[Opinion] AI and the return of the renaissance generalist

For most of my career, I’ve been that person at the cocktail party who struggles with the inevitable question: “So, what do you do?” I usually take a deep breath, look down at my drink, and mumble something like, “Well, I sort of do a bit of… um… different things?”

See, I’ve spent decades bouncing between industries, disciplines, and roles. Hands-on in technology one year, a corporate role the next, leading teams in a startup after that, and then there’s been writing, creative strategy, and leadership consulting.

Maybe, as it turns out, my inability to “pick a lane” might not be a bug. It could be a feature.

And here’s why: Artificial Intelligence might just be setting the stage for the triumphant return of the Renaissance generalist.

During the actual Renaissance, the most celebrated minds weren’t narrow specialists — they were passionate polymaths who excelled across multiple disciplines simultaneously.

Then came the Industrial Revolution. Everyone needed to be a cog in a very specific wheel.

By the early 2000s, when I was stumbling into my mid-twenties, the message was clear: find your niche.

This approach made perfect sense in a world where human expertise was the bottleneck. The collective knowledge of humanity had grown so vast that no individual could possibly master more than a sliver of it.

The Renaissance man was dead, or so I thought.

The New Renaissance Generalist

Artificial Intelligence, particularly the large language models and AI systems we’re seeing today, can absorb and process information at a scale no human could ever match. They can become “experts” (and I’m using that term with several metric tons of nuance) in multiple specialised domains simultaneously.

AI can diagnose specific medical conditions, write specialised code, draft changes to legal contracts, analyse financial markets, and generate scientific hypotheses.

When specialised knowledge is no longer the bottleneck — when it’s available on demand through AI — the comparative advantage shifts. Suddenly, the most valuable human skill isn’t knowing everything about one narrow slice of reality. It’s knowing how to navigate between different domains, identify unexpected connections, and integrate insights across fields.

Let me clarify something important: When I talk about the return of the Renaissance generalist, I’m not suggesting we can all become Leonardo da Vinci overnight.

The new Renaissance generalist isn’t someone who knows a little bit about everything but can’t do anything useful with that knowledge.

The potentially valuable generalist might have what some call “T-shaped” knowledge — broad awareness across many domains, with deep expertise in at least a few areas. The difference now is AI could help us rapidly develop sufficient depth in new areas when we need it.

Twenty years ago, if I wanted to contribute meaningfully to a new field, I’d need months or years to develop enough expertise. Now with AI, I might get up to speed in days — maybe hours. The AI could handle the toil of memorising facts and procedures while I provide the judgment, creativity, and cross-domain connections that AI might struggle with.

This could become the superpower of the modern generalist: the ability to rapidly develop working knowledge in new domains by leveraging AI as a cognitive partner. No longer will we be limited by our capacity to memorise specialised information — we could instead be limited mainly by our ability to ask good questions and make sense of the answers.

Why Generalists Could Thrive in an AI Age (A Theory, Not a Guarantee)

There are certain things AI systems don’t do well, or at least where it needs some handholding— and it’s precisely the stuff that generalists excel at:

1. Making weird connections between chaotic, unrelated things
I once built a startup culture program by applying principles from screenwriting. Specialists need well-defined problems, and AI needs structured data. But generalists? We thrive where clarity doesn’t exist yet. We’re comfortable with “something feels off but I can’t quite put my finger on it,” connecting seemingly unrelated dots while others are still demanding more parameters. AI can’t make these bizarre leaps because it doesn’t obsess over seemingly irrelevant topics.

2. Translating between expert humans (and now, between humans and AI)
As I mentioned above, I’ve spent much of my life being that person who helps the engineers understand what the marketing team is trying to say, and vice versa. Now, I’m also explaining to company leaders about how they can talk to AI and that what AI says back often matters. I’m like a translator for professional jargon and silicon-based thinking. It’s exhausting, but apparently valuable.

3. Pivoting fast
If there’s one skill every generalist has mastered, it’s this. We’ve been forced to adapt to new fields, technologies, and roles our entire careers. In a world where AI is reshuffling the professional deck every six months, being adaptable is becoming the main game.

4. Leading actual humans (not just algorithms)
AI can crunch data and predict outcomes, but it can’t inspire a demoralised team. It can’t read the room and realise Erin from accounting is seething about Dave from sales. Leadership requires emotional intelligence that AI doesn’t have.

Generalists often slide into leadership roles like they were born for them. Why? Because we’ve spent our careers being professional dot-connectors and people-understanders. We speak enough engineer to talk to the tech team, enough finance to not horrify the CFO, and enough design to appreciate why the creative director is having an existential crisis over a shade of blue. In a world where AI handles the specialised knowledge, leading with empathy, vision, becomes the superpower hiding in plain sight.

