. "AI is not to replace the human entirely," she says. "AI is to make the human even more human." The point of the efficiency is to buy back time for the parts of recruiting that carry invaluable weight and that no model can replicate.

Advice for 2026: Fix the Process First

Her first piece of counsel to other talent leaders is blunt. AI will not fix a bad process. "If you have a bad process, no matter what technology it is, it's still going to be a bad process." Before the pilot, before the procurement cycle, outline what you actually do. Is it correct? Is it right? Is it scalable? Where are the openings? Repair those, then let the technology accompany the process rather than paper over it. Skip that step, she warns, and the initiative is more likely to fail than not.

Her second is permission to experiment. Not every AI solution will be the right one, and that is acceptable. What is not acceptable is standing still. "If you don't try, then you're behind the curve." Try it, iterate on it, take the chance. If it works, excellent. If it works halfway, interrogate why: implementation, design, training. There are always avenues.

Her third is governance, and she treats it as non negotiable. Responsible AI means the human remains the decision maker, particularly in talent acquisition, with the technology serving up information more efficiently so that person can decide better and faster. That is the line she holds while everything else moves. AI, as she puts it, is here to stay and not leaving us, so the work now is to get our arms around it properly.