The Inquisitive Will Inherit the Earth

Part two in a series on what AI really changes about work.

Part one: "AI Doesn't Replace Experience. It Replaces Inexperience.

In Brief 

AI has made answers abundant and nearly free.  That means the competitive advantage has moved upstream - to the quality of the questions being asked.  New Gallup data shows employee engagement has stayed flat even as AI adoption accelerates: the tools alone are not moving people.  The winners of the next decade will not be the organisations with the best technology.  They will be the ones with the most inquisitive minds: people who probe, challenge, and refuse to accept the first plausible answer - and cultures that give them room to do it.

In my last piece I argued that AI replaces inexperience, not experience - that as machines absorb the repeatable work, the value of judgement rises.  Several people asked me the obvious follow-up question: if experience is what matters, what makes experience valuable in the first place?

Here is my answer.  The most valuable people I have worked with in nearly thirty years of data, advertising and consulting share one trait, and it is not intelligence, qualifications or technical skill.

They are relentlessly inquisitive.

They are the ones who look at a dashboard everyone else has signed off and ask, "why is that number going up when this one is going down?”  The ones who sit in a board meeting and ask the question everyone was thinking but nobody voiced.  The ones who hear "that's just how we've always done it" and treat it as an invitation rather than an answer.

For most of business history, these people were mildly inconvenient.  They slowed meetings down.  They picked at thigs that seemed settled.  In a world where finding answers was slow and expensive, curiosity was a luxury - nice to have, rarely rewarded.

AI has just turned that world upside down.

Answers are now a commodity.

Every organisation now has access to the same extraordinary capability: machines that can analyse, summarise, draft, and calculate at a speed and scale no human team can match.  Within a few years this will be as unremarkable as having electricity.

When everyone has the same answer machine, the answers stop being the advantage.  The differentiation moves entirely to the input - to what you choose to ask, and how well you interrogate what comes back.

This is a genuine reversal.  The industrial economy rewarded people who could execute reliably.  The knowledge economy rewarded people who could find and process information.  The AI economy rewards something different: people who can want to know the right things.

And wanting to know is exactly what machines cannot do.  An AI model has no curiosity.  It does not wonder.  It does not lie awake puzzled by an anomaly in the numbers.  It waits, brilliantly, to be asked.  Someone still has to do the asking - and the quality of that asking now determines the quality of everything downstream.

What inquisitive actually looks like.

Inquisitiveness is not the same as asking lots of questions.  Anyone can generate questions; AI can generate thousands.  Genuine inquisitiveness has three characteristics that matter commercially.

It is dissatisfied with the first answer.  AI produces plausible answers with total confidence, which makes it dangerously persuasive.  The inquisitive mind treats a fluent answer as the start of the conversation, not the end of it.  It asks what the answer assumes, what it leaves out, and what would have to be true for it to be wrong.  In an AI-first organisation this is not a personality quirk - it is quality control.

It connects things that don't obviously belong together.  The best commercial insights rarely come from drilling deeper into one dataset. They come from someone noticing that a pattern in customer complaints looks like a pattern they once saw in supply chain data, or that a pricing problem in one sector rhymes with a solved problem in another.  Machines are superb within the frame they are given.  Inquisitive people redraw the frame.

It is anchored in genuine interest in the business.  The most useful question in any engagement is rarely technical.  It is some version of: "what is this organisation actually trying to decide?"  Inquisitive minds care about the answer.  They read the annual report.  They talk to the people on the front line.  They want to understand how the business makes money, not just what the data says. That interest is what turns analysis into advice.

This is where the series connects.  Experience tells you which questions matter.  Inquisitiveness makes sure you never stop finding new ones.  Experience without curiosity calcifies into "how we've always done it.”  Curiosity without experience produces interesting questions with no commercial edge.  The winners will have both - and AI will amplify them beyond anything we have seen.

The evidence: tools don't engage people.

If AI alone created better organisations, we would see it in the workforce data by now.  We don't.

Gallup's latest midyear figures, released this week, show employee engagement has remained flat even as AI adoption accelerates - around three in ten employees engaged, with roughly one in six actively disengaged.  Two years into the fastest technology rollout in business history, the needle on human involvement and enthusiasm has barely moved.

That should stop every leader who believes an AI licence is a transformation strategy.  But the more interesting finding is buried in the same data: the organisations that do see stronger engagement are the ones pairing AI with clear expectations, thoughtful implementation and genuine manager support.  In other words, AI lifts an organisation only when the human conditions around it are deliberately built.

This is precisely what you would expect if the argument above is right.  Hand an answer machine to a disengaged workforce and you get faster indifference - the first plausible answer, accepted without a second look, at scale.  Hand the same machine to people who are genuinely interested in the business, and who know their questions are welcome, and something very different happens.  The technology is identical.  The curiosity is not.

Engagement, at its core, is what inquisitiveness looks like at organisational scale: people who care enough to ask.

The leadership implication.

If curiosity is the scarce asset, most organisations are managing it badly - because most organisations were built to suppress it.  Rigid job descriptions, meetings designed to reach agreement quickly, cultures where questioning a number is read as questioning a colleague: all of it optimises for smooth execution in a world where execution was the bottleneck.  It no longer is.

Gallup's prescription - clear expectations, thoughtful implementation, manager support - is sound, but I would push it further.  Those are the conditions for adoption.  Building for advantage means going after curiosity itself.  Three suggestions for leaders who take this seriously.

Hire for curiosity, not just credentials.  In interviews, pay less attention to the answers candidates give and more to the questions they ask.  Someone who interrogates your business model with genuine interest will outperform someone with a perfect CV who asks nothing.  The CV tells you what they have done; the questions tell you what they will do.

Make challenge safe and expected.  The moment it becomes career-limiting to ask, "are we sure about this?", your organisation has switched off its quality control at exactly the moment AI has made confident-sounding wrong answers free and instant.  Build the challenge into the process: every significant AI-assisted recommendation should have a named human who has actively tried to break it.

Protect time to wonder.  Inquisitiveness needs slack.  If every hour is accounted for, people will accept the first answer because they have no time to question it - and you will have paid a premium for judgement you never gave the space to operate.  The efficiency AI creates should be reinvested in thinking, not simply harvested as cost saving.

The quiet advantage.

There is an irony in all of this.  For years, the technology industry has told us the future belongs to those who master the machines.  I think the opposite is closer to the truth.  The machines are mastering themselves at a remarkable rate.  What they cannot supply is the itch - the human instinct to ask why, to poke at the settled thing, to be interested.

That instinct is unevenly distributed, hard to fake, and now more commercially valuable than it has ever been.  Every organisation has people who have it.  Most have spent years training them to keep quiet - and the flat engagement numbers are the invoice for it.

Find them.  Promote them.  Put the machines at their disposal.

The inquisitive will inherit the earth - and they will get there by asking for directions no one else thought to request.

Beyond: Putting Data to Work is a global data and AI consultancy.  We start with decisions, not dashboards.