The shift from volume to quality
For most of its history, recruiting was a volume game. Post the job, collect the CVs, filter by keyword. Thiago has watched that model collapse in real time.
"Some years ago it was still about volume," he says. "Now it's about quality. Now it's about knowing how to sell your value proposition. Now it's about having the right tools — because you're looking for efficiency and good results."
The paradox: the explosion of AI-powered tools has made recruiters simultaneously more powerful and more overwhelmed. The answer, in Thiago's view, is not more tools — it's the right tool that actually simplifies decisions rather than multiplying data points with nowhere to go.
Companies don't have a data problem. They have a clarity problem. They're obsessed with gathering data — but they don't know what to do with it.
— Thiago Santos
Where AI is already better than humans
Thiago is unusually candid about this: in certain tasks, AI has already won, and pretending otherwise is counterproductive. The areas where he says human recruiters simply can't compete:
AI's clear advantages in recruiting
- Screening large volumes of profiles consistently and without fatigue
- Identifying patterns across millions of data points — impossible for a human
- Automating follow-ups (a task most recruiters skip, which kills conversion)
- Structuring candidate information so recruiters don't start from scratch every time
"AI works brilliantly where humans are slow, inconsistent, or overwhelmed," Thiago explains. "In those areas, AI is not the future. It's already better than us. We have to rely on it."
Where humans remain irreplaceable
The flip side is equally clear. AI, in Thiago's experience, breaks precisely where things get most human:
AI handles
- High-volume profile screening
- Automated outreach & follow-up
- Pattern recognition at scale
- Information structuring
- Talent scoring & ranking
Humans own
- Final hiring decision
- Cultural misalignment detection
- Understanding ambition behind CVs
- Ethical dilemmas & edge cases
- The call when there's no clear answer
There's also what Thiago calls "an uncomfortable truth" — one that many recruiters haven't yet internalized: AI doesn't remove responsibility. It amplifies it. Because now you're accountable not just for your own judgment, but for how you interpret the data AI hands you.
The danger is not using AI. The danger is delegating thinking to AI.
— Thiago Santos
On talent scores and the "wow moment"
Thiago was invited to try Nova Recruiter before its public launch. His first reaction wasn't polite approval — it was surprise.
"I don't rely on new tools at first sight," he's clear about that. "I have to test them. But when I saw the talent score working across millions of profiles — that was a wow moment."
The insight he keeps coming back to: sourcing used to be intuition-driven. You'd search LinkedIn, find profiles, guess which ones might be strong. Now, with a talent score, it becomes insight-driven. You're not searching in the dark with a flashlight anymore. You're turning the lights on.
"Most of the time, the best candidates don't apply to your job. You have to go find them. But you don't know where they are, or whether they're genuinely good or just good at selling themselves. The talent score addresses that — it tells you where to look. It focuses judgment, it doesn't replace it."
Why "human in the loop" is a product decision, not a concession
One of the product choices Thiago found most thoughtful about Nova Recruiter: the platform doesn't force a single AI-or-human workflow. Some recruiters want to trust the talent score but write their own outreach. Others want to delegate messaging but shortlist manually. The tool adapts to both.
"The hardest thing when you're building for HR leaders is that each one tends to be different," he says. "Hypercustomization is hard — but now it's possible. And you've made a very good decision from the very first beginning."
The ethics of AI in hiring: where should the line be?
This is where Thiago gets deliberate. He's thought carefully about where AI should — and shouldn't — be allowed to go in a hiring process.
His current position: AI can inform, suggest, and prioritize. But the final decision should always have a human signature on it. Hiring carries long-term consequences — for candidates, for teams, for organizations — and those consequences require human accountability.
He also flags three specific practices he'd consider red lines:
- Fully automated rejections — there should always be a human validation step, even for volume roles
- Black-box models with no explainability — if a candidate can't understand why they were rejected, the system isn't fair
- AI making the definitive hiring call — at least for white-collar roles, the final yes or no should remain human
"If it's not fair, it's not sustainable," he says simply. "The future of recruiting is not about being faster. It's about being better — without losing our humanity."
Hiring is not just a business decision. There is a human decision within hiring — with long-term consequences. AI should inform. AI should suggest. But it should not decide.
— Thiago Santos
The community edge: what AI can't replicate
Beyond the tools conversation, Thiago keeps returning to something AI genuinely cannot substitute — the value of a community of practitioners who've been there before you.
"When you ask an HR director about a problem you're living right now, and they answer from their own experience — that's a different layer of intelligence," he says. "You can ask AI any doubt you have. But human intelligence built through lived experience in communities? That's even better."
With a community of more than 3,000 HR leaders, Thiago has seen what happens when practitioners share wins and failures in real time: the learning compresses. One person tests a new tool, reports back, and 50 others avoid a mistake they would have made alone.
"You don't have to test everything. Others will use it and give feedback. And we will all go in the same direction together."
Key takeaways from this episode
- Recruiting has shifted from volume to quality — and the tools that win are the ones that deliver clarity, not more data
- AI is already superior to humans in screening, pattern recognition, follow-up automation, and information structuring
- Humans must retain final hiring decisions, cultural assessment, and ethical accountability
- The talent score changes the sourcing conversation from "who do we like?" to "who actually matches what we need, and why?"
- AI amplifies recruiter responsibility — it doesn't reduce it
- Communities of practitioners remain irreplaceable for lived-experience intelligence that AI can't replicate
- Integration — not proliferation — is the right lens for evaluating any new HR tool
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