David Leech

From Admissions Offices to the Boston Staffing Floor

He studied political science and expected to become a lawyer. Instead his first professional recruiting job came in college admissions, doing outreach to high schools and persuading teenagers to choose his institution. The mechanics were the same ones he would use for the next two decades: find the right people, understand what motivates them, and make the case.

A move to Boston led him to the staffing firm Aquent, where he started in business development. Selling suited him. He rose to run the sales side of the Boston business, then took over the entire office, overseeing both sales and recruiting, and stayed roughly seven years. The exit was fitting. A good recruiter from Wayfair reached out, and the pitch worked. He joined as a manager running the UX recruiting division.

Leech is unsentimental about the path. He fell backwards into the profession, he says, because he likes talking to people and because he is competitive, which is the same instinct that powers the sales mindset recruiters have to carry whether they admit it or not.

What AI Actually Changes, and What It Doesn't

Leech's read on the technology is unusually balanced. On the gains he is direct: sourcing and screening that once took days can now take hours. Coordination, follow up, sequences and summaries can be automated. Assessment is getting meaningfully better through AI assisted resume review and skills matching, which he expects will make skills based hiring the norm rather than the ambition. Fewer wasted hours. Cleaner analytics. A clearer view of the return on recruiting effort than the function has ever had.

The harder question is where to stop. Most of the recruiting process could theoretically be automated today, he notes, but that is not the same as saying it should be. Candidate opinion on being assessed by a machine rather than a person is genuinely mixed, and stakeholders are not uniformly ready either. His guidance is to stay on the change curve rather than out ahead of it, and to treat candidate experience as the measurement that governs how fast a company moves.

His current portfolio makes that debate concrete. AI can already do much of what entry level workers at large companies once did: analytics, documentation, research. Some organizations are stepping away from entry level hiring entirely, a shift he expects to show up plainly in the job market. Others are moving in the opposite direction, with IBM tripling its entry level hiring. Leech is candid that no one has solved it. "I don't think any company knows exactly what they're going to be doing," he says, "but we're all grappling with that right now."

Advice for the Next Three Years

To talent leaders still hesitating, Leech is blunt: not investing in AI now would be a huge mistake. Lean into the technology, vet the vendors seriously, decide deliberately where humans stay in the loop, and keep measuring what the candidate experience metrics are telling you. His organizing principle is compact enough to put on a wall: automate the process, but not the relationship.

He also asks leaders to plan past the current quarter. Think short term, he says, but think three years out as well. What does your recruiting organization look like then, and do you have the right people to fulfill it? He believes the role itself is about to change dramatically. Dedicated sourcers will be needed far less. Recruiters will increasingly manage agents that automate large parts of the process. The people who thrive will combine technical fluency, high learning agility, meaning the ability to pick up a new tool and integrate it quickly, and critical thinking sharp enough to work with AI well and prompt it correctly. That last skill, he argues, is no longer a recruiting requirement. It is an every employee requirement.