A Possible New Workplace Dynamic

Picture this: You walk into your workplace of the near future (or log into it). In one corner, AI might be handling specialised analyses. In another, it could be writing code. Elsewhere, it might be drafting contracts and reviewing documents. All with machine-like precision and efficiency.

At the centre of it all is the human generalist as orchestra conductor. The AI violinist might play perfect notes, but doesn’t know when to come in, how to harmonise with the AI oboist, or why this particular note should swell with emotion. That’s the generalist’s job — orchestrating these specialised capabilities into something cohesive and meaningful. Bringing the human touch to the final product.

Trying to compete with AI on specialised tasks might eventually feel like trying to outswim a shark — technically possible for about 15 seconds before you become minced meat. Instead, generalists find their sweet spot one level up: integrating, contextualising, and humanising what AI produces.

This shift surely transforms traditional career paths — climbing a single specialisation ladder may no longer be the optimal route to success.

Instead, we might see the rise of the “zigzag career” — moving between different domains, gathering diverse experiences, and building unique combinations of skills and perspectives along the way. What once looked like career wanderlust might now be reframed as strategic adaptability.

Of course, this doesn’t mean specialists will disappear. Deep domain expertise will remain valuable, particularly in fields that require years of embodied practice or specialised judgment that AI can’t easily replicate. But I propose that even specialists may need to become more “T-shaped” — maintaining their depth while developing broader awareness and collaboration skills.

For organisations, this shift means rethinking hiring, team structure, and leadership development. Companies that once prized narrow specialists may now seek out these boundary-crossing generalists to help integrate AI into their operations, connect siloed departments, and identify opportunities that specialists might miss. I call it hiring “athletes”.

How to Become a Renaissance Generalist in the AI Age

The good news is that having diverse interests and the ability to make connections across domains is becoming increasingly valuable.

The bad news is that  knowing a little bit about a lot of things isn’t enough.

And if you’re a lifelong specialist possibly feeling the winds of change, you probably don’t need to suddenly become interested in everything. But you might want to consider broadening your horizons and practising new skills.

Because the new Renaissance generalist will need specific meta-skills to thrive in an AI-augmented world — these being a great start, in my view:

1. Mixing and matching ideas
You need to get good at spotting the patterns, pulling out the gold nuggets, and remixing them into your own mental playlist. Don’t just collect information like a digital hoarder — learn to connect the dots between that podcast on ancient Rome, that article on supply chains, and that weird documentary about octopuses. (Tiago Forte’s “Building a Second Brain” is the book to read on this stuff).

2. See the matrix behind everything
Develop your sense for how things are connected behind the scenes. While specialists are zoomed in on their piece of the puzzle, you’re backing up to see the whole picture — and noticing that moving this piece over here causes unexpected wobbles over there. It’s about spotting those “oh crap, nobody thought about THAT” moments before they happen.

3. Ask questions others haven’t considered
As AI gets better at answering questions, the superpower becomes asking questions nobody thought to ask yet. It’s being that person who pipes up with “Wait, but why are we even doing this?” right when everyone’s arguing about how to do it. The best generalists are walking question marks — relentlessly asking “why?” but with strategic purpose.

4. Become fluent in speaking human, machine, and everything in between
Be that rare person who can get the data scientists, the creatives, and the AI tools all playing nicely together.  Like a social butterfly with technical chops — hosting the dinner party where everyone can actually understand each other and maybe even become friends.

5. Learn fast
You’ll never know everything about everything. But what you can do is get freakishly good at going from clueless to dangerous in new domains quickly. Become comfortable with being the dumbest person in the room on a particular topic…until you’ve absorbed enough to contribute by quickly reaching competence with the help of AI tools and your human peers.

So, What Do You Do?

The next time someone at a cocktail party asks me what I do, I might just say: “I’m a Renaissance generalist in the age of AI.” And when they look confused, I’ll explain that I’m professionally curious — I ask great questions, make unexpected connections, and collaborate with humans and tools to solve interesting problems across domains.

Or maybe I’ll just mumble something about being “in tech” and change the subject. Old habits die hard.

But for those of us who’ve always been generalists, this could potentially be our moment.

So here’s to the Renaissance generalists, past and future — may we continue to frustrate career counsellors, confuse HR departments, and thrive where humans and AI collide. Our time has come… again.

Clayton Moulynox has 20+ years of global experience in management, strategy, sales, leadership and culture, and has worked with Australian technology IPOs, global tech companies and US-based startup unicorns. His previous roles include head of culture at Auth0, national partner channel development manager at Microsoft, and general manager of Evolve IT Australia. He currently runs the consulting firm MX Growth.

Clayton is a member of the Channel Guru advisory team. Visit channelguru.com and register your interest to lock in early access and a special introductory offer when Channel Guru launches.