Over the last two weeks of my daily writing, I have been circling around one uncomfortable question: what happens to a company’s culture on the day it stops needing its people. I left it as a worry.

That was only half the work.

There are two serious and completely opposite arguments running right now about whether AI makes human beings less central to an organisation or far more central,

and almost every leader I meet has heard only the frightening one, absorbed it, and quietly begun to plan as though it were already settled and done.

It is not settled. Far from it. So before you redesign a single role, I want to lay both arguments side by side, name the questions that sit in the gap between them, and set out the first concrete moves to make while the answer is still yours to shape.

THE FIRST ARGUMENT: you will need people less.

In early 2025, a group of researchers led by Jan Kulveit published a paper called Gradual Disempowerment,1 and its central idea is quietly chilling. For all of history, humanity has kept its grip on economies, states and cultures for one unglamorous reason: those systems could not run without us, and being needed is what gave us our leverage over them. Now the need is fading. As AI grows able to do more of the producing, the deciding, and even the creating, that old leverage thins, not through one dramatic robot takeover or any single catastrophic moment, but through a slow and almost invisible drift in which one institution after another gradually stops having to serve the very people it once could not have functioned for a single day without. Shrink it to one firm, and the warning lands. As the organisation depends on its people less, the quiet discipline that kept it serving them, the voice, the development, the basic care, comes loose with it.

THE SECOND ARGUMENT: You will need people more.

The opposite case is argued just as seriously by people staring at exactly the same technology. In his 2025 book Superagency2, Reid Hoffman argues that broadly shared AI does for human capability what the car once did for human movement: amplifying the agency of ordinary people rather than shrinking it and handing individuals the kind of reach that used to belong only to large institutions. The MIT labour economist David Autor makes the harder-edged version3: that AI can drive down the cost of expertise and hand expert judgment back to ordinary workers, rebuilding the valuable middle-skill work we spent forty years hollowing out. The picture inverts. Read this way, the firm does not need fewer people; it needs people who can suddenly do far more, and the truly scarce thing stops being labour and becomes the human judgment to aim all that raw new capability at something worth doing.

Both arguments cannot be right. One of them is wrong. Which one comes true inside your organisation will not be decided by the technology at all; it will be decided by the choices your leadership makes over the next two years, while the concrete is still wet. That is why the debate cannot wait. It has to happen now, out loud, at your table and not someone else’s.

THE QUESTIONS YOUR ORGANISATION HAS TO DEBATE

These are the fault lines. Every leadership team should be able to say where it stands on each one and exactly why.

1. Replace or amplify?

2. Where must a human always stay?

3. What are people actually for here?

4. How do we keep listening once we no longer have to?

5. Who captures the gain when everyone is more productive?

6. What happens when some of our people have far better tools than others?

7. Are we still growing task mastery or judgment?

THE NEXT TEN STEPS WE HAVE TO DO

1. Put both arguments in front of your executive team, not as a tidy briefing but as a genuine debate, and make every person in that room take a side out loud and say exactly why they have taken it.

2. Define what humans are for here. One sentence. One owner.

3. Before any agent goes live, decide which judgments and relationships are simply off-limits to automation, and write them down.

4. Change the very first question asked of every AI project from “what can we cut here” to “what has just become newly possible for our people and our customers”, because the question you choose to ask first, before any other, quietly decides almost everything that follows it.

5. Redesign one role around amplification, not removal: give a capable person powerful AI and widen their remit.

6. Fund voice and development as a defended budget line, and hold it there even when the cold headcount logic says you could quietly drop it.

7. Set the fairness rule early. Before the gap opens.

8. Move hiring and promotion away from task mastery and toward judgment, relationship, and the skill of directing AI well.

9. Put one permanent question on the monthly executive agenda and refuse to let it slide off: where exactly are we drifting from serving our own people, and who in this room is willing to stand up, right now, and name it out loud?

10. Join the wider conversation. No one does this alone.

For thirty years, I have watched People and Culture move from administrator in the Industrial Age, to business partner in the Information Age, and now toward the thing I have always believed we were meant to become, the choreographers of human ingenuity in the AI Era itself.

So here is what I am building—launching on 17 August

A way for our whole sector to grow that ingenuity as fast as AI is expanding around us.

Instead of a conference you attend once a year and forget, it is a living collaboration that runs around the clock, with human judgment through our waking hours, AI curation and integration through the night, and all of us surfacing once a week to think out loud together.

From next Monday, the 22nd of June, I will show you exactly how it works, a little more each day, building up to the launch on 17 August. Follow along. Reply if you want the one-page description, and come and build it with me.

Or simply follow this Substack to hear more about how you can get involved.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

I am building a Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. Launching on 17 August. Subscribe to get updates on how to get involved.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.

Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work

katharinemclennan.com

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Every organization I have ever worked inside treats its best people as scarce, and it builds an entire apparatus to prove the point: succession plans, talent pools, high-potential programs, retention bonuses that quietly admit we cannot simply make another one of her. The whole architecture rests on one assumption we almost never say out loud, that judgment lives inside individual human beings and cannot be duplicated, that the best we can manage is to find it, grow it slowly over years, and pray it does not walk out the door on a Friday. We treat that as a law. It is not.

Now sit with the assumption-breaking.

The essayist Dwarkesh Patel asks us to imagine a fully agentic firm, one where your most capable performer is not a person at all but a model, and where a model, unlike a person, can be copied. Not a junior version. Not a trainee who needs five years of seasoning and a few scars to be useful. An exact copy, with the skills and accumulated context fully intact, quietly running 200 instances by Thursday afternoon while the rest of us are still arguing about the offsite date.

Stay with what that does to the shape of your organization, because the org chart was never a law of nature either. It exists for one mundane reason: a single human leader can only supervise so many people, hold so many conversations, and carry so much in one head at a time, so over a century, we built spans of control and layers of management and the whole careful geometry of the firm as an elaborate workaround for the limits of a single human attention span. Copying erases the limit overnight. Patel argues that this transforms management even more than it transforms labor, because coordination, the very thing managers exist to provide, suddenly costs almost nothing.

Here is the part that should stop those of us who have spent our lives on culture. A human firm cannot replicate itself. It cannot clone its culture, its trust, or its hard-won institutional memory, and that very impossibility is precisely why culture has been such a durable competitive advantage for the better part of a hundred years. It was the one asset a competitor could never download. You could lose your strategy to a leaked deck and your product to a clever teardown, and still keep the way your people actually treated each other on a bad Tuesday. If even part of that now becomes encodable and copyable, leaders will need a far sharper answer than they have ever needed before to one deceptively simple question: which parts of who we are cannot be copied, and why are those the parts worth paying for?

I have a strong sense of where the answer lives, even if I cannot hand it to you finished and gift-wrapped. The copy will hold the skills. It will not hold the thing that once made people follow the original because they wanted to, and not because they had to. It cannot choose its own goals. It cannot feel the weight of a hard decision settle in its chest, or make another frightened human being feel understood, or tell you the truth at real cost to itself, which is the rarest and most valuable act anyone in a hierarchy ever performs. Copy the competence, and you have built something extraordinary. You still will not have the person your people trust with their doubts at midnight.

So the copyable parts of leadership will be copied. That much is already settled. The Irrelevance road is the easy one, where we let the copying quietly stand in for the whole of leadership and wake up with two hundred competent instances and not one soul left who can hold a room that has gone quiet with fear. The Ingenuity road is harder, and far more interesting, because it asks leaders to name the uncopyable human core out loud, to protect it, fund it, and design the organization around it on purpose, instead of trusting it to survive by the same accident that has carried it this far.

So play with this, and be honest as you do. If you could copy your best leader two hundred times before tomorrow morning, what would you actually set all of them to do? Most executives answer the first half in a heartbeat, the analysis, the coverage, the endless coordination that eats their week. Then they slow right down, because they realize that the things they lean on that leader for most are precisely the things a copy would never carry across. That hesitation is not a problem to be solved. It is the most useful thing you will learn all year about what leadership in your organization has actually been all along.

I do not have the full answer, and I will not pretend to. I am building a year-long conversation to work it out with many minds rather than hand it down from a stage, and I will say more about that soon.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

This essay is day six of seven, the on-ramp to something I am building called Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. More this week.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.

Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work

katharinemclennan.com

I told you yesterday that today would belong to People and Culture, the function closest to my heart, and this morning I read Pope Leo XIV’s Magnifica Humanitas, so I had to rewrite this essay entirely. Most people have been saying that the Pope has come out against the tyranny and future doom caused by AI. This is far from the case. You need to read it. It is extraordinary.

Pope Leo XIV signed Magnifica Humanitas on May 15, 2026, the 135th anniversary of Pope Leo XIII's Rerum Novarum, the foundational text of modern Catholic Social Thought that addressed the condition of the working class during the Industrial Revolution. The date was deliberate. Two days after his election in May 2025, Leo XIV told the College of Cardinals that Leo XIII had addressed the social question in the context of the first great industrial revolution, signaling that he intended to address it in its modern form.

If you listen to the headlines about the Pope’s encyclical, you might conclude that he said AI fuels war, human control is slipping, and the Vatican is instructing it to slow down. From there, the news hardens into something simpler: that the Pope has set himself against the machine. The people repeating this to me have read the coverage and never the text. Magnifica Humanitas contains no rejection of AI in any of its paragraphs. It contains a labor encyclical. The most serious one in 135 years.

It excites me because I have been writing about changes in our organizational culture and leadership during the transition from the Industrial Age to the Information Age, which I argue occurred in 1995, when Netscape went public. That year, I graduated with an MBA from Stanford, and some of my classmates became founders of companies like eBay and Hotmail.

(Yes, I should have joined the Stanford MBA Technology Club: one of the thousands of “could have, would have, should have’s I have managed to accrue so far over this lifetime).

Now, I am writing about the transition from the Information Age — to — what? I refuse to call it the AI Age. I challenge us to choose which age we are moving into by pitting the Irrelevance Age, defined by speed without judgment and data without meaning, against the Ingenuity Age, where human wisdom and machine intelligence amplify one another.

My book Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era (not AGE!) — walks you through these various ages and shows you how we can make a choice through all the levers we have to pull in organizations - leadership, structure, people processes, engagement, systems, processes, and values.

I have also been hosting a podcast where I invite one of my Stanford MBA classmates from the class of 1995 (now 60 years old) to speak to the rather wise-before-their-time recent graduates of the Stanford MBA Class of 2025 (now 30 years old)

And I have a personal stake in trusting leaders like this one. At Christmas in 1979, in the first full year of his papacy, I stood in St Peter’s watching John Paul II celebrate, the first non-Italian pope in four and a half centuries, a Pole elected while half of Europe lived behind a wall, and at the time my own family was living in Cold War West Berlin, where the wall was not a metaphor but the view from the window. Ten years on, it fell.

Pope John Paul II had stood with the shipyard workers of Gdansk while the unmovable quietly moved. When the Berlin Wall came down in 1989 it opened Eastern Europe to rejoin the world, an upheaval so extraordinary that I am writing a novel set around it, which means I have been living inside that history every morning while this new Leo was drafting his letter.

Popes who can see a whole system have a history of changing it.

Now, the first American pope has turned that same systemic sight on AI.

In my book, I argue that the AI-era executive has to become the philosopher who meets the business leader. This letter is what the philosopher’s half of that conversation sounds like at full strength.

Here are his ten points as I read them, each followed by my take, consistent with what I have argued this week and in Before the Fingerprint Fades.

1. Technology is never neutral.
It “takes on the characteristics of those who devise, finance, regulate and use it” (paragraph 9 of the Encyclical).

I have spent this week saying that technology amplifies the system it meets, and the Pope has now said it of civilization itself. This means the question facing every leader is what their system actually is before the amplifier arrives, what gets compounded the day the machine is switched on. Point it at strength and the strength compounds. Point it at weakness, and so does the weakness, which is why the quadrants in my book exist at all.

2. The choice is not yes or no to AI.
The real decision, he writes, is between “constructing Babel or rebuilding Jerusalem” (paragraph 9), between community organized around power and community organized around shared responsibility. With that single image, he walks calmly off the stage where the optimists and the doomers have been waiting all year to debate him. Even his strongest phrase, the call for disarming AI, he defines as preventing the technology from dominating humanity rather than refusing it.

So much for the headlines of our main media outlets. The fork he describes is what I have called across my book and now in my writing and speaking, the choice between Irrelevance or Ingenuity. It is chosen, never suffered.

3. Unprecedented power, privately held.
“Never has humanity had such power over itself” (paragraph 4), and its main drivers are private, often transnational parties with resources beyond many governments (paragraph 5).

Boards inherit this warning in miniature. When the redesign of work is handed to whoever bought the software, the company has quietly reproduced the very concentration he is naming, and the leaders who are accountable for human beings have surrendered the pen without ever deciding to surrender it. My dear friend Theresa Lim, who builds AI products for a living and published her own reading of the encyclical this week, gives the warning its sharpest commercial edge in seven words: the capability to build is not a mandate to build.

4. The person is not translatable into data.

The Pope rejects the pretense that one language, even a digital one, can render the mystery of a person “into data and performance” (paragraph 10).

Yesterday, I described the last thirty years of organizational talent work as plotting human beings as dots on a nine-box grid, ranking whole lives along two axes, filing the result where the person being measured could never see it, and calling the entire exercise a science of potential. We have been reducing people to data long before the machines could. AI inherited our habit. It did not invent it.

Theresa makes the matching argument from the builder’s side of the mirror, writing that the attention economy turned human beings into the product rather than the customer, by deliberate design and not by accident. Two professions. One examination of conscience.

5. Human limits are not defects.

The Pope writes that building for the common good means accepting our limits and weakness “without considering them an error to be corrected” (paragraph 12).

Everything scarce that I named this week, judgment above all, is formed through limitation, through the failed project and the hard year, and the decision that taught by wounding. Engineer away the limits, and you engineer away the formation.

Theresa compresses the same truth into the cleanest line I have read on this point, that AI can speed the journey from data to knowledge and cannot generate wisdom, and wisdom is what the limits were growing in us all along.

A fingerprint is itself a limit. One unrepeatable pattern instead of every possible one. That is exactly what makes it worth protecting before it fades hence my book’s title.

6. Work is a fundamental good of the person.

The Pope argues that work is not “simply a problem to be dealt with or a means of generating income” (paragraph 37).

The job is the two-hundred-year-old invention I described on day one of my 7-day write-a-thon, scaffolding raised around the machinery of another century and mistaken ever since for the building itself, while work is the older human good that was standing underneath the scaffolding the whole time. His distinction is the one our headcount spreadsheets never learned to make. It changes what we are protecting.

7. Judge automation by dignity, not efficiency alone.

Pope Leo continues that automation “must not be evaluated solely in terms of efficiency, but in relation to the dignity of the worker” (paragraph 37).

This is the sharpest test the Pope delivers to our organizations, and nearly every AI business case in circulation fails it on page one, because a design that only counts what gets cheaper will deliver the helper on a leash I warned about on day four and then call the leash a transformation.

Efficiency is real. I do not sneer at it. But dignity is a design choice, and nobody is currently designing for it.

8. The new wealth carries an old obligation.

The principle that creation is destined for everyone now extends, he writes, to “patents, algorithms, digital platforms, technological infrastructure and data” (paragraph 67), or the gap between the included and the excluded becomes a chasm.

Drawn at the scale of nations, these are the Outpaced and Irrelevant quadrants from my book, described in this Substack. Drawn at the scale of one company, it is the talent I described on day five, capability locked in boxes while the teams that need it starve, surplus and starvation hidden from each other by the org chart that sits between them.

9. The builders cannot govern alone.

The Pope calls for independent checks, transparency about algorithms, equitable access to data and avenues of recourse (paragraph 71).

A handful of laboratories writing their own report card is not governance. The corporate version is no better, where the people whose working lives are being redesigned never enter the room where the redesign happens, and where the ethics committee meets quarterly while the deployment schedule meets every single day. They belong in that room.

Theresa’s phrase for the same conviction is that humans belong in the driving seat, not merely in the loop, with agency designed in from the first line of the architecture rather than bolted on afterward as a checkpoint.

Tomorrow I will show you the room I am building.

10. No one is saved alone.

The Pope’s hardest chapter faces weapons, the normalization of war, and force without limits, and his closing conviction is that “no one is saved alone” (paragraph 73).

The machine has no conscience. It will scale whatever we hand it, mercy or violence, with equal fidelity, and so the human fingerprint stays pressed onto every consequential decision, or the title of my book stops being a metaphor and quietly becomes a report.

LET US REFLECT!!!

Before I leave you with his question, I want to name what Pope Leo XIV models as a leader, because it is the very thing I have spent a week arguing no machine possesses.

He thinks in the context of “love-meets-strategy,” with the heart, brain, and gut working as one instrument, systemic sight applied to the whole world at once, and that this integration cannot be replicated by AI, however fluent the simulation becomes.

I am delighted that this Pope refuses to let us forget it. He speaks to the heart, constantly, about what matters to every one of us, Catholic or not.

Read the whole letter if you can make the time, because the headline versions from the mainstream media are not just thin; they are woefully inadequate and incorrect in their interpretation of his Encyclical.

The man did not set himself against the machine. He handed every leader the examination question of the next decade:

“Will you design this technology around the dignity of the people who do the work, or only around the price of them?”

The Pope asked his question for a civilization, and starting tomorrow, on day seven, I will show you how I intend to ask it for the working world, in public, for a full year, with the machine sitting in the room as a participant rather than a tool.

Come and argue with all three of us. I don’t have the answer, but perhaps human wisdom and artificial intelligence might meet somewhere in the middle. I will be designing how we all can play together in this exploration, so

STAY TUNED.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

This essay is day six of seven, the on-ramp to something I am building called Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. More this week.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.


Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work

katharinemclennan.com

Yesterday I asked whether 2026 sends us toward Irrelevance or toward Ingenuity, and I left you with a promise: if your job was only ever a fragment of some larger whole, and you are so plainly more than that fragment, then talent itself was never a fragment either. Today I collect on it. The question is easy to say and very hard to answer. If talent is not a fragment, what is it? How do we see the real potential buried in a person, and how on earth do we put that potential to work in a world that has stopped arranging itself into the neat little boxes we spent two centuries drawing?

Start with the seductive wrong turn. Almost every company is about to take it, and it will feel, for a quarter or two, exactly like genius.

Picture a business that buys AI for every function and wakes up convinced it has reinvented itself overnight: finance no longer grinding through spreadsheets because the machine reads them faster and more accurately than any analyst, marketing no longer pouring millions into a customer system because the system now builds and corrects itself, IT turned into something none of the old textbooks ever described, risk wearing a wholly new face as cybersecurity passes into agentic hands, and a strategy team running Porter and every rival scenario through portals that refresh themselves by the second. Faster, sharper, cheaper. On every dashboard in the building, it looks like transformation.

This kind of “AI Augmentation” is not what AI’s potential could be if it were combined with our potential talent - but in the same job as we have today. It is merely an AI-augmented Industrial Age. Perhaps lower costs, fewer “FTE” (don’t get me started about that term) — and maybe more engaging chatbots.

Watch what happens to the actual people, because it is almost always one of two things. Either the person is let go, since the machine now does most of what their fragment demanded, and the scraps that remain are folded into somebody else’s fragment, or the cost is taken some other way, and we tell ourselves a comforting story about the survivors, that they finally have time, saner workloads, better mental health, an earlier train home to their families.

I would love to believe that story. I doubt it. The first instinct in almost every boardroom is to ask where the cost reductions are hiding, never where the revenue might lift, never where people might work in truly different and healthier ways, because no shareholder in my lifetime has rewarded a leader for sending the team home rested. This is the Industrial Age, super-powered. The fragments are faster. The cuts run deeper. The underlying design has not changed by a single line.

None of it changes what work actually is, and none of it rests on any new way of seeing the human beings who do the work. That second failure is far older than AI, and quieter, and it is mine to confess, because I have spent my whole working life inside it.

For at least thirty years (the Information Age in which we had more and more data and lost our intuition, wisdom and connection to others and their story amidst it), we have looked at talent through a three-by-three grid, plotting people as dots with their so-called potential running up one axis and their performance along the other, then hunting for the single dot in the top corner, the high-potential high-performer, and pouring our development budgets and our succession plans and our money into that one glowing box.

We rarely spend an hour on the person. Where they grew up. What their career has actually taught them. What they learned the hard way, in the year everything went wrong. What they quietly dream of building before they die. We almost never sit beside them to ask how the work itself might be rebuilt around the thing they are genuinely good at, so instead we hand them a generic course, fast-track the anointed few, and forget that the other eight boxes are full of human beings too.

Here is the part we never say aloud. We almost never tell a person why they truly earned a five, or a three, or a one, we do not show them where they sit on the grid, and we do not explain the number on the bonus, so the rating means nothing real, the succession plan built on static positions means nothing real, and the human being walks out of the room having been measured, ranked and filed by someone who never once asked them a question that mattered. The Information Age did not fix any of this. It buried it. More data, more dashboards, more nine-box slides, every one of them still blind to everything I have just described.

So now what?

If the old jobs are dissolving, and the org chart is dissolving with them, and the strange new kinds of work look nothing like the roles our entire talent machinery was built to manage, then we have been handed the rarest opportunity of my whole career:

the chance to finally ask what talent actually is,

with not one of the comfortable old boxes left to hide inside.

I do not have the answer yet. I want to be plain about that.

I have spent thirty-six years growing talent. I can see the old model dying in front of me with complete clarity, and I still cannot see the shape of the thing that will replace it, and I trust no one who stands on a stage and claims that they can. The answer will not come on a framework. It will not come on a slide. It is simply too large for one person, one company, or one think-tank afternoon that everyone has forgotten by Friday lunchtime. So I am building something different to find it, and I will tell you exactly what it is before this week is out.

Tomorrow, I come to the function closest to my heart, and the one I think I can help the most in its role as the facilitator of what could be a transformation of Ingenuity rather than an abyss of Irrelevance. People and Culture. If talent is about to mean something entirely new, then the people whose entire job is talent have the most to lose here, and by far the most to give.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

This essay is day one of seven, the on-ramp to something I am building called Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. More this week.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.

Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work



katharinemclennan.com

For most of two centuries, two great eras built the world of work, and the picture above marks their end because both are now finished.

The Industrial Era ran from around 1769 to 1995. It took whole human work and cut it into fragments small enough to time, supervise, and standardise, and it ran on Volume, Instruction, Standardisation, Timekeeping, and Authority. Look at the first image: the factory floor, the metrics board, the clock, the supervisor watching from the rail. You are looking at a design that lifted millions out of poverty and asked each person, in return, to be a reliable piece of a machine.

The Information Era ran from 1995 to the present. It promised to set us free with connection and search, and in many ways it delivered, but look at the second image. Rows of people bent over screens, drowning in feeds, served more and more of whatever someone decided they should see. It did not undo the fragmentation of the Industrial Era. It sped it up and wired it to our attention.

Both eras are over, and 2026 is the fork in the road. AI has arrived, and the honest question is the one in the middle of the picture. What now for humans?

Yesterday, I argued that your job today may well be a fragment, but that you are not, and that the valuable part of you was never inside the fragment at all. Today, I want to name the most expensive mistake we are about to make with this technology, the one that will look like progress and be quietly the opposite, and then I want to show you how to turn it on its head.

Here is the mistake. We take the fragment each of us has been reduced to, and we point this powerful new machine straight at it. We automate the bounded tasks, make the rest faster, and measure the efficiency we gain. The accounts payable clerk processes invoices in half the time and then does not need to process them at all. It feels like transformation, because the speed is real and the savings are real. But the job stays the unit, the box stays the map, and the fragment simply shrinks until nothing human remains inside it. Look at the third image, the one labelled Irrelevance. Efficiency. Innovation. Autonomy. The future is automated. A room full of machines and a single lonely human who no longer has a reason to be there.

There is a principle underneath this that I keep returning to. Technology amplifies the system it meets. Point it at fragments, and it will industrialise the fragmentation, faster and cheaper and at a scale that makes the old design even harder to question, because now it is delivering numbers nobody wants to touch. The Irrelevance road is the easy one. It asks for no imagination at all. You simply let the machine finish the cut the Industrial Era began.

The other road starts at the same fork, with the same machine, and the only thing that changes is where you point it. Instead of automating the human inside the fragment, you use the machine to free the human from it.

Picture an accounts receivable clerk, and let me give him a name, John Meyers. For years, his job was to chase late invoices, one at a time, a small bounded piece of a much larger flow he was never allowed to see. The Irrelevance road hands his chasing to the machine and quietly empties his desk. The Ingenuity road hands the chase over to the machine, too, and then it sends John Meyers to answer a question no one inside any single box could ever answer. Why is the cash always late? He walks the whole flow. He sits with the customers who simply cannot pay on the terms they were given. He finds the manufacturing line starved of cash because the money never arrives in time. And he finds the finance partner who factors the receivables and quietly profits from the very lag everyone has been treating as a fact of nature, so that its whole interest lies in keeping things exactly as broken as they are.

John Meyers stops being a fragment and becomes the person who can see the whole, and then he does the thing no machine can do for him. He uses his judgment to invent new ways for those customers to pay, arrangements that actually fit them, and he leads a small group across the silos to build it. Yesterday, I wrote that we ask people to exceed our imagination while giving them no room to use their own. This is what it looks like to finally give them the room. Look at the fourth image, the one labelled Ingenuity. The same warm light, people of every age around one table, the machine present everywhere as the glowing map of the whole flow and nowhere as a cage. That is not a fantasy. That is a choice.

This is why I no longer call what is coming the AI Era, as though it were a single fixed destination. The same five things bend either way. Vision or Void. Intuition or Inertia. Synergy or Silos. Trust or Tyranny. Authenticity or Apathy. Same technology, same people, two completely different destinations, and the machine holds no opinion about which one we walk toward.

That is the part almost everyone has the wrong way around. They are waiting to see what AI will do to us, as though the technology holds the verdict. It does not. The technology will faithfully amplify whatever we point it at. The choice between Irrelevance and Ingenuity was never a technical question, and it will never be answered in a product roadmap. It is a leadership decision, made one organisation and one John Meyers at a time, and 2026 is the year we begin making it, whether we admit it or not.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

This essay is day one of seven, the on-ramp to something I am building called Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. More this week.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.



Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work

katharinemclennan.com

Yesterday we asked a hard question. What if your job is really just a fragment, now that AI has arrived?

I want to sit with the part that comes next, because your job today may well be a fragment, but you are not, and the most valuable thing you bring was never inside the fragment at all. It is the part of you that no one ever thought to measure.

And that is why it is our collective “JOB” to reconstruct this thing we call “work,” and what we humans do, starting from a fresh, blank white canvas that is waiting for us.

At the moment, we have an Industrial Work design and way of working that needs toppling – and now more than ever. We adjusted it around the edges in response to the Information Age, but the Information Age came in 1995, and now that is past. We can’t wait any longer.

At the top, a CEO and a board hold the whole picture. They are responsible for the integration, the systems, for seeing the future and reading the past.

Then they take that whole vision, and they fragment it. They hand pieces to the executive team, to finance, to people and culture, to marketing, to technology, to business unit A and business unit B, to risk, to legal. Each executive turns away from the table and fragments their piece again, down to their direct reports. Those reports fragment it again, and so it goes, down and down.

Until one day, perhaps one fifty-thousandth of that supposedly holistic vision lands on your desk as a job description. Here is what you are responsible for. Here are your key result areas (“KRAs”) , the handful of outcomes we will hold you to. Here is the performance you must deliver this year. Here are our values, our definitions of those values, and our descriptions of the behaviours that demonstrate them.

And at the end of the year, you will receive a number from one to five. One means you did not deliver your fifty-thousandth. Three means you delivered exactly what we told you to deliver. Five means you went beyond our imagination.

Beyond our imagination is exactly the point, and we miss it every time. We ask the person in the fragment to exceed our imagination, while giving them no room to use their own, and while we ourselves too often failed to use ours when we drew the whole in the first place. We needed imagination at the top. And we needed to make sure the person holding the fifty-thousandth piece got to bring theirs as well. Instead, we built a machine for shrinking people to the size of their fragment.

And now AI arrives, and it is very good at fragments, as I argued yesterday. So the fragment begins to shrink further, one piece at a time, the bounded tasks lifting quietly out of your job and into the machine. If you are only your fragment, that is terrifying, and the fear is honest. But you were never only your fragment. The valuable part of you is the vision, the intuition, the synergy, the trust, the authenticity, the part no credential proved, no score measured, and no job description ever asked for. The trouble is that you cannot bring those from inside a fragment. And here is the harder truth for leaders. The organisation will not survive if its people stay fragments, because a company of fragments has handed its whole self to the machine, one piece at a time.

So the real question, the one I want to ask out loud and keep asking, is this.

How do we build organisations where people are not shrinking fragments, but are free to bring the ingenuity that was always in them and that no machine can copy?

I do not have the answer, and I want to be honest about that. I have the question, I think it is the right one, and I think it is far too big for any one person, or any one company, to answer alone.

The answer to this is not something we find once and keep. The moment we answer it, the world moves in response, and the question opens again, slightly changed. So we will find an answer that is true for today. Tomorrow, the world will have shifted, partly because of what we did today, and we will have to find it again. And the day after that, again. That is not a failure to be fixed. It is the reason this has to be a conversation that never closes, rather than a report that gets written once and filed. It is why I am building something that runs every day, all year, with many minds and the machine in the room, instead of standing on a stage to hand you my single answer.

Tomorrow, the most expensive mistake we might be making with this technology, the one that looks like progress and is quietly the opposite. And how to turn that on its head.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

This essay is day one of seven, the on-ramp to something I am building called Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. More this week.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.

Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work
katharinemclennan.com

Subscribe now

A week of daily provocations about the future of work . . .
just to get us started for a year of dialogue

(at least year, possibly 10 years, 20 . . . .? )

Today, the quiet question under every desk is whether your job survives AI. If you are just arriving, welcome; you can start anywhere.

What if your job is really just a fragment, now that AI has arrived. I want to start there because it sits beneath many quieter questions. Will my job survive this? Will I. People are asking it in the shower, on the train, at two in the morning, and they are mostly asking it alone, because it does not feel safe to say out loud at work. I am not going to wave that fear away. It is honest, and the disruption is real. But I think the fear is sharpened by a mistake in how we frame it, and if we fix the frame, the fear changes shape.

Here is the reframe. Your job was never the whole of anything. It is a fragment. Yesterday I argued that the job is a roughly two-hundred-year-old invention, a slice of whole work cut into a standardized, person-sized, repeatable piece to suit the machinery of the Industrial Age. That cut was brilliant for its time, and we have lived inside it so long that we mistook the fragment for the work itself. We say my job as if it were a whole thing, when it was always a part, designed to be supervised, measured, and replaced.

Now look at what AI is genuinely good at. It is good at fragments. It is good at the bounded, repeatable, well-defined slice: the invoice processed, the application screened, the report drafted, the clause checked. The better defined your fragment, the more exposed it is. That is the real source of the dread. It is not that AI has come for your humanity. It is that we spent two centuries turning work into fragments, and then we built a machine that is superb at fragments, and now the two have met.

But here is what the fear misses, and it is the most important thing I know about this moment. The real work was never in the fragment. It lives in the flows between the fragments. I spent four years on operational planning for the Sydney Olympics, facilitating more than forty separate functions and forty venues into a single operation that had to come alive by 7 pm, 15 September 2000, with the world watching. Nothing that mattered happened inside any one function. It happened in the seams, where someone held two parts in their head at once and saw what neither owner could see alone. The fragments were necessary. The value was in the connective judgment that no fragment contained.

That connective judgment is the part that stays yours. Reading a situation the data does not fully describe. Deciding well when the rules run out. Knowing which question to ask, and which answer to trust, and taking responsibility for the call. Holding the whole when everyone else can see only their part. None of that is a fragment, and none of it is what AI does. It is the most human thing you do, and it has been quietly undervalued for decades, precisely because it never fit neatly inside a job description.

So the question that keeps you up at night, will my job survive, is the wrong question, and its wrongness is what makes it so frightening. It assumes the fragment is you. It is not. The better question, the one that turns dread into direction, is this. What is the whole work that my fragment was only ever a slice of, and where do I, as a human, belong inside and outside of it now? Ask it that way and you stop defending a box and start looking for the flow.

The question for you is: how do I stop being a fragment on an assembly line and instead become the leader of a workflow from start to finish?

What next, then? I do not think anyone has a clean answer yet, and I distrust the people who say they have figured it out. What I am sure of is that we can not work it out alone, one frightened person at a time, each defending a single fragment. We work it out together, out loud, with the machine in the room as a participant rather than a threat.

That is how this week begins, and it is what I am building for the year ahead in an always-on 365-day dialogue that I hope to expand exponentially with humans and the capability of AI to synthesise and provoke wisdom — and completely new ideas behind the scenes.

In the coming two weeks, I will launch this dialogue.
Watch for the posts that invite you to join me.

No one person has the answer. This I know for sure. Just like we needed 3000 staff, 50,000 volunteers and 75,000 contractors to run the Sydney 2000 Olympics and Paralympics. Every single one — working for a flow that worked across 44 days and 40 venues.

Tomorrow I want to turn to the thing we spent thirty years calling scarce, and why I think we were hunting the wrong thing all along. It connects directly to this, because once you stop defending the fragment, you start to see what was actually valuable the whole time.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

This essay is day one of seven, the on-ramp to something I am building called Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. More this week.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.

Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work

katharinemclennan.com

Subscribe now

Invite me to speak at your next event.

Who Invented the Job?

Day one of seven. A daily reflection on what work actually is, before we drag the obvious technology into it.

Full disclosure, this is not the view from my actual desk, but I managed to swing it for one morning on the theory that a borrowed harbour might be exactly the right place to kick off seven days of serious daily thinking about the one thing none of us ever stops to question, which is work itself.

You have a job. You have a title, a description, a place on an org chart, and a number that represents you in someone’s budget. You have probably never asked who invented the idea of a job, or why, because it feels as natural as the weather. It is not natural. It is one of the most successful technologies ever built, and like all old technologies, it has become invisible to the people who depend on it.

For most of human history, people “did” “work.” The word is better as a verb than a noun. Work was varied, seasonal, and whole. A person planted, harvested, built, repaired, traded, and taught, and the boundaries between those things were soft. Then came the machinery of the Industrial Age, and machinery has a requirement that human variety does not satisfy. It needs the work fed to it in standardised, repeatable, supervisable pieces. Frederick Taylor brought a stopwatch onto the floor of Bethlehem Steel and timed men hauling pig iron, convinced that work could be studied and optimised like any mechanical process. Henry Ford applied the same logic and built the assembly line, where a car could be assembled in 93 minutes by people each doing one small, fixed, repeated task.

The job was the cut. It was the slicing of whole work into person-sized portions that could be timed, supervised, standardised, and replaced. As a solution to the coordination problem of its era, it was extraordinary, and the prosperity it produced was real. Railways crossed continents, cars remade daily life, and the standard of living rose for millions. I do not want to romanticise what came before or pretend the job was a mistake. It was an honest answer to a real question.

The trouble is that we kept the answer long after we stopped asking the question. We built an entire profession, mine, around administering the cut. Recruitment fills the boxes. Job descriptions define the boxes. Performance management measures people against the box. Succession planning replaces the person in the box. Headcount counts the boxes. Almost everything the people profession does assumes the box is the unit, and almost no one ever asks whether the box is the right unit, because the box is the ground we stand on.

I spent part of my childhood in occupied West Berlin, and one thing that city taught me early is that the structures people treat as permanent are often just decisions that hardened. The Wall looked eternal until the night it did not. Organisational structures are softer than concrete, but we defend them as if they were load-bearing walls rather than the scaffolding they actually are. We have lived inside the scaffolding so long that we mistake it for the building.

So here is the question I want to hold for the next seven days. If the job was invented to suit the machinery of one age, what happens to it when the machinery changes again, as it is changing now?

I am not going to reach for the obvious word yet. The technology everyone is talking about is part of this, but it is not where the thinking starts, and starting there is exactly the mistake I want us to avoid. The reframe has to come first. So this week I am questioning the most basic unit of our working lives, one idea a day, and I would like you to question it with me. Tomorrow, where the work actually lives, because it is almost never where the org chart says it is.

I am Katharine McLennan. After thirty-six years facilitating how people think together, I now bring human and machine intelligence into the same room to rethink what work and leadership become.

This essay is day one of seven, the on-ramp to something I am building called Human + AI What If, a year-long, around-the-clock conversation about the future of work, where people and AI think together and the whole of it becomes visible to everyone inside it. More this week.

Six ways to further our thinking together:

(1) SUBSCRIBE to this Substack and dialogue with me. I try to post five times a week, give or take.

Subscribe now

(2) COMMENT away on thoughts or questions you have upon reading this post.

Leave a comment

(3) SHARE the post onwards to people you think might be interested.

Share

(4) READ my book, Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. In it, I walk from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Order my book

(5) INVITE me to speak to your conference, board, or executive team.

Invite me to speak

(6) ASK me about my upcoming one-year-long, 24-hours-a-day, 365-days-a-year dialogue about work in the AI era, coming to these channels very soon.

Thank you for stopping by. I really appreciate your time.
Cheers, Katharine

Katharine McLennan, Facilitating the human + AI conversation about the future of work
katharinemclennan.com

Leave a comment

AI has ended the Information Age. What comes next is not a technology question, and it is not a procurement decision either; it is a leadership and culture choice, and every organization is about to make that choice whether or not anyone names it out loud, because the pressure of the new era does not wait for a board to put it on an agenda. You will drift into the Irrelevance Age, all speed without judgment and data without meaning, or you will build the Ingenuity Age, where human wisdom and machine intelligence make each other sharper. The old era rewarded whoever could store, search, and standardize. That era is over. Most of the tools we built to win it were built to sit still.

I learned this in one afternoon. I have just published a book called Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era, and many of the people who read it came back with the same request: they did not want another framework to admire, they wanted to run it, to point it at their own organization and see where they actually stood before anyone told them. So I asked my AI partner, Patrick Keough, to turn the models in the book into something working. It took him four hours. He built what would once have taken a team a year, pointed it at a single real company using nothing but public data, and watched it read that company’s leadership and culture across fifty-five questions, grounded in more than a hundred cited sources, scoring each claim against the book and showing its work.

Here is the part that matters. What we built is not a report. It is a living system, and the printed document is the least interesting thing about it, because I can run it again tomorrow against different questions, point it at new sources, cut the data another way, and then ask it what the answers might actually mean for the people inside. The PDF is a photograph. The thing itself is a moving picture.

None of this existed a year ago. The reason is the whole story, so it is worth a moment: for most of the short life of public AI, using it meant chat, where you open a window, you ask, and a single model answers from its own memory and from whatever you happen to paste in front of it. Chat cannot go anywhere. It cannot fetch a document, run a process, or check itself, and it will answer just as smoothly when it is guessing as when it knows. Then agentic AI arrived. An agent is not a voice in a window; it is a worker with tools, and when you give it a goal it plans the steps, reads thousands of real sources, writes and runs its own code, scores the evidence against a defined framework, and refuses to assert anything it cannot trace to a source you can open yourself. A model that talks has become a system that works.

Set that beside the tools our profession actually relies on, and the gap is uncomfortable. We have never had more software for engagement, performance, succession, recruitment, and reward, and through the early 2020s it grew steadily more tailored to whoever bought it. The tools are good. They are also, once built, frozen, because the best culture platform in the industry rests on science-backed surveys grouped into fixed factors, and its benchmarks refresh twice a year, every January and every July, against a set look-back window. Compensation data from the traditional houses is often six to eighteen months old by the time you read it. The deeper issue is architectural. In these systems the categories are decided before the data arrives, since the survey, the nine-box grid, the skills taxonomy, and the pay ladder are each a fixed schema, and the data is poured in to fill it. That fixedness buys their rigor. It is also why they can never answer a question nobody thought to model, or notice a pattern that did not exist when the schema was set.

An agentic capability inverts that order. Because it reasons over language instead of a fixed schema, the categories become an output, re-derived for the exact question in front of you, drawn from whatever sources happen to be in scope this morning rather than the ones somebody chose a year ago. It can read an organization’s own living evidence- the org charts, the performance reviews, the pay reports, the recruitment questions and answers, the exit interviews, and the training programs- and rebuild its own model as the conditions shift under it. It can hold a quiet, anonymous conversation with thousands of employees at any hour and in any country, adapting to what each person is reflecting on and asking for the example behind the comment. The model stops being something you fill in once a year. It becomes a partner you question every day.

I want to be careful here. The easy version of this argument is wrong, because the fixedness of the old tools is not a flaw to mock; it is what gives them their rigor, and an agentic capability earns its advantage only when it is governed, and only when deep human judgment sits at its center to aim it. The agent sees. The expertise aims. Neither is worth much alone. I have spent thirty-six years in leadership and culture, Patrick has spent his whole career building agentic systems, and the interesting thing here is not either of us on our own; it is what happens when those two kinds of expertise sit down at the same table and start asking each other questions.

We have outgrown the word tool. A tool is a fixed thing you pick up and put down, and what we are describing does not sit still long enough to be picked up, because it keeps working while you sleep, re-reading the world and revising its conclusions. What it really resembles is a partnership. Human wisdom and artificial intelligence, each lifting the other, the expert bringing judgment, context, and the questions that matter, while the agent brings reach, speed, and a tireless honesty about evidence. Put them together, and you have something new. The organizations that learn to work this way first are the ones that will still be standing when the Ingenuity Age arrives.

We built our example in an afternoon, on the public record alone, and it still saw more of that company’s leadership and culture than most insiders manage to put into words after years on the payroll. Now imagine it pointed inward. Imagine what it sees with your own people in the room.

I help leaders get their People & Culture capability ready for the AI era, working with AI to generate Ingenuity rather than Irrelevance.

Three ways in:

(1) Bring me in to speak to your conference, board, or executive team;

(2) Have me teach your People & Culture team to apply AI across the whole function, lever by lever; or

(3) Just message me, and we’ll brainstorm the first ideas you can play with.

Build the People & Culture capability on purpose, before it’s rebuilt for you.

Katharine McLennan
AI for the People & Culture function

My Book:

Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era

This book walks you through leadership and culture from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

Subscribe now

Yesterday, I wrote about an 80-year-old math problem that a machine cracked in 32 hours, and asked which age was opening for us, Irrelevance or Ingenuity. The question is bigger than one proof. Today I want to show you the map that organises it. Three ages. Two futures.

The map is one of the four pictures at the front of my book, and it is the simplest of the four. It runs from a steam engine in 1769 to whatever we are deciding to call 2030, layered by generation, scored by the technology each generation grew up assuming was just how the world worked. The story it tells is three ages, back-to-back. The Industrial Age, from 1769 to 1995, saw the development of machines. The Information Age, from 1995 to 2026, moved the data. The age opening now has no name yet. It has two.

In 2026, the timeline forks. Through one door, an Ingenuity Age, where humans use AI to amplify the very best of how we already think and decide and lead. Through the other, an Irrelevance Age, where AI quietly takes over the work and most of us drift into the role of audience members in our own organisations. Most leaders I talk to assume the door is theirs to choose. Most are not yet choosing.

There is a quieter pattern on the map that I had not noticed until I drew it. Each generation grew up inside a different age, with a different default sense of what work is for, what success looks like, what a leader does on a Tuesday afternoon when nobody is watching. Baby Boomers were trained in the late Industrial Age, where the job was efficiency at scale. Gen X grew up with the first PCs landing on the desk, half in Industrial habits and half in software. Millennials are the first natives of the Information Age, fluent in software, networks, and knowledge work. Gen Z arrived with the smartphone in the cradle. Gen A and Gen Beta are about to walk into the Ingenuity-or-Irrelevance fork wearing whatever default we hand them. Which is to say: we are the curriculum. They are the next age.

I am now working with the People and Culture function to facilitate the organisation's choice of the Ingenuity Age. We do this by championing talent and culture approaches that fit this age, and by inspiring leadership to change radically to meet it. P&C is the function that shapes whether the daily work of Attract, Enable, Develop, and Reward bends the organisation toward Ingenuity or quietly hands it to Irrelevance.

