Category: Digital Transformation

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The Automation Paradox: Why AI Makes Human Capacity More Valuable (Not Less)

(This post was originally shared on my LinkedIn Profile.)

We’re told AI will handle routine work, freeing humans for creativity and critical thinking. Sounds great. So why do leaders I speak with say their organisations feel less creative, not more? (Some have said they feel like AI is making them dumb.)

The problem isn’t AI. It’s that we’ve been systematically dismantling the conditions humans need to think, create, and judge well—and we did it before AI arrived.

The Post-mortem of Lost Capacity

Over the last 15+ years, organisations have optimised for efficiency: fewer meetings (no, we added more), faster decision-making (no, we added layers of approval), knowledge capture (no, we built systems nobody uses). The net result? Cognitive exhaustion. People are too busy processing information to actually think with it.

Add AI to this picture, and something shifts. Organisations realise they can automate tasks, but they can’t automate the parts of work that matter: understanding what problem actually needs solving, sensing when the data is misleading you, creating something genuinely new, making judgements that hold human values.

Suddenly, the capacity for critical thinking, intuition, and creativity isn’t a nice-to-have. It’s everything.

But here’s the trap: you can’t generate that capacity on demand. It requires conditions. Uninterrupted thinking time. Psychological safety to challenge ideas. Exposure to perspectives that collide with your own. Reflection. Sense and meaning-making.

Most organisations have actively eliminated these conditions in the name of efficiency.

Where Knowledge Management Has Failed (And Why It Can Recover)

Traditional KM treated knowledge like widgets: capture it, store it, retrieve it. The assumption was that better information architecture = better decisions. It didn’t account for the human dimension.

We lost the messy, generative stuff: the conversations where ideas collide, the storytelling that embeds wisdom, the reflection that turns experience into judgement. We built systems, not cultures.

So, when AI arrived, organisations had already stripped away the human conditions for thinking. The software wasn’t the problem. The culture was.

Radical KM: People-First, Not Technology-First

This is where the work shifts. If human capacity for creation, critical thinking, and judgement is the competitive advantage in an AI world, then KM isn’t about technology adoption. It’s about designing the conditions that allow humans to do what humans do best.

That means:

  1. Making space for thinking. Not as something to aspire to, something that is structurally embedded in the systems. Protected time. Simplified information. Reduction of noise.
  2. Reactivating curiosity through exposure. Cross-sector conversations. Diverse perspectives. Learning that isn’t bounded by function. This is where intuition develops—through pattern recognition across domains.
  3. Creating safety for dissent and iteration. Humans refine judgement through being challenged. Organisations that treat disagreement as a threat lose their smartest people.
  4. Embodying knowledge differently. Not everything knowable fits in a database. Wisdom about how to navigate ambiguity, where to apply intuition, when the data is lying to you—these are often learned through story, conversation, and shared sense-making.

Using arts-based approaches to do all of this.

I know that last line raises eyebrows. But arts-based interventions—guided visualisations, drawing, painting, storytelling, reflection practices—aren’t luxuries. They work because they interrupt the efficiency mindset, create psychological safety, and make knowledge shareable in ways that pure information architecture can’t reach.

A facilitated drawing exercise doesn’t seem like “knowledge work.” But it’s creating the conditions where people actually think together instead of just exchanging information.

The Choice

You can treat AI as a threat to human work, and race to automate more. Or you can treat it as a signal: the human work matters now more than ever. Which means investing in the conditions that allow humans to create, think critically, and exercise sound judgement.

That investment starts with culture, not code. With people, not platforms. With how you design the rhythm and psychology of work itself.

Organisations that get this right won’t lose to AI. They’ll use it to do what it does—handle volume, pattern-match, optimise routine—while reclaiming the uniquely human work their people are actually capable of.

The question for your leadership team: Are the conditions in your organisation supporting human capacity, or eroding it?

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Stop Talking About Knowledge Management. Start Showing Its Impact

(This post was originally shared on my LinkedIn Profile.)

Your organisation doesn’t have a knowledge management problem. It has a credibility problem.

You can launch the most elegant KM programme, design the cleverest framework, or build the sleekest knowledge platform. But if nobody sees how it changes the way work actually gets done, they won’t care. And why should they?

The organisations that genuinely embed knowledge management aren’t the ones with the loudest programmes. They’re the ones where people notice that knowledge moves, decisions get made faster, and reinvention stops happening.

Here’s how that actually occurs in practice.

1. Anchor to outcomes, not terminology

Stop leading with “knowledge management.” Lead with the outcome your organisation desperately needs: faster decision-making, reduced reinvention, onboarding that doesn’t take six months, compliance that’s actually defensible, or customer responsiveness that beats your competitors.

The frameworks work behind the outcomes. Make them invisible. When a senior leader notices that new hires are productive in weeks instead than months, or that a decision gets made because the right knowledge actually arrived, they start valuing what made it possible. They just don’t call it “KM.”

2. Build credibility through small, visible wins

Don’t launch a programme across the enterprise. Pick one team—preferably one where knowledge clearly gets lost or repeated—and work with them quietly.

Document what changes: time saved, mistakes avoided, ideas that moved between people. Then let their story travel.

Peer testimony is infinitely more powerful than a pitch from the programme office. People trust other practitioