the collaboration principle

  • “FINALLY ON SIDE BY SIDE FROM NOUGHT ANEW”: WHAT TRUE LEADERS OWE TO THIS MOMENT IN TIME

    LEADING THROUGH THE INTELLIGENCE AGE SERIES (PART 2)

    In “Company” published in 1979, Beckett returns to that refrain again and again throughout his piece , as if starting over were not a failure but the only honest way forward. It simply is the recognition that certainty was never coming, and the decision to begin again anyway, from nothing, as many times as it takes.

    Leaders in the intelligence age are going to need exactly that discipline.

    This is not a piece for executives alone. It is a call to anyone who leads anything right now — a company, a ministry, a movement, a coalition — to see, think and act differently.

    Not a playbook to adopt if the numbers work out, but a small number of imperatives leaders cannot trade away, whatever the pressure to do otherwise, because leading exactly as before, on the assumptions of before, is no longer available to anyone.

    Part 1 of this series made the case for four conversations organisations need to hold as AI reshapes how they decide, learn, create and compete — a case made as much for cabinets and coalitions as for companies.

    This piece is about what leaders owe those conversations. Intelligence itself is not short of new models this year. Leaders are the ones who need them. These are the five imperatives we believe every leader owes this moment, whoever they are.

    The Hype and the Data


    Start with the evidence, because it is more sobering than most boardrooms, cabinets and executive committees have admitted. Three years of confident proclamations — mass unemployment, imminent AGI, a productivity bonanza — collapse against what has actually happened. And the reason isn’t that the technology is weak. It’s that pilots stall inside organisations that never change to use it.

    Hamel & Zanini, Closing the AI Hype Gap, Saïd Business School, July 2026. Eighty-nine percent of 6,000 executives surveyed reported no measurable productivity gain from AI over three years; AI added just 0.01 percent to total-factor-productivity growth in 2025. (Yotzov et al., NBER Working Paper 34836, March 2026; Penn Wharton Budget Model, September 2025)


    The same story repeats at scale. The overwhelming majority of enterprise pilots fail to deliver a measurable return, and most organisations experimenting with AI right now see no bottom-line impact from it at all. Only a tiny fraction call their rollout mature.

    MIT Media Lab, Project NANDA, The GenAI Divide, 2025 — 95 percent of pilots showed no measurable return. McKinsey & Company, State of Organizations, 2026, surveying more than 10,000 leaders across 16 countries — 88 percent of organisations experimenting with AI, 81 percent reporting no bottom-line impact, just 1 percent describing their rollout as mature.

    The pattern is not confined to the private sector. Governments show the identical shape, for the identical reason: bureaucracy, centralised decision-making, and a workforce without the skills to govern the tools it is being told to use. The clearest illustration ran for four months in Washington, where a much-publicised push to slash federal spending through AI-accelerated efficiency delivered a small fraction of what it promised — disruption mistaken for redesign.

    OECD, Digital Government Outlook, 2026. The US Department of Government Efficiency promised $2 trillion in federal savings; independent estimates put the actual figure closer to $160 billion, itself disputed. Hamel & Zanini, “America Needs a Smarter Government, Not Just a Smaller One,” Project Syndicate, June 2025 — the result, in their words, was “performative stunts” in place of meaningful reform.

    Civil society shows the same shape again: near-universal adoption, almost no strategic use. Most nonprofits have picked up AI tools individually and reactively rather than as part of any plan, and their leaders overwhelmingly point to the absence of direction from the top, not a lack of tools, as the real constraint.

    Virtuous, 2026 Nonprofit AI Adoption Report — 92 percent of nonprofits use AI in some form; 65 percent describe that use as reactive and individual; only 7 percent have embedded it into goals, budgets or planning; 67 percent of leaders cite the absence of strategic direction as the real constraint; fewer than a quarter have any formal AI governance policy.

    This is the gap in which the hype lives. A former chief information officer who spent years running technology inside major retailers has given its two failure modes their names. The first is wishing: the belief that AI is magic, that you can wave its wand at a hard problem and skip the work of solving it — sincere, and dangerous precisely because it is sincere. Its insidious cousin is washing: claiming to be doing more with AI than you actually are, usually because a board, an electorate, or a donor base wants to see progress a quarter can’t yet deliver.

    Julie Averill, former CIO of Lululemon and Nordstrom, “I Helped Run Lululemon. Companies Need to Stop Kidding Themselves About A.I.,” The New York Times, August 3, 2026.

    Both are common enough to be the norm rather than the exception, and both produce the same outcome: real cuts justified by a capability that doesn’t yet exist, followed quietly by the rehiring of the people who were let go.

    Writer & Workplace Intelligence, 2026 — 75 percent of executives admit their AI strategy is “more for show.” Challenger, Gray & Christmas, May 2026 Report — 97,000 US job cuts announced in May 2026 alone, 40 percent blamed on AI. Robert Half, May 2026 Labor Market Update — roughly a third of hiring managers who eliminated a role over AI had already rehired for the same or a similar one. (All cited in Averill, The New York Times, August 3, 2026)

    That is not efficiency. That is a leader discovering, after the fact, that the capability they claimed never existed. The cost isn’t only financial — a meaningful share of the workforce, especially its youngest members, now admits to actively working against its own employer’s AI rollout. Trust, once spent this way, does not come back on request, whether it belongs to a workforce, a public, or a membership base.

    Writer & Workplace Intelligence, 2026 — 44 percent of Gen Z workers, and roughly a third of the wider workforce, admit to actively sabotaging their own company’s AI rollout.

    And the world is not slowing down to let those models catch up. Half a billion years ago, the Cambrian explosion was the brief geological moment when life suddenly diversified from a handful of simple forms into nearly every major body plan that exists today.

    Software is living through its own version of that moment: coding agents collapsing the cost of building so fast that the population able to build is expanding by orders of magnitude, tools and architectures multiplying faster than any single leader can track. Robotics is entering the same phase behind it. There is little reason to think the pattern stops there.

    What is coming is not a market shift to manage. It is a Cambrian explosion of everything — and no leader, in business, government or civil society, gets to sit this one out.

    At the Level of Discernment

    The most useful finding in the research on AI’s limits isn’t that it’s weak — it’s where. AI performs brilliantly on structured tasks with a clear, checkable answer, and underperforms, sometimes badly, on the ambiguous, multi-step problems that depend on judgment and context.

    The reason traces back to how these systems actually work: they predict the next word, not the state of the world. They hold no persistent model of how things causally relate to each other, which is why they struggle with reasoning, counterfactuals, and anything that unfolds over time.

    Dell’Acqua et al., Organization Science, 2026 — the “jagged technological frontier.” Marcus, Quattrociocchi & Capraro, 2026 — the “world model” problem.

    The discipline is the same whether the decision is a hospital’s triage protocol, a city’s permitting queue, or a company’s underwriting call: know where that frontier runs before you hand something across it. Leaders owe their institutions discernment over delegation — knowing exactly which judgments the model can carry, and which must remain, irreducibly, theirs.

    At the Level of Honesty

    One of AI’s most prominent researchers put it bluntly in early 2026: the entire industry has been swept up in its own hype. The discipline this moment calls for is testing bold claims before repeating them, not after — especially the claims made by people whose financial and reputational interests are served by exaggerating what the technology can do.

    Yann LeCun, interview, The New York Times, January 2026 — “the entire industry has been LLM-pilled.”

    The same standard has to apply after the decision, not only before it. Averill tells the story of an employee who gave a company two decades of work before being told, in a short meeting, that software could now do her job. It couldn’t, not really — she was the person who knew why the numbers looked the way they did, the context no tool could see. The leaders who quietly rehired for roles they had just eliminated confirm the pattern from the other side: the efficiency never existed. Only the decision to blame something other than themselves for cutting it did.

    What leaders owe here is honesty over performance — the same discipline applied twice, whether the claim is a company’s earnings call, a government’s savings announcement, or a nonprofit’s annual report: tested before it is repeated, owned after it is acted on. A model does not get to carry blame, or credit, that was never really its to carry.

    At the Level of Structure

    Where AI has actually worked, the pattern is consistent: it required rebuilding, not addition. The clearest gains show up only where AI was built into a redesigned workflow, never where it was layered onto an old one — and the organisations getting the most out of it are consistently the ones willing to rethink how the work gets done, not just which tool touches it.

    Stanford Digital Economy Lab, The Enterprise AI Playbook, April 2026 — a median 71 percent productivity gain across 51 successful deployments, all built into redesigned workflows. McKinsey & Company, State of Organizations, 2026 — highest-performing organisations three times more likely to have fundamentally redesigned how work gets done.

    Averill’s own account of running technology at two major retailers bears this out from the inside: the projects that delivered took time, people and real budget to fit around how the business actually ran, while the pilots that failed wanted clean, connected data and consistent decisions from a company that, like most real ones, ran on a dozen systems that did not agree with each other.

    Government and civil society tell the identical story from the other side of the ledger. Public AI strategies routinely fail to translate into practice because the underlying structures — procurement, data, workforce skills — go untouched, and nonprofit leaders report the identical stall: initiatives that never scale past isolated tasks because nobody set the direction.

    OECD, Digital Government Outlook, 2026; Virtuous, 2026 Nonprofit AI Adoption Report — 67 percent of nonprofit leaders cite the absence of strategic direction as the reason AI initiatives never scale.

    The same root cause shows up wherever pilots fail: organisations avoid the friction of genuine integration — the retraining, the redesign, the hard conversations about who decides what — and reach for the announcement that skips it instead. Barely a fifth of firms were running AI in production at scale as of early 2026, against the overwhelming majority that had expected to get there twelve months before.

    MIT Media Lab, Project NANDA, 2025; UBS, AI Adoption Survey, March 2026 — 19 percent of firms in production at scale, against an 84 percent expectation twelve months earlier.

    That gap is exactly the redesign work leaders keep deferring — and deferring it forever carries a price already being paid. Leaders, of companies, of ministries, of movements, owe their institutions redesign over bolt-on. Anything less just produces a faster bureaucracy, not a different one.

    Hamel & Zanini — bureaucracy costs the global economy roughly $3 trillion a year in lost productivity.

    At the Level of Collaboration


    Ashby’s Law, which opened Part 1 of this series, still governs: only variety can absorb variety. A frontier this jagged, shifting by function and by task, cannot be navigated by a single point of view, however well-informed. It requires structured, cross-functional sense-making — the kind that turns scattered individual experimentation into a collective, integrated capability. Most organisations are still doing only the former, largely alone.

    McKinsey & Company, State of Organizations, 2026 — 88 percent of organisations are experimenting with AI individually rather than collectively.

    We have watched plurality do this work outside the private sector too. Part 1 of this series described an international coalition that found, in two days of structured deliberation, what years of formal coordination had missed. The mechanism does not check what kind of institution is using it. Leaders owe plurality over uniformity. It is not a cultural nicety here. It is the only mechanism precise enough to track a frontier this uneven.

    At the Level of Renewal

    The refrain that opened this piece belongs here too. Amid a Cambrian explosion of everything, no leader — including us, and including whoever is currently defending a government’s approach or a movement’s — gets to hold the same answer for long. Leaders owe renewal over preservation: the discipline to keep starting anew rather than defend what worked last quarter.

    Finally on, from nought anew, as many times as it takes.

    Immanuel Kant’s categorical imperative doesn’t ask what a leader can get away with. It asks what is owed — to the decision, to the people affected by it — regardless of convenience, regardless of who is watching. What if this became a universal law? Kant’s answer does not bend to circumstance: it holds, or it was never a duty at all.

    That is the standard these five imperatives are written to meet — not a strategy to adopt if the numbers work out, but obligations leaders cannot trade away, whether they answer to shareholders, to citizens, or to a cause.

    The organisations who wait for certainty before starting will be led by people still running yesterday’s decision models on tomorrow’s problem. The Collaboration Principle exists to help leaders — in companies, in institutions, in movements — build these five imperatives into how they actually think, decide and act — not as a framework to admire, but as a duty to practise.

    If you recognise this in your organisation, your institution, or your cause — the sense that the old models are running out faster than new ones are arriving — we would be glad to have a chat with you.


    Antoine Viornery — Founder, The Collaboration Principle

  • GOING ON BEING IN THIS STRANGE WORLD

    Why the Old Sources of Meaning Have Run Out — and What Organisations Can Build in Their Place..

    Before We Talk About Purpose

    I have carried a passage from Baudrillard for over a decade. It is the bleakest, most precise description of the world we live and work in that I have ever read.

    “We will live in this world, which for us has all the disquieting strangeness of the desert and of the simulacrum, with all the veracity of living phantoms, of wandering and simulating animals that capital, that the death of capital has made of us—because the desert of cities is equal to the desert of sand—the jungle of signs is equal to that of the forests—the vertigo of simulacra is equal to that of nature—only the vertiginous seduction of a dying system remains, in which work buries work, in which value buries value—leaving a virgin, sacred space without pathways, continuous as Bataille wished it, where only the wind lifts the sand, where only the wind watches over the sand.”

    — Jean Baudrillard, Simulacra and Simulation

    He wrote that in 1981, describing the death of a system most people had not yet noticed was already dying. Forty-five years later, it has never felt more accurate. Not because capital has died, but because the architecture that used to manufacture meaning inside organisations — hierarchy handing down purpose, tradition handing down belonging — is the thing now buried under its own weight. What is left looks a great deal like Baudrillard’s desert: more signs than ever, more dashboards, more all-hands meetings explaining the new strategy, and underneath all of it, a growing number of people who could not tell you, with any conviction, what their work is actually for.

    I am writing this because that gap — between the volume of signals organisations produce and the silence where meaning used to be — is the central organisational problem of this decade. And because there is something specific that can be done about it.

    The Paradox Nobody Wants to Name

    We have more tools than any generation before us. More channels to communicate, more platforms to express ourselves, more data to inform our decisions, more AI to accelerate our thinking. And inside organisations everywhere, the same quiet crisis is spreading anyway: people do not know what their work is for anymore.

    This is not a motivation problem. It will not be solved by a better bonus structure or a more inspiring town hall. It is something deeper — a loss of the felt sense that what I do here matters, that the system I am part of is oriented toward something worth orienting toward, that my specific contribution, irreplaceable and unrepeatable, is actually needed.

    Global employee engagement fell to 20 percent in 2025, its lowest level since the pandemic. Gallup puts the resulting cost in lost productivity at 10 trillion dollars a year — 9 percent of global GDP. In the United States only a third of employees are engaged, a decade low. In Europe, engagement sits at just 13 percent. (Gallup, State of the Global Workplace, 2025–2026)

    Ashby put it plainly: nobody knows what to do against the purely new. The world we are navigating is purely, relentlessly new. AI is not just automating tasks; it is dissolving the boundaries of what counts as skilled work.

    The World Economic Forum projects that AI and adjacent technologies will displace 92 million jobs by 2030 while creating 170 million new ones — a net gain of 78 million, but one that requires 39 percent of the average worker’s existing skill set to be transformed or made obsolete along the way. (World Economic Forum, Future of Jobs Report, 2025)

    The pace of change has outrun the capacity of any single person, or any single leadership team, to hold enough of the picture to give coherent direction. Meaning, which used to be handed down through hierarchy and tradition, can no longer be manufactured at the top and distributed downward. It has to be found, or more precisely, it has to be made, collectively, from the inside.

    The organisations that will navigate what comes next are not the ones with the best strategy documents. They are the ones whose people have rediscovered why they are here together, and have the conditions to act on that answer.

    Loyalty Was Never the Real Problem

    For years the convenient story about disengagement was that loyalty itself had eroded — that people simply cared less than they used to. The data tells a more precise story. Loyalty has not disappeared. It has become conditional on something organisations stopped supplying.

    Across EMEA, intent to stay fell from 66 percent in 2024 to 62 percent in 2025. But nine in ten engaged employees intend to stay with their organisation, against roughly five in ten of the disengaged — and a ten-year trend analysis shows belonging and feeling valued sliding to the bottom of what drives retention, while confidence in senior leadership and trust in how change is managed have risen to the top. (Perceptyx, Employee Experience Trends, 2025–2026)

    Employees have not stopped asking what their employer offers them. They have started asking a harder question: do I believe this company will succeed, and will I succeed with it. That question is, in the end, a question about meaning. People do not commit discretionary effort — the kind no performance review can mandate — to a system they cannot see the point of.

    Nine in ten employees say they would trade an average of 23 percent of their future earnings for work that felt consistently meaningful. Those who experience their work as highly meaningful stay, on average, 7.4 months longer than those who do not; among managers who find deep meaning in their own work, turnover falls to 1.5 percent, less than half the national average. (BetterUp, Meaning and Purpose at Work, 2025)

    Replacing an employee who leaves anyway costs an estimated 50 to 200 percent of their annual salary, rising past 200 percent for senior and specialised roles. (SHRM; Gallup, 2025)

    Loyalty was never the problem. The absence of something worth being loyal to was.

    What We Actually Do About It

    At TCP, this is the work we consider most important and most often overlooked: helping organisations rebuild a living, shared sense of purpose — not as a communications exercise, but as an embodied, collective experience.

    The methods we use are drawn from decades of large-group facilitation, collaborative design, and the study of how meaning actually forms in human systems. They are not workshops in the conventional sense. They are designed experiences, in which the conditions for genuine encounter are created, and something real can happen.

    We work at three levels simultaneously.

    The first is the individual. Before a person can contribute their full intelligence to a collective, they need to reconnect with what they actually care about — not what the job description says they should care about, not what the latest employee survey revealed as collective sentiment, but what they, specifically, bring to this work that no one else brings in quite the same way. We design processes, drawing on dialogue practice, reflective inquiry, and structured peer exchange, that create the space for this reconnection to happen. People are often surprised by what surfaces. The purpose they thought they had lost turns out to have been waiting, just beneath the noise.

    The second level is relational. Purpose does not live in individuals in isolation. It lives in the quality of the connections between them. We use a blend of methods in large-scale systems intervention to bring people into genuine contact across the silos and hierarchies that normally keep them apart. When a logistics manager and a strategy director and a field coordinator from three different continents sit together and talk honestly about what they are trying to do and why it is hard, something shifts. Not because they have agreed on a new framework, but because they have recognised each other as people working toward something shared. That recognition is the substrate on which purpose is rebuilt.

    Google’s own research into what separates its highest-performing teams from the rest — Project Aristotle, which studied more than 180 teams — found that psychological safety accounted for the largest share of the variance in team performance of any factor measured. Teams with high psychological safety were 19 percent more productive, 31 percent more innovative, and had 27 percent lower turnover than teams without it. (Google re:Work; Edmondson, The Fearless Organization, 2018)

    Relational purpose and psychological safety are not separate projects. They are the same infrastructure, built from two directions.

    The third level is systemic. Once individuals have reconnected with their own sense of meaning, and relationships across the organisation have been reactivated, we work with leadership to translate that energy into the structures and rhythms of the organisation itself — how decisions are made, how learning is shared, how contribution is made visible, how the organisation signals, every day, that the people in it are the point, not a resource to be optimised.

    These three levels do not work independently. The individual work without the relational work produces insight that goes nowhere. The relational work without the systemic work produces connection that cannot sustain itself. The power is in holding all three together, across a room of twenty people or four hundred, across a two-day intensive or a six-month transformation journey.

    Where AI Stops and People Begin

    The instinct, faced with numbers like these, is to assume AI is coming for what is left of meaningful work. The evidence says something more specific, and more useful.

    PwC’s annual AI Jobs Barometer, built from close to a billion job postings worldwide, found in its 2026 edition that AI is splitting the labour market into two tracks. ‘Professionalised’ roles — where AI absorbs the routine parts of a job and leaves human judgement and expertise to do the rest, such as radiology or recruiting — are growing twice as fast, with 42 percent faster salary growth, than roles merely ‘democratised’ by AI, where the technology simply makes the job easier for non-experts to do. The new tasks being added to AI-exposed jobs are two and a half times more likely to require empathy, judgement, and creativity than the tasks they replace. Workers with AI skills now command a 62 percent wage premium over otherwise similar roles, up from roughly 25 percent two years before. (PwC, Global AI Jobs Barometer, 2026)

    McKinsey’s research points to the same conclusion from a different angle: as AI absorbs the chores of sifting information, organising data, and drafting first versions, what remains is judgement, relationship-building, critical thinking, and empathy — the capabilities machines do not yet offer.

    More than 70 percent of the skills employers look for today apply to both automatable and non-automatable work, depending on how they are deployed; another 12 percent remain entirely human, for now. (McKinsey Global Institute, 2025)

    What that means in practice is specific, not abstract. Roles built on sustained human interaction — nursing, therapy, teaching, frontline care — consistently rank among the hardest for AI to touch, because the interaction itself is the value being delivered, not a process wrapped around it. In healthcare, the cases that matter most — end-of-life decisions, rare or ambiguous diagnoses, the conversation where a clinician has to deliver news no algorithm should deliver — depend on context, judgement, and empathy that cannot be outsourced. In organisations, the work of leadership, negotiation, and ethical judgement under uncertainty runs on the same human substrate. AI can inform all of this. It cannot stand in the room.

    This is exactly the work this practice exists to build the conditions for. Not because we are nostalgic for human-only work, but because the parts of organisational life that are becoming more valuable, not less, are the parts that depend on people trusting each other enough to think, decide, and act together.

    Organisations that deliberately design how humans and AI work together — rather than letting the technology arrive unmanaged — are 2.4 times more likely to report both stronger financial performance and more meaningful work for their people. Deliberate design, not the technology itself, is the variable that decides which way it goes. (Deloitte, Global Human Capital Trends, 2026)

    What Becomes Possible

    Organisations that go through this work tend to describe a shift that is difficult to quantify and impossible to miss.

    • At the human level, people re-engage. Not because they have been told to, but because they have remembered that engagement was available to them all along, and that the organisation, perhaps for the first time in years, has made room for it. Discretionary effort, the kind that no performance management system can mandate, returns. Attrition slows. The people who stayed because they had nowhere else to go start staying because they want to be here.
    • At the operational level, alignment accelerates. When people share a genuine sense of purpose, the friction that normally characterises cross-functional work diminishes. Decisions that used to require three layers of sign-off start being made by the people closest to the problem, because those people now trust each other and share a common orientation. The organisation becomes faster, not because it has been restructured, but because the relational infrastructure that makes speed possible has been rebuilt.
    • At the strategic level, the organisation develops resilience of a kind that cannot be purchased or planned. When the next disruption arrives, and it will, the question will not be whether the leadership team has the right answer. It will be whether the organisation has enough shared understanding, enough genuine connection, enough activated intelligence distributed across its people, to find the answer together. That capacity is what this work builds.

    Companies that lead with genuine purpose have commanded valuations up to four times higher than low-purpose peers during periods of crisis, with 40 percent higher retention and 30 percent higher innovation output; employees at high-purpose companies are far more confident in their organisation’s growth than employees elsewhere, by a margin of roughly 82 percent to 48 percent. Over twenty years, purpose-led companies have outperformed the S&P 500 by a factor of five. (Deloitte; Jump Associates, Payback on Purpose)

    Purpose, in the end, is not a statement on a wall. It is the lived experience of doing something that matters, with people you trust, toward an end you believe in. That experience can be rebuilt. We have seen it happen, in multilateral organisations and global corporations, in leadership teams that had stopped talking honestly to each other, and in frontline teams that had never been asked what they thought.

    It begins with making room for people to go on being: singular, irreplaceable, and genuinely needed.

    Going on being was never guaranteed by the world. It has always had to be built.

    Antoine Viornery — Founder, The Collaboration Principle

  • WHAT DOES IT TAKE TO TRUST?

    The Condition Every Organisation Claims to Want and Almost None Have Built.

    Before We Talk About Culture

    I have been working in a lot of rooms. Leadership teams in Paris, boardrooms in Singapore, strategy sessions in Geneva, Cairo, Ahmedabad, Melbourne — from 6 individuals to four hundred people who had never really spoken to each other before and were suddenly asked to think together for three days. Off-sites where the real conversation happened in the corridor during the coffee break, and never made it back into the room.

    In almost every one of those rooms, at some point, someone said the word “trust.”

    Usually in a sentence that began with: what we really need around here is more…

    And I have spent twenty-five years watching what organisations actually do next. The town hall where the CEO explains the new values. The team-building day with the ropes course. The engagement survey, the results shared six months later in a slide deck, the action plan that lives in a shared drive no one opens.

    None of it works. And everyone knows it doesn’t work. And they do it anyway, because doing something that looks like trust-building is much easier than doing the thing that actually builds trust.

    I am writing this because I think we have been wrong about what trust is. And because getting it right matters more right now than it ever has.

    Self-Trust Is Not a Leadership Competency. It Is a Foundation.

    Goethe’s instruction sounds deceptively simple: “Trust yourself, then you will know how to live”.

    In an organisation built on hierarchy, approval cycles, and the careful management of visibility, that sentence is borderline subversive.

    We have designed systems — at enormous cost, over decades — that systematically replace individual judgment with process. That substitute compliance for conviction. That reward the performance of confidence while quietly punishing the exercise of genuine discernment. You get promoted for having the right answers, not for asking the questions that matter. You get ahead by being aligned, not by being honest.

    The result is organisations full of capable, intelligent people who have learned — rationally, as a survival strategy — not to rely on their own perception of what is true, what matters, and what needs to happen.

    People who wait to be told rather than acting on what they know.

    People who have, in the most precise sense of the word, lost trust in themselves.

    This is not a character flaw. It is a rational adaptation to an irrational environment.

    And it is costing organisations more than they can measure.

    What Self-Trust Actually Looks Like

    Leonardo da Vinci did not wait for a leader to tell him which boundaries were worth pushing. Marie Curie did not require organisational sign-off to follow the question that consumed her. Frank Lloyd Wright did not design Falling Waters by compromise.

    We are not suggesting your organisation needs geniuses. We are suggesting it needs the conditions in which ordinary human intelligence — the kind every person walking through your door already carries — can actually be used.

    What da Vinci, Curie, and Wright shared was not superhuman talent alone. It was the willingness to press hard on their own understanding. To strip away received wisdom until they reached something they could genuinely stand behind. And then to act from that place with commitment, in the face of uncertainty, resistance, and the very reasonable possibility of being wrong.

    That capacity is not rare. It is suppressed.

    In every large-group session we have ever facilitated, at some point in the second day, something shifts. People stop performing expertise and start thinking out loud. They stop managing their visibility and start actually engaging with the problem. The quality of the conversation changes completely. The ideas that come out of that state are different in kind from the ideas that come out of polished presentations and pre-cooked consensus.

    What changed? Nothing except the conditions. The space became one where it was safe to trust your own thinking.

    That is the foundation. Everything else — relational trust, systemic trust, organisational performance — depends on it.

    Trust Is the Connective Tissue. And Most Organisations Have Severed It.

    Individual self-trust matters enormously. But it does not operate in isolation.

    The organisations we have seen perform at the highest level — under pressure, in conditions of genuine complexity, when the stakes were real — are not simply collections of self-trusting individuals. They are systems in which trust operates as connective tissue, flowing between people, across silos, through the layers of hierarchy that would otherwise trap it.

    When trust is present at this level, everything changes.

    Conversations become more honest. Which means they become more useful. Decisions draw on better information, because people share what they actually know rather than what they calculate is safe to say. Disagreement becomes generative rather than political. Learning accelerates, because failure can be examined rather than concealed.

    This is not idealism. We have watched it happen. We have helped design the conditions that produce it.

    The research is unambiguous: psychological safety — which is trust made structural — is the single strongest predictor of team performance across every measure that matters. Not talent density. Not leadership charisma. Not strategy. Trust.

    The question is not whether trust is valuable. The question is how to build it, reliably and at scale, in organisations that have often spent years — sometimes decades — eroding it.

    You Cannot Train Your Way to Trust

    Organisations consistently treat trust as a culture initiative. Something you install through communication, workshops, values posters, leadership development programmes. Something you can buy and deploy.

    You cannot.

    Trust is not a communication product. It is not something you can declare into existence. It is not produced by a facilitator who helps a team get vulnerable for two hours on a Tuesday and then sends them back to a system that hasn’t changed.

    Trust is a structural property of a human system. It is built — or destroyed — through the accumulation of thousands of small moments in which people discover whether reality is safe to tell, whether judgment is safe to exercise, whether they will be supported when they act on what they actually believe.

    Those moments are shaped by design. By the decisions you make about how information flows, how decisions get made, who is in the room when the important conversations happen, and what happens to people who tell inconvenient truths.

    You can design for trust. Or you can design against it. But you cannot escape the fact that you are always designing one or the other.

    Three Levels. All Three. At the Same Time.

    In twenty-five years of this work, we never believed in sequential transformation. You cannot fix the individual, then fix the team, then fix the organisation. By the time you get to step three, step one has regressed.

    Trust has to be built simultaneously at three levels.

    At the individual level: people need to reconnect with their own capacity for honest self-assessment. Before anyone can trust across an organisation, they have to have had the experience of articulating what they actually think — not what they are supposed to think, not what is strategically advisable to say, but what they actually know and believe. We design processes that create that space. The results consistently surprise participants. The clarity and conviction that emerge when people are genuinely invited to trust their own perception turns out to have been there all along, waiting for the conditions.

    At the relational level: trust between people does not form through team-building activities or away-days. It forms through the experience of having thought through something genuinely difficult together and having arrived somewhere neither could have reached alone. We have seen this happen in groups of twenty and in groups of four hundred. When a person discovers that the colleague across the silo holds knowledge that directly illuminates their most difficult problem, something in the relational field shifts. That shift is the beginning of trust. We design sessions that produce that experience — deliberately, reliably, at scale.

    At the systemic level: individual and relational trust cannot survive contact with an organisation structurally designed to suppress them. Decision-making processes that perform distributed intelligence rather than practicing it. Communication rhythms that filter honest information rather than enabling it to flow. These are not soft problems. They are design problems. And they have design solutions.

    Individual self-trust without relational trust produces isolated brilliance the system cannot absorb. Relational trust without systemic trust produces pockets of genuine connection that get crushed on contact with the organisation’s actual operating logic.

    The power is in building all three simultaneously. That is what our large-group methodology is designed to do.

    What Becomes Possible When Trust Is Actually Present

    At the human level: people show up differently. Not because they have been told to bring their whole selves to work, but because the organisation has actually created conditions in which doing so is safe. The quality of thinking improves. The quality of relationship improves. The quiet, grinding exhaustion of navigating an environment you cannot trust begins to lift.

    At the operational level: speed increases dramatically. Trust is, among other things, the most powerful friction-reducer available to any organisation. When people trust each other’s judgment and intentions, the elaborate systems of checking, approving, escalating, and covering that consume so much organisational energy become largely unnecessary. Things move.

    At the strategic level: the organisation becomes genuinely adaptive. When trust is distributed across a system rather than concentrated at the top, the system can sense and respond to change from anywhere within it. It does not have to wait for the signal to travel up the hierarchy and the instruction to travel back down. It can act, at the point closest to the reality that requires action, with the confidence that the rest of the organisation will understand and support what it is doing.

    This is not a vision for the future. It is a description of what we have seen function, repeatedly, in organisations willing to do the actual work of building it.

    The Beginning Is Always the Same Place

    In Alice’s Adventures in Wonderland, the King’s advice to the White Rabbit was right, simple and direct: “Begin at the beginning”.

    And the beginning — always, in every organisation we have ever worked with — is trust. Not as an aspiration or a cultural value statement. Not as an item on the leadership agenda. But as a living, structural, actively maintained property of the human system.

    That is where capability comes from. That is where collective intelligence comes from. That is where organisations find the capacity to face whatever comes next — including the things they cannot yet see coming.

    We have been building it for twenty-five years. In organisations that were thriving and in organisations that were breaking apart. We know what it takes. We know what it costs when it’s missing.

    Antoine Viornery — Founder, The Collaboration Principle

    This post owes a great debt to Josie Gibson, who first asked this question on our shared blog back in 2013 — and answered it with the precision and warmth that characterize everything she does. It was a privilege to think alongside her then. She’s doing amazing work at http://www.catalyst-fx.com/.

  • THIS IS THE MOMENT THE AID SECTOR BECOMES WHAT IT ALWAYS PROMISED TO BE.

    Why the Global Development System Must Learn to Think Together — Starting Now.

    Before the Argument Starts.

    I have spent more than a decade working alongside these organizations. WHO. UNDP. GAVI. WFP. World Bank Group. In Geneva, yes — but more importantly, in the field. In West Africa during vaccination campaigns. In the Middle East when the coordination tents were the only structure left standing. In Southern Asia with teams trying to hold programs together with less than they needed and more commitment than anyone had a right to expect.

    I have seen what happens when a good idea leaves Geneva, New York, Washington, Rome or Paris. I know the distance between a strategy document and a community health worker standing in the rain with no supplies and no signal. I have been in those rooms — the ones where the people doing the actual work explain, patiently, again, what is really happening on the ground, and watch the information travel upward and arrive somewhere unrecognizable.

    It has been one of the privileges of my working life to be trusted with that work. These are not faceless bureaucracies to me. They are colleagues. Friends. People who gave years — in some cases, decades — to something they believed in. People who still do.

    That is why I am writing this. Not to bury these organizations. To fight for them.

    The Age of the Professional Humanitarian Is Ending.

    Not because the need is disappearing. The need is larger than it has ever been. But the architecture that was built to respond to it — the agencies, the frameworks, the funding flows, the whole elaborate system of global solidarity that took 80 years to construct — is breaking apart faster than anything is being built to replace it.

    • 860 million people still live in extreme poverty. 733 million go to bed hungry every night. Climate-related displacement is projected to reach 1.2 billion people by 2050. The need has never been greater. The system has never been more fragile. (UN, FAO, World Bank, 2025)

    This Is Not a Funding Crisis.

    Global official development assistance fell by 23.1% in 2025 — the largest annual contraction in the recorded history of ODA, according to the OECD. That single statistic does not capture what it means in practice: 86% of USAID programs terminated, WHO cutting its Geneva headquarters from 76 departments to 34, a quarter of the WHO workforce — over 2,300 positions — eliminated by mid-2026. The multilateral system is running on reserve funds it will exhaust before the year is out.

    This is not a funding crisis. It is a legitimacy crisis. And underneath it, a design crisis.

    • ODA fell from USD 215 billion in 2024 to USD 174 billion in 2025 — bringing it back to 2015 levels. The OECD projects a further 5.8% decline in 2026. The US alone accounted for 57% of the total drop. Core contributions to the UN system fell by 27%, the largest annual decline on record. (OECD, April 2026)

    The Old Model Was Always a Fiction.

    The old model assumed that impact flowed from the top down — that resources, knowledge, and solutions originated in the North and were delivered to the South. That model was always contested. Now it is collapsing. And the question is not how to save it. The question is what comes next, and who gets to shape it.

    • Of the USD 174 billion in ODA disbursed in 2025, ODA to Ukraine alone — a single country — exceeded the total bilateral aid provided to all Least Developed Countries combined, and all of sub-Saharan Africa combined. The geographic and political distortion of the system is no longer deniable. (OECD, 2026)

    The Pivot Is Real. But It Goes Dangerously Shallow.

    The pivot everyone is talking about — toward private finance, toward philanthropy, toward development banks and blended mechanisms — is real and necessary. GAVI’s new 2026-2030 strategy (Gavi 6.0) points in this direction. Lean delivery, measurable outcomes, results tied to disbursement. That logic is right. The world cannot afford to fund process. It must fund impact.

    But here is where the conversation goes dangerously shallow.

    • At GAVI’s June 2025 replenishment summit, world leaders secured USD 9 billion against a USD 11.9 billion target — a USD 2.9 billion shortfall. Private sector and development finance institutions unlocked an additional USD 4.5 billion in complementary financing, signaling the direction of travel. The model is shifting from grants to outcomes-based investment. (GAVI, 2025)

    Measurable Impact Cannot Be Designed in Geneva and Delivered at Scale.

    Measurable impact in complex human systems — in health, in education, in food security, in climate adaptation — is not a product you can design in Geneva and deliver at scale. It is something that has to be co-created, continuously, with governments, with institutions, with communities, and most critically, with the people who are supposed to benefit from it.

    You cannot make a lean system work without genuine collaboration at every level of it. Leaner is not simpler. Leaner means less redundancy, less slack, less room for error — which means the quality of the decisions that drive the system has to be dramatically higher. And better decisions in complex environments don’t come from smaller leadership teams with faster approval cycles. They come from mobilizing the intelligence of everyone who holds a piece of the reality you are trying to change.

    • A landmark PLOS One systematic review of community participation in health systems found consistent positive outcomes — in health, empowerment, and organizational effectiveness — when communities were genuinely involved in design and implementation, not just consulted. The evidence is clear: participation is not a values choice. It is a performance variable. (PLOS One, 2019; WHO, 2024)

    That Means Everyone in the Room. Actually.

    That means governments as genuine co-architects, not compliance partners. That means civil society as strategic actors, not delivery mechanisms. That means communities not just consulted at the margins but present in the rooms where priorities are set, where resources are allocated, where course corrections are made.

    This is a culture shift, not a structural adjustment. And it is the one shift the sector is most capable of making — because the values that justify it have been written into every mission statement, every theory of change, every funding proposal the sector has ever produced. The sector has always known this. It now has the necessity, and the permission, to actually do it.

    • GAVI 6.0 explicitly commits to being ‘community-owned and inclusive,’ directly engaging communities and civil society organisations in planning, implementation, and oversight of immunisation — and consolidating all cash-based funding into a single country-led envelope tied to immunisation delivery outcomes. The new model names co-creation as an operating principle, not an aspiration. (GAVI 6.0 Strategy, 2024)

    The Culture That Built the Old System Cannot Build the New One.

    The hierarchical, expert-driven culture of the old model was not malicious. It was a rational response to the constraints of its time. But those constraints have changed. The question is whether the sector’s culture can change with them.

    You cannot build participatory systems with institutions that cannot practice participation internally. You cannot credibly claim to center communities in your programs while running leadership processes that exclude 95% of your own staff. The organizations that close that gap — between what they say and how they actually work — will be the ones that earn the trust the new model requires.

    • When WHO announced its restructuring plan — cutting headquarters departments from 76 to 34, reducing staff by up to 22% — its own Staff Association stated: ‘This is not just about numbers. It is about trust.’ Decisions about workforce reductions were being made without access to the data by the people most affected. The sector’s internal culture gap is not a soft problem. It is a systemic risk. (Health Policy Watch, 2025)

    The Organizations That Thrive Will Not Be the Biggest.

    The hierarchical, expert-driven culture of the old model was not malicious. It was a rational response to the constraints of its time. The organizations that thrive in this transition will not be the biggest, or the best-funded, or the ones with the longest history. They will be the ones that genuinely change how they think together — that build the internal collaborative infrastructure to match the external collaborative demands being placed on them.

    And more than that: the organizations that shape what comes next will not be organizations at all in the traditional sense. They will be coalitions. Temporary structures built around specific outcomes, drawing on the knowledge of governments and communities and the private sector and civil society simultaneously, designed to dissolve when the work is done and reconstitute around the next challenge.e constraints have changed. The question is whether the sector’s culture can change with them.

    • The five largest bilateral donors — the US, Germany, UK, Japan, and France — accounted for 96% of the total ODA decline in 2025. No single institution, however large, can absorb that shock alone. The math of impact now requires coalition. (OECD, April 2026)

    The Collaboration Imperative.

    The collaboration imperative is not a call for more coordination meetings or better stakeholder engagement frameworks. It is a call for a different theory of change altogether — one that starts from the premise that the intelligence needed to solve the world’s most complex problems is already distributed across the people most affected by them, and that the job of any serious global institution is to build the conditions in which that intelligence can be heard, connected, and converted into action.

    The world doesn’t need more experts delivering solutions.

    It needs better infrastructure for thinking together.

    • The SDG financing gap stands at USD 4 trillion per year. No government, foundation, or multilateral institution can close it alone. Only a genuinely collaborative architecture — one that connects public finance, private capital, community knowledge, and government commitment around shared, measurable outcomes — has any chance of getting close. (UNCTAD, 2024; UNDP, 2025)

    This Is the Moment.

    This is the moment the aid sector becomes what it always promised to be.

    And I say that as someone who has sat across the table from the people inside these organizations — the program officers who stayed late to make something work, the field coordinators who improvised when the plan fell apart, the country directors who fought for their teams when headquarters stopped listening. I have watched extraordinary people operate inside imperfect systems and produce results that should not have been possible.

    Those people deserve a system worthy of them.

    The window is open. I don’t know how long it stays open. But I know some of what it takes to think together under pressure — to create the conditions where the right conversations actually happen, where the intelligence in the room gets used, where people leave with something they built together rather than something handed down to them.

    If any of that is useful to you right now, I am here.

    Antoine Viornery — Founder, The Collaboration Principle

  • OF PATCHES AND NODES: RETHINKING HOW ORGANIZATIONS MOVE AT THE SPEED OF CHANGE


    We are living through a period that defies the logic of the organizations we inherited.

    The hierarchical model that shaped the twentieth century was built for a world that changed slowly enough to be managed from the top down. It gave us stability, predictability, and scale. But it was also built on an assumption that has quietly collapsed: that the people at the top could hold enough of the picture to make the right calls for everyone below them.

    That assumption no longer holds. Not in a world where AI is reshaping entire industries in the span of months, where geopolitical disruption outpaces strategic planning cycles, where the complexity organizations face has long since exceeded the cognitive bandwidth of any single leadership team.

    The typical response? Add a new workstream. Convene a task force. Appoint a Chief Something Officer. In other words: more boxes, more process, more structure layered onto an architecture that was already struggling to breathe.

    We call this the patch reflex. And it is making things worse.

    What organizations were actually built for

    In “The Nature of the Firm”, an article published in 1937, Ronald Coase argues that firms emerge because they are better equipped to deal with the transation costs inherent in production and exchange than individuals are. He was awarded a Memorial Nobel prize in Economics for this paper in 1991.

    In other words, organizations exist to simplify the coordination between people who need to work together. That’s it. Nothing mystical. A car does not require a company to exist, but building one affordably requires synchronizing designers, engineers, suppliers, distributors, and customers in a way that no informal arrangement could sustain at scale.

    The org chart is the attempt to draw that coordination on paper. And on paper, it often looks rational. But here is what the chart never captures: the real forces that hold any organization together are not reporting lines. They are passion and indifference, loyalty and quiet betrayal, the energy of people who care deeply and the drag of those who checked out two years ago. They are the informal conversations, the cross-functional relationships that nobody sanctioned, the individuals who bridge silos because they happen to trust each other.

    The connections that generate the most value are almost never the ones that appear in an org chart. They are the ones that cross it.

    The Patches and Nodes model

    The framework we work with at TCP starts from a different premise: that organizations are not machines to be engineered but living systems to be cultivated.

    In that system, every person is a Node. An individual with a unique set of experiences, capabilities, and relationships. Nodes are not cogs. They are the actual sources of intelligence in the system, and they are naturally oriented toward connection.

    A Patch is a community of intent: a group of people gathered around a shared purpose, a common task, or a lived experience. A business unit is a Patch. So is a project team. So is the informal network of people across your organization who care about the same thing and have found each other anyway.

    A Patchwork is the whole: the sum of all Patches and, critically, the density and quality of the connections between them. The health of a Patchwork is not measured by how well-defined its boxes are. It is measured by how well information flows, how quickly learning travels, and how effectively the system can reconfigure itself around what actually matters right now.

    No one drives a Patchwork. No one owns it. It is governed by the same principles that govern any living, adaptive system: variety matching complexity, signal amplification through connection, distributed intelligence outperforming centralized control.

    Why this matters now more than ever

    The Law of Requisite Variety, formulated by the cybernetician W. Ross Ashby, states that a system can only regulate itself against complexity if it contains at least as much variety as that complexity. In plain terms: if your environment is more complex than your organization, your organization will lose.

    Most organizations today are losing that race. Not because their people are not capable, but because the architecture suppresses the very variety it needs. Hierarchy homogenizes. It filters signal into noise. It rewards conformity at precisely the moment when the world is punishing it.

    The Patches and Nodes model is not a structural fix. It is not a new org chart. It is a shift in how people relate to each other and to the work, governed by three principles that sound deceptively simple:

    First, ship what you learn. Every insight, every discovery, every lesson from failure: share it, deliberately and quickly, with the people who could use it. Not in a quarterly knowledge-management review. Now.

    Second, use what you get. Whatever reaches you through the network, integrate it. Let it change how you work. The point of information flowing is that it should move something.

    Third, optimize your Patch. Know who is in your immediate community of intent. Know what they are capable of. Distribute responsibility in a way that stretches people and wastes no one.

    These three rules, applied consistently, produce something that no process redesign or leadership offsite can manufacture: an organization that learns faster than its environment changes.

    What this looks like in practice

    Our work at TCP is to help organizations build those conditions deliberately.

    This happens primarily through large-group facilitation: immersive sessions of twenty to two hundred people, designed to surface the real connections and the real obstacles in a system, to activate the distributed intelligence that exists across an organization but has never been given a room to work in together.

    We bring together people who do not normally share a table. We design interactions that make the informal visible. We create the conditions for cross-Patch connections to form, strengthen, and carry learning back into the work.

    We do this for multilateral organizations navigating structural transformation, for global corporations facing discontinuous change, and for leadership teams that have understood, finally, that the answer to increasing complexity is not a smarter strategy document. It is a more connected, more adaptive, more genuinely intelligent organization.

    Matt and Gail Taylor who first played with and taught us about Patchwork Architectures and Designs wrote : ” Life must be lived, not managed.” .

    It’s not easy for leaders and managers to just let things be, but this is what a patchwork needs.

    What becomes possible

    The value of this work is not always easy to put in a slide. But organizations that have gone through it tend to describe the same things: decisions that used to take months start moving in days, because the people who need to align have actually met each other, understood each other’s constraints, and built enough trust to move without waiting for permission. Silos that had calcified over years begin to dissolve, not through mandate but through the simple experience of having solved something together that neither side could have solved alone.

    At a human level, people remember that their work can mean something. Engagement, that most elusive of organizational metrics, tends to follow when people feel that their contribution is visible and that the system around them is actually responsive to what they bring. The talent that hierarchies routinely suppress, the person in the middle of the org chart who holds the relationships and the institutional knowledge and the goodwill that no one thought to make official, comes into the light.

    At a strategic level, the organization develops what might be the most valuable capability available in a volatile world: the ability to reconfigure quickly around what matters now. Not because a leader told it to. Because the Patchwork already knew what needed to happen, and had the connections to make it happen.

    The investment is a few days, sometimes a few weeks. The return, when the conditions are right and the intent is genuine, is an organization that is measurably more capable of facing what comes next. Whatever that turns out to be.


    Antoine Viornery is the founder of The Collaboration Principle. We work with multilateral organizations, global corporations, and executive education programs to build the conditions for large-scale collaboration.

  • LEADING THROUGH THE INTELLIGENCE AGE: THE 4 CONVERSATIONS THAT MATTER MORE THAN EVER

    We are living through a period that defies the logic of the organizations we inherited.

    W. Ross Ashby’s Law of Requisite Variety is one of the foundational principles of cybernetics — the science of how complex systems regulate themselves and maintain autonomy in the face of disruption. Its formulation is deceptively simple: “Only variety can absorb variety.” A system overwhelmed by complexity cannot regulate itself with a narrow range of responses. To remain in control of its own future — to act with genuine autonomy rather than simply react — it must match the disruption with an equivalent breadth of perspective. The law was conceived to describe machines and biological systems. But in twenty-five years of working with organisations under pressure, I have never found a more accurate description of what separates those that navigate complexity well from those that don’t.

    The organisations that hold their autonomy in turbulent conditions are not those with the best individual minds. They are those that have learned to think together — to generate, collectively, the variety that no single perspective can produce alone.

    That capacity — genuine, structured, productive collaboration — is about to become the most strategically valuable thing an organisation can build. Not because it is a nice aspiration. Because without it, the most powerful technology in human history will deliver a fraction of what it is capable of.

    Artificial intelligence is not arriving as a tool to be handed to individuals. It is arriving as a force that will reshape how organisations function — how they decide, how they learn, how they create, how they compete. Its potential is genuinely extraordinary. We are at the very beginning of a new human era, one in which the ceiling on what organisations can achieve has been raised in ways that would have been difficult to imagine even five years ago. The organisations that learn to harness that potential will not simply be more efficient. They will be capable of things that were previously out of reach.

    But here is what the early evidence is already showing: the value that intelligent systems create is not evenly distributed. It concentrates in organisations where people collaborate well. Where knowledge moves fluidly across functions. Where diverse perspectives are genuinely integrated rather than siloed. Where the humans working alongside these systems share a common understanding of what they are trying to achieve and why. In those organisations, AI amplifies human intelligence. In organisations where collaboration is weak, it amplifies noise.

    This means the dialogue cannot wait. Structured, informed exchange — bringing together curated participants, carefully prepared, designed for genuine collective sense-making — is what transforms intelligent technology from a productivity tool into a force multiplier for human judgment. It is needed now, at every level.

    At the level of ethics

    Who decides what the organisation uses these systems for, and on what basis? What does it mean to make a consequential decision when part of the reasoning was produced by a system no one fully understands? Organisations that work through these questions together — rather than letting them settle by default — build a shared ethical framework that guides decisions with speed and coherence. They create institutional trust that attracts people who care about how things are done. They develop a collective moral clarity that becomes, in itself, a competitive advantage.

    At the level of strategy

    What is the organisation actually for, in a world where many of the tasks that justified its current structure can now be automated? This question tends to be avoided because it is uncomfortable. But the organisations that face it directly, and think it through together, arrive somewhere energising: a sharper sense of distinctive purpose, a clearer view of where human judgment creates irreplaceable value, and a strategic confidence that does not depend on defending yesterday’s positions. Collaboration here is not a process. It is the mechanism through which strategy becomes genuinely shared — and therefore genuinely executable.

    At the level of culture

    What happens to trust, to identity, to the implicit contracts between people and institutions, when the nature of work changes this fast? Organisations that engage with this openly find that the act of engaging is itself part of the answer. People who feel genuinely heard in moments of uncertainty become more committed, more creative, and more willing to take the risks that innovation requires. The collaborative culture built in this moment becomes the substrate on which transformation can actually take root.

    At the level of practice

    Which judgments remain irreducibly human? Where does the human need to stay in the loop — not for compliance reasons, but because the quality of the outcome depends on it? These questions are currently being answered in fragments, individually, without coordination. Brought into structured cross-functional dialogue, they produce shared operating principles, faster collective learning, and the practical wisdom that compounds into genuine organisational capability. This is how humans and intelligent systems learn to work together well — not through individual trial and error, but through deliberate collaborative sense-making.

    Hannah Arendt wrote that human plurality has a twofold character: equality and distinction. We can understand each other because we share a common humanity. We need each other because our judgments are irreducibly our own. The extraordinary promise of this new era is precisely that: technology of almost unlimited analytical power, in the hands of organisations capable of the kind of collective human thinking that no machine can replicate. The two are not in tension. They are, at their best, designed for each other. But only if the human side of that equation is taken as seriously as the technological one.

    “Nobody knows what to do against the purely new.” Ashby was right. But a leadership team that thinks together — that has built the collective variety to meet complexity with complexity — does not need to know in advance. It needs to be capable: capable of sensing, of honest disagreement, of integration across difference, and of commitment that survives contact with reality. That capability is not given. It is built deliberately, through structured dialogue, over time.

    We have seen that in practice — in industrial programmes that finally turned a corner when the right people sat together honestly for the first time, in international coalitions that discovered in two days of structured deliberation what years of coordination had missed, in leadership teams that arrived carrying certainties and left carrying something more useful: better questions, shared ownership, and the beginnings of the collaborative intelligence their organisations needed.

    Intelligent systems are ready. The question is whether the humans working with them are ready to collaborate at the level the technology demands — and deserves. The organisations that answer yes, and start building that capacity now, will not simply be ahead. They will be the ones defining what this era turns out to mean.


    If you are reading this and recognizing something in it — a sense that your organization has the intelligence it needs but not yet the conversations — we would be glad to have a chat with you.