Look at the Talent levers through that lens, and the picture sharpens. Attract is no longer just about brand and reach. It is about whether the people who come into your orbit can already see the Ingenuity Age in you and choose you because of it. Enable used to mean a laptop and a chair, and now means AI fluency to do the work in a way that the last decade did not require, the way a thirty-year-old in 1996 had to learn email, a browser, and a search engine if they wanted to keep up. Develop used to mean training programs we measured by attendance, and now means a curriculum that grows the very human capabilities AI cannot replicate: curiosity, judgment, and trust. Reward used to be about what people did last quarter, and now has to recognise the human work that machines depend on but cannot do. Four levers. All four dials still set to 1995.

Look back at the map. Find your year of birth on the left. What world did you enter into? How has that world changed now that it is 2026? What are you doing this week to equip yourself so you can help your organisation, your neighbourhood, and your family steer toward Ingenuity? Choose on purpose. Or do not. Either is a choice.

Yesterday, a machine cracked an 80-year-old problem in 32 hours. Today, the map says it is 2026, and the next age is opening. Which one of your P&C functions is preparing your organisation for, on its very best Tuesday and its very worst, is the most honest answer to the question nobody at your leadership table is yet asking out loud. Ask it. Out loud.

I help leaders get their People & Culture capability ready for the AI era, working with AI to generate Ingenuity rather than Irrelevance.

Three ways in:

(1) Bring me in to speak to your conference, board, or executive team;

(2) Have me teach your People & Culture team to apply AI across the whole function, lever by lever; or

(3) Just message me, and we’ll brainstorm the first ideas you can play with.

Build the People & Culture capability on purpose, before it’s rebuilt for you.

Katharine McLennan
AI for the People & Culture function
My Book:

Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era. A walk through leadership and culture from the Industrial Age to the Information Age, the fork now opening between Irrelevance and Ingenuity, and the imaginative possibility waiting beyond.

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I have spent the last two years writing a book about a single fork in the road that opens up the moment the Information Age finally exhausts itself, which is happening now, in front of us, faster than anyone expected and far more quietly than the last age ended. Two doors open. Through one, we walk into an Irrelevance Age, where AI quietly takes over the work and most of us drift. Through the other, we walk into an Ingenuity Age, where AI takes over the grinding and we finally do the work only humans can do. I thought the fork was theoretical. Then last Friday, an article landed in my inbox that made it physical.

Ben Cohen’s piece in the Wall Street Journal led with one sentence I keep rereading. “A famous math problem that stumped humans for the better part of a century has finally been toppled by AI.” The problem is Paul Erdős’s unit-distance puzzle, posed in 1946 with a five-hundred-dollar bounty that nobody collected for eight decades, the kind of giant acorn the eccentric Hungarian was famous for dropping into the mathematical world before disappearing back into his suitcase and his next country and his next collaborator. OpenAI fed the question to one of its models. Thirty-two hours and around a thousand dollars in tokens later, it produced a proof. No human at a blackboard. No team of co-authors. Just the machine.

Cohen cites Timothy Gowers, one of the most decorated living mathematicians, statement: “There is no doubt that the solution to the unit-distance problem is a milestone in AI mathematics,” he wrote, adding that if a human had submitted the same paper to the Annals of Mathematics, he would have recommended acceptance without hesitation. As Cohen puts it, AI has gone in no time at all “from stupid to frighteningly smart.” Gowers went further. “It will become very difficult for humans to compete with AI at solving mathematical problems.” Sebastien Bubeck, one of OpenAI’s researchers, said it more directly. “Forget one year ago,” he told Cohen. “A month ago.”

Here is what I cannot stop thinking about. Cohen’s article points to three reasons AI succeeded where humans did not, and each one maps straight onto our choice as humans: whether to lean into AI on purpose or watch it lean into us by default.

Why did AI succeed after 80 years of humans attempting? Cohen describes three solutions that we need to take heed of, and use it to build our own ingenuity.

First, the model was willing to attack the problem from the angle that almost every human mathematician had quietly stopped trying, which is the angle of disproof rather than proof. Erdős had posed it as a conjecture, and decades of mathematicians lined up to prove him right. The AI lined up to prove him wrong. AI went about things counterintuitively. And won. By a mile. Our intuition is exceptionally strong, and AI might not replicate it. And our intuition can often lead to errors or missing the forest for the trees.

Second, and this one I have argued for years inside hospitals and universities and global corporations that were quietly drowning in their own narrow specialisation while the answer to the very problem they were chasing sat one floor up or one corridor over, the AI did what almost no human team has done well in living memory. It integrated. It pulled tools from algebraic number theory and stitched them onto discrete geometry, two corners of mathematics that rarely sit at the same table, in the way The Wisdom of Crowds (Surowiecki) is supposed to but almost never does inside our hyper-specialised institutions. We trained ourselves out of integration in the name of expertise. The AI never learned to stop.

Third, the AI had something we have all but lost. Time. Attention. Patience. Focus. Thirty-two unbroken hours of focus on one single question, while we are picking up kids, answering Slack, sitting in a meeting we did not need to be in, half-watching a screen on a Tuesday morning while a half-empty coffee goes cold next to us. Which sounds like a defeat, and is not. Because the trade is actually the most interesting one on the table. The machine gets the grinding. We get the asking. But we may also get our time to grow our questions, curiosity, and pondering about which questions may be important now. And we might enjoy life. A possibility.

It is genuinely easy, when you read a story like this one, to read it as the opening note of an Irrelevance Age that runs from now until the moment we all become spectators on our own former lives. Mathematics has been an exceptional expression of the human mind for two thousand years, and a machine just did it better, alone, in a day and a half, for the cost of a decent restaurant meal. If our cleverest territory falls this fast, what is left for us? Here is the fallback to “Irrelevance.”

The other possibility of “Ingenuity” is the one buried in Cohen’s own piece, in a single line from inside OpenAI that should be taped to the wall of every leadership team meeting in the country and read aloud at the start of every board agenda about technology. “Like a calculator,” they say, “AI is a tool that can expand our curiosity rather than destroy it.” Notice what that sentence does. It hands the human back exactly the thing we have been losing under the weight of our own busyness: the room to ask a better question.

Cohen himself is careful to mark the line. The ability to solve Erdős problems, he writes, is not the same as superhuman intelligence. And from inside OpenAI, the researcher Sebastien Bubeck offered the line I find most worth taping to a wall: “It’s fair to say that we haven’t seen yet the spark of genius that you could attribute to one of the grandest proofs in the history of humanity.” That spark is still ours. So is the question of what is worth solving in the first place, which is a much harder and more human question than any of the proofs.

Here is the line I keep coming back to in my own book. AI does not fix what is broken in us. It amplifies what is already there. Apply it to a curious mind and a strong culture, and you get the Ingenuity Age, the version of the next decade where the machine clears the underbrush, and the humans finally get to think. Apply it to a distracted mind and a tired culture, and you get the Irrelevance one. Either age is available from this point forward. Both are real. We just have to be honest about which one we are deciding on.

The unit-distance proof did not answer the question of what comes after the Information Age. It sharpened it. Will the next age make us irrelevant, or free us to be genuinely ingenious? The machines have just shown us what they do with their thirty-two hours, and the only thing left to decide, the one thing they cannot decide for us, is what we are going to do with ours, with the time and the attention and the questions only we know how to ask. Our move. Choose well. Now.

I help leaders get their People & Culture capability ready for the AI era, so we can choose Ingenuity over Irrelevance for humans.

