← Talent 100, Class of 2026
2026 Talent 100 Honoree

Alan Henshaw

Booz Allen Hamilton

“People that are naturally curious take the time to learn what's going on in the market.”

Alan Henshaw has been named to the Talent 100, Class of 2026, the annual award recognizing up to 100 leaders in each category of talent acquisition. Honorees are nominated by peers or found by committees that look for excellent work wherever it happens, then chosen for the depth of their craft and their impact on hiring. This is Alan's story.

In 2007, Alan Henshaw walked into a staffing agency to interview for a sales role. He walked out weighing a career he could not yet define. Nearly two decades later, at Booz Allen Hamilton, he is helping build large language models that can look at an employee's history and tell you whether that person is a beginner or an expert in Java, and then explain exactly how it reached that conclusion. The distance between those two moments is the story of a talent leader who never stopped being curious about the technology he recruits for.

The Interview That Became an Offer

The agency he visited was working a sales requisition. After the conversation, the recruiters there asked him a question he had not anticipated: had he ever considered recruiting? "I have no idea even what recruiting is," he told them. He had a friend in the business, called him, talked it through, and took an offer to get his feet wet.

His first four or five years were spent in finance and accounting recruiting. He was good at it, but he is candid that the subject matter never fully caught him. It was a job rather than a calling. That changed in 2011, when he moved into technology recruiting and immediately recognized the difference. "I consider myself a tech nerd, but not like an engineer or anything," he says. "I just love technology." The market he was suddenly working in rewarded exactly that instinct, and the long-term career he had not planned on came into focus.

Teaching a Model to Grade a Skill

Ask Henshaw where AI has actually earned its keep in recruiting, and he starts with the unglamorous parts of the life cycle. Preparation, he says, is where the gains have been clearest: better intake meeting templates, sharper questions for hiring managers, more rigorous probing of the skill set itself so a recruiter genuinely understands the role before sourcing begins. Candidate correspondence has gotten faster too. His teams use ChatGPT like everyone else, but Henshaw's ambition is further out. He is pushing toward agent to agent conversations, where process flow runs on the back end and recruiters can step back from the mechanics.

His most consequential recent project sits at the intersection of talent acquisition and internal mobility, a boundary many organizations still treat as someone else's problem. Booz Allen, like most large employers, talks constantly about skills and upskilling. If software engineers need to learn more about AI, the answer is to enroll them in programs. What the company lacked was any way to measure proficiency. Employees could list their skills in Workday, and their work history offered clues, but nothing assessed whether a person was a beginner in Java programming or an expert.

So Henshaw helped kick off the build of an LLM on the back end that ingests the employee data the company already holds and returns a proficiency rating on a five point scale, beginner through expert. Crucially, it shows its work: the model explains the reasoning behind each rating and which data it weighed. Accuracy, he reports, has been strong. The practical value is immediate. If someone is already highly proficient in a technology, there is no reason to route them into training for it. Find the gap that actually exists instead. The system is, in his words, "making a large impact already."

Curiosity, and the Room You Are Lucky to Be In

Asked for advice to other talent leaders, Henshaw lands on two things. The first is natural curiosity, and he means it literally. He walks into work talking about the CEO interview or panel he watched the night before. Lately that has meant a run of conversations about AI and what the future holds, including the rising cost of running these models and how that economics will play out. Very little of it is talent acquisition content, and that is the point. Understanding the ebbs and flows of the market and of business in general is what shapes the conversations he has internally and what lets him think in a different way.

The second is a reframe of a meeting most recruiters treat as administrative. Recruiters, he points out, are fortunate enough to sit in rooms with extremely smart leaders, and intake calls are the clearest example. His guidance to teams is to walk in excited rather than procedural. "Use it as like an opportunity to fill in gaps of your knowledge bank," he says. Too often recruiting arrives at the intake with a script: this is the process, this is what we do, this is how it will go. Henshaw argues for the opposite posture, an assumption that you will learn something in that call you did not know before.

There is a business case underneath the humility. Talent teams tend to assume hiring managers understand recruiting and know the process, and they usually do not. Building the relationship first, hearing what has worked and what has not from the manager's side, is what makes it possible to explain why the process will be effective. Open-mindedness, in his telling, is not a soft skill. It is how you earn the right to be listened to.

The Talent 100 exists to celebrate the people shaping the future of how the world hires, and few embody that better than Alan. We are honored to welcome Alan Henshaw to the Talent 100, Class of 2026, and grateful for the experience, perspective, and craft they bring to this community. Congratulations, Alan. Welcome to the Talent 100.

About the Talent 100

The Talent 100 is an annual list spotlighting the leaders who push HR and talent acquisition forward, organized by Noon AI. Honorees are selected through peer nominations and independent selection committees. Selection is entirely merit-based, with no fees or pay-to-play requirements.

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