Hiring for AI can be confusing, because AI itself can be…confusing. The tech is new, the job titles are all over the place, and half of the ‘industry-standard’ tools didn’t even exist a year ago. So how are you supposed to know who to hire? And to do what, exactly?
And we know — the pressure’s on, too. Businesses that figure out how to use AI effectively will inevitably pull ahead from those who don’t.
As an added complication, everyone seems to be looking for the same few unicorns: machine learning engineers, data scientists, prompt engineers, and folks who can wrangle giant models like they’re spreadsheets (or people who can do two or more of those things!). But AI isn’t just a tech team issue. It’s changing how marketing runs campaigns, how sales finds leads, and how ops streamlines workflows.
So, who should you actually hire to help your company make the most of AI? This post breaks down five key traits to look for; whether you’re hiring a technical specialist or someone who knows how to apply AI where it counts.
Cross-functional fluency
A strong AI hire won’t work in a vacuum, so they need to understand how your different teams operate and how AI can actually make those teams run better.
That means being able to talk shop with engineers one minute, then explain a use case to your head of operations the next. It also means knowing when not to use AI. Sometimes the best solution is a simpler one, and a good hire will be able to spot that.
Cross-functional fluency shows up in how someone thinks, so pay attention when interviewing. Do they ask questions about business goals? Do they tailor their ideas to the people in the room? If your marketing team is drowning in campaign data, your AI hire should be able to recommend a solution that works and explain it in plain English.
This skill is especially important for non-engineering AI roles. Whether it’s a marketer using AI to segment audiences or a sales lead forecasting deals, the best hires connect AI tools to real-world outcomes. They build trust across departments and help AI become a shared language, not just a technical one.
Adaptability and continuous learning
AI moves fast. What’s cutting-edge today might be outdated six months from now. So when you’re hiring, focus less on someone’s current toolkit and more on how they learn and adapt.
Importantly; stop unicorn-hunting. You don’t need someone who knows everything. You need someone who knows how to keep learning. The best AI hires are curious by default. Maybe they experiment with new tools in their free time. Maybe they take short courses or follow research papers like most people follow celebrity gossip. The point is: they know this field doesn’t sit still, and neither do they.
You can also spot this mindset in the interview. Skip the “Where do you see yourself in five years?” question. Instead, ask: “What’s something new you’ve learned recently, and how did you use it?” You’ll get a clearer picture of how they think. Look for people who’ve picked up new skills on the job or shifted their focus as the tech evolved. If their resume includes words like “self-taught,” “beta tester,” or “built this on a weekend,” that’s a good sign.
AI adoption doesn’t come with a rulebook. You want someone who can roll with the changes, figure things out as they go, and help your company stay ahead.
Strong problem-solving
You don’t need someone who dreams in algorithms. You need someone who solves problems.
A good AI hire doesn’t just ask, “What can this model do?” They ask, “What problem are we trying to solve?” They look for bottlenecks, inefficiencies, and repetitive tasks; and then figure out if AI can help.
That might mean using machine learning to improve customer churn predictions. Or building a simple automation to speed up invoice processing. It doesn’t always involve a fancy model or a PhD-level approach. Sometimes it’s just about knowing the right tool for the job and using it well.
When interviewing, listen for how candidates talk about their past work. Do they lead with results? Do they mention business impact? Bonus points if they’ve helped launch or test an AI pilot, especially one tied to a specific department or use case.
AI for the sake of simply having/using AI is a waste of time. The right hire knows how to apply those tools where it matters, measure what works, and move on from what doesn’t.
Ethical awareness and a responsible AI mindset
Just because AI can do something doesn’t mean it should.
From biased algorithms to questionable data practices, the risks are real — and they’re growing. That’s why ethical awareness isn’t a bonus trait in an AI hire. It’s a requirement.
The best candidates think critically about how their work affects people, not just performance. They ask where the data came from. They test for bias. They question assumptions. They’re mindful of what they feed into AI, too. In high-stakes industries like finance or healthcare, this mindset isn’t just helpful, it’s non-negotiable.
Look for folks who’ve worked with compliance frameworks, done model audits, or helped set guardrails for responsible AI use. If someone brings up fairness, transparency, or explainability without being prompted, take note.
And if they can explain those concepts without sending your whole team into a jargon-induced nap? Even better.
Communication skills and stakeholder influence
A good AI hire needs to communicate clearly, whether they’re building a tool, using one, or helping others adopt it.
They should be able to explain what they’re doing, why it matters, and how it helps the team reach its goals. This goes beyond giving a slick presentation. It’s about building trust. Clear, honest communication helps demystify AI and makes people more likely to adopt it. If your sales lead doesn’t understand how a new AI tool qualifies leads, they’re not going to use it. And they definitely won’t advocate for it, and then you can kiss those efficiencies goodbye.
The best AI hires know how to read the room. They adjust how they talk based on who’s listening. They ask for feedback. They make space for questions. In short, they don’t act like the smartest person in the room (even if they are).
Look for people who’ve led cross-team projects, run demos, or trained others. If they’ve convinced a skeptical team to try something new, that’s a sign they won’t just build smart tools, they’ll help the whole company use them.
AI can make your business faster, smarter, and more competitive, but only if you have the right people in place. Whether you're hiring for tech, marketing, or operations, focus on folks who can solve real problems, communicate clearly, and adapt fast.
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