Hiring in tech has always moved fast, but few corners of it are shifting as quickly right now as recruitment itself. In this episode, I sat down with Bruno Lomardo — “Loma” to most people — who leads talent acquisition at Rasa, the conversational AI platform. We talked about what generative AI is doing to hiring, the strange new problem of deep fake candidates, and why getting diversity right isn’t a box-ticking exercise but a competitive advantage. From recruiter to AI talent lead Loma’s path into tech recruitment wasn’t a straight line, and that turns out to be part of why he sees the field clearly. He’s lived through hiring booms and the cooldowns that follow, watching the market swing from “we’ll take anyone who can write a for-loop” to far pickier, signal-hungry hiring. That cyclical experience shapes how he reads the current moment — because the latest swing isn’t really about headcount. It’s about the tools. “We’ve been working with conversational AI for years,” he points out, and that long runway matters. At Rasa, AI isn’t a buzzword bolted onto the hiring process; it’s the product. So when generative AI started reshaping how candidates apply and how teams screen, the team had a head start in understanding both the upside and the failure modes. What generative AI actually changed The most visible effect of generative AI on recruitment is volume. Applications are easier to produce than ever, which sounds great until you realize a polished cover letter no longer tells you much. When everyone can generate a flawless, perfectly tailored application in thirty seconds, the signal that used to come from effort and craft starts to disappear. That creates a real discrepancy in the market. On paper, candidates look stronger and more uniform than ever. In conversation, the gaps show. Loma’s takeaway is that the screening burden has shifted — away from filtering for basic competence on paper and toward verifying that the person behind the application is real, capable, and who they say they are. Which leads to the most unsettling part of the conversation. The deep fake problem “Deep fakes are getting better and harder to detect,” Loma says, and he means it literally. Recruiters are now encountering candidates whose video presence, voice, or even live interview behavior may be synthetically generated or assisted. What started as an edge-case curiosity has become a credibility problem teams have to actively manage. The detection methods are evolving alongside the threat — verification steps, live and unscripted interactions, and tooling built specifically to flag manipulated media. But Loma is candid that this is an arms race, and the honest position is to assume the fakes will keep improving. The practical defense is process: build interviews that are hard to fake your way through, and don’t outsource your judgment entirely to a tool that can be gamed. Doing diversity right Where the conversation turned genuinely energizing was on diversity, equity, and inclusion. Loma’s framing cuts through the usual debate: this isn’t charity and it isn’t optics. “Doing diversity right creates better teams,” he says — and the emphasis lands on right. Done badly, diversity efforts become quotas chasing optics, which helps no one and breeds resentment. Done well, they widen the pipeline, surface candidates conventional processes overlook, and produce teams that make better decisions because they bring more perspectives to the table. The work is in the how: structured interviews, debiased job descriptions, broader sourcing, and consistent evaluation criteria that give every candidate a fair read. The road ahead Looking forward, Loma sees AI playing an even larger role in hiring — handling the repetitive front end, surfacing strong candidates faster, and freeing recruiters to do the human work that actually predicts success on a team. But the same technology that makes hiring more efficient is also what makes it harder to trust. The recruiters who thrive will be the ones who treat AI as a tool to sharpen judgment, not replace it. If there’s one thread running through the whole conversation, it’s that: the fundamentals of good hiring — verification, fairness, and genuine human evaluation — matter more now, not less. Get full access to My Data Guest at mydataguest.substack.com/subscribe