Three ways:

(1) Bring me in to speak to your conference, board, or executive team;

(2) Have me teach your People & Culture team to apply AI across the whole function, lever by lever; or

(3) Just message me, and we’ll brainstorm the first ideas you can play with.

Build the People & Culture capability on purpose, before it’s rebuilt for you.

Katharine McLennan
AI for the Ingenuity in the People and Culture function
My Book: Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era

Sources

• Ben Cohen, “A Famous Math Problem Stumped Humans for 80 Years. AI Just Cracked It.,” Wall Street Journal, 29 May 2026.

Open any serious newspaper this year, and the verdict is the same. The Wall Street Journal reports that tens of thousands of white-collar jobs are already disappearing as AI starts to bite. The chief executive of Anthropic, the company behind one of the most powerful models on earth, says the technology could erase half of all entry-level white-collar jobs within a few years, and the chief executive of Ford put it more bluntly still, warning that AI will replace half of all white-collar workers in the United States. The headlines are loud. The numbers underneath them are louder.

And here is the quieter half of the story. While the work itself is being rewired underneath us, almost nobody is being retrained fast enough to keep pace. The World Economic Forum expects nearly two in five of the core skills we use at work today to change by 2030. Researchers at Stanford have already measured a steep, double-digit decline in early-career employment across jobs most exposed to AI, meaning the rising generation cannot find the first rung, let alone climb it. We are being outpaced and left under-prepared at the very same time. That is a dangerous combination.

Here is the part almost nobody is pricing in. AI does not fix a broken culture. It amplifies it. Point a genuinely powerful model at an organisation that already hoards information, punishes dissent, and rewards the loudest voice in the room, and you do not get wisdom at scale; you get dysfunction at scale, faster and cheaper and wrapped in the language of progress.

I drew the whole problem as a single map, and it sits at the front of my book. Two axes. Down the vertical axis, whether you have actually pointed AI at that strength or left it untapped. Across the horizontal axis, the strength of your leadership and culture.

A weak culture with minimal AI is simply IRRELEVANT, drifting toward an exit nobody chose. A weak culture with advanced AI is worse, OUTPACED by its own misdirected machines, scaling its very worst habits faster than any human in the building can see it happening, let alone stop it. A strong culture with untapped AI is the gentle failure, PRIMED for the moment and yet standing dead still. And then there is the one corner worth living in, a strong culture with AI deliberately deployed to amplify it: INGENIOUS. Nobody lands there by accident.

Now ask the obvious question. Which function in your organisation owns the habits, the hierarchies, the hiring, the rewards, the trust, and the unspoken rules, the exact material AI is about to amplify? It is the People and Culture function. And in most organizations, it is the one function sitting furthest from the AI strategy, treated as a downstream recipient of decisions already made in technology and finance, handed the change-management leaflet long after the real choices are locked.

I have spent thirty-six years on both sides of this, as a Chief People Officer on the inside and as a C-suite coach and clinical psychotherapist on the outside, and across all of it I watched brilliant strategies die in the narrow gap between what a company says it values and what it actually rewards on an ordinary Tuesday. That gap has always been expensive. AI makes it exponential.

The book is called Before the Fingerprint Fades, and the title is a warning, plain and simple. Your company has a fingerprint. It is the particular, hard-won, impossible-to-replicate way your people think and decide and treat one another when no process is watching, and it is precisely the thing a carelessly deployed AI will quietly sand down into a generic, efficient blur. That trace can fade.

So I am planting a flag. Starting today, I aim to write every weekday (good goal at least), walking the entire People and Culture function through this map one lever at a time, the way I would if your People and Culture team were sitting across the table from me with a real problem and a real deadline, no slides, no theory for its own sake. Lever by lever. I have started calling it the Ingenuity Function, because that is what the people function becomes the moment it stops administering the past and starts amplifying the future.

The question beneath it all is brutally simple, and every CPO is already answering it. Irrelevance, or Ingenuity? You answer it every time you approve a tool without asking what it amplifies, every time you dodge a hard conversation, every time you let a broken process calcify because the restructure is louder. The only real question left is whether you answer it on purpose. Most have not noticed yet. Let us change that.

Sources:

• WSJ, "Tens of Thousands of White-Collar Jobs Are Disappearing as AI Starts to Bite" (Oct 2025)
  • Axios, "Behind the Curtain: A white-collar bloodbath" — Dario Amodei, Anthropic (May 2025)
  • Fortune — Ford CEO Jim Farley warns AI will wipe out half of white-collar jobs, but the ‘essential economy’ has a huge shortage of workers (July 2025)
  • WEF, Future of Jobs Report 2025
  • Stanford Digital Economy Lab, "Canaries in the Coal Mine?" (2025)

I help leaders get their People & Culture capability ready for the AI era. Three ways in:
(1) Bring me in to speak to your conference, board, or executive team;
(2) Have me teach your People & Culture team to apply AI across the whole function, lever by lever; or
(3) Just message me and we’ll brainstorm the first ideas you can play with.

Build the People & Culture capability on purpose, before it’s rebuilt for you.

Katharine McLennan
AI for the People & Culture function
My Book: Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era

My book is out. Before the Fingerprint Fades: Leadership and Culture Readiness for the AI Era is now in hardback, paperback and ebook, and this Substack is where I am going to keep thinking out loud about the question that has taken over the last few years of my working life.

I have spent the last year trying to squash my 36 years of building frameworks in leadership and culture - testing them, rebuilding, etc — and then watching them all explode as AI has arrived. Now I have come back out the other side to bring you my ideas adjusted for a future that evolves exponentially faster than we have ever seen.

AI has ended the Information Age, and what comes next is not a technology decision but a leadership and culture one, a choice between drifting into the Irrelevance Age, fast and full of data and empty of judgment, and building the Ingenuity Age, where human wisdom and machine intelligence make each other stronger. The machines will not decide that for you.

I wrote it for the leader who can feel the ground shifting under the whole organisation, who was promoted for being certain, and who was never once handed a map for a moment that has no precedent.

The book looks at leadership and culture through six lenses:

1. history,

2. etymology,

3. philosophy,

4. neuroscience,

5. artificial intelligence, and

6. 36 years of practice inside and outside the C-suite.

Every chapter pairs hard research with questions and guides on how you can use my insights “on a Monday morning,” so you see how the brain behaves under real pressure, how AI is quietly reshaping the actual work, and what the most effective organisations on earth are doing differently from everyone else. It is not a theory of the future. It is a working manual for the present.

I built a self-assessment runs all the way through the book, so you are scoring your own ingenuity readiness as you read, and you finish the last page knowing exactly where you stand and where to begin on Monday morning. And your organisation in parallel.

Leaders I respect have stood behind it. A chief executive who has run NeoGenomics, Ortho Clinical Diagnostics and Cochlear called it a practical way to build organisations that stay human while AI moves fast, and the chief financial officer of Charles Schwab called it a roadmap for executives facing the next frontier of leadership. That is who I wrote it for.

So what is this Substack? It is where I think out loud between books, about the choice in front of us, the leaders getting it right, the ones getting it expensively wrong, and the practical tools you can put to work this week. Some weeks it will be an idea. Some weeks it will be a story. It will always be honest.

The fingerprint is still warm. The choices we make now, while the new shape is still soft and the window is still open, are the ones that harden into the organisations our children will work inside for the rest of their lives. I am glad you are here.

I bring this work to the keynote stage and into executive teams through Coach the C-Suite, my masterclass series for senior leaders.
Keynotes and executive workshops
Coach the C-Suite: coachthecsuite.training
Before the Fingerprint Fades is out now in hardback, paperback and ebook.