Beyond the Hype: Hiring in the Age of AI
🕒 In just 6 minutes, gain clarity on hiring AI talent that delivers real value.
Over the past few years, I’ve had countless conversations about AI, but the one I recently had with Paul from UPTIC hit a nerve.
We’re both veterans of multiple tech waves — from the dot-com era to the RPA boom — and what we’re seeing now with AI is equal parts déjà vu and something entirely new. So I wanted to write down a few takeaways from that conversation — because if you're trying to build serious AI capability in your organization, you need to hear this.
Everyone’s Suddenly an AI Expert
Let’s start with the elephant in the LinkedIn room: overnight, everyone became an AI expert. People are claiming 20 years of experience in a field that didn’t even exist in its current form three years ago.
And I get it — everyone wants to ride the wave. But here’s the catch: it’s made hiring real talent extremely difficult. When everyone’s profile looks impressive, how do you tell who knows what they’re doing?
Paul and I laughed about this. He studied AI formally back in 1994. I’ve built my career helping companies deploy AI that works. And we have trouble keeping up with the speed of change today. So what does that tell you about the thousands of people adding “AI Strategist” to their bios this week?
The Real Risk Isn’t Overpaying — It’s Under-Delivering
Companies are now paying 30 to 50% premiums for AI talent. Sounds like an investment — but often, it’s just burning cash on the wrong profiles.
One of the biggest failures I see? Organizations are hiring someone who’s touched one AI project and thinking they’re ready to lead a full initiative. Experience isn’t just ticking boxes. It’s scars. Mistakes. Lessons learned. If your AI lead hasn’t failed at least once, they’re not seasoned — they’re just early.
Know What You Need — Most Don’t
This is where the confusion starts. Companies rush to hire AI people without even knowing what problem they’re solving. Are you building a chatbot? Doing document processing? Predictive analytics? Nobody hires a data scientist to build an LLM — or at least they shouldn’t.
And once they figure out what they need, they realize… they can’t afford it.
Especially if they insist on hiring locally.
The “Remote” Myth
Here’s the thing: remote ≠ risky.
I’ve seen companies terrified of hiring someone in another country, but fine with someone in Manchester when they’re based in London. Remote is remote. The real issue is: are they managed well?
This is why local oversight matters. When you work with a partner that provides HR, cultural alignment, and project management, suddenly the fear disappears. You’re no longer worried about timezone or distance. You’re focused on delivery.
Staff Aug vs Managed Service: Pick Your Poison
There’s no universal answer here. Some teams want control, so staff augmentation makes sense. Others don’t have the internal expertise, so they need a managed service.
My take? If you don’t know how to build the house, don’t just hire a few people and hope for the best. Get someone to deliver it for you, then learn from them.
Eventually, sure, you can take it in-house. But don’t gamble your first AI project on guesswork.
Cultural Fit Is Real — But Manageable
One thing people often raise is cultural fit.
“Will a developer in Asia or Eastern Europe understand my company in Germany or the UK?”
Fair question. But here’s what I’ve learned: experience bridges that gap. If the person — or partner — has worked with your type of business before, the cultural concerns fade quickly.
And let’s not kid ourselves: I’ve seen bigger culture gaps between two teams in the same office than between a French manager and a Filipino engineer.
AI Doesn’t Stop — So Why Should Your Team?
AI moves insanely fast. If your team isn’t training continuously, they’re becoming obsolete. Plain and simple.
As a client, you can’t do everything. So your partner must help keep talent sharp — certifications, training, hands-on labs. You don’t need “experts” in everything. You need people who stay current within your project’s scope. That’s how you win.
Let’s Summarize the Hard Truths
Here’s what I tell every client who asks me for help finding AI talent:
Everyone looks great on LinkedIn. Experience is what matters.
Remote is only risky if unmanaged. Local oversight changes everything.
Don’t just hire fast — hire smart. Look for people who’ve failed before and learned.
Choose the right model. Staff augmentation for control, managed service for outcomes.
Keep learning. AI doesn’t pause for you to catch up.
And most importantly:
If your AI team costs a fortune and still fails to deliver, you didn’t just waste money — you missed the entire point.
A balanced mix — a few strategic onshore roles, and a high-quality offshore backbone — is how you make your AI roadmap financially viable.
So yeah, there’s a lot of noise out there. But if you know what to look for — and who to partner with — you can still cut through it and build something real.
If you’re serious about doing that, drop me a message. Let’s talk.
— Olivier Gomez (OG)
Watch the series here:
https://www.youtube.com/playlist?list=PLwi85l6lHMiy4QJGWkNGNK9FlFhGhr12k
Watch the full video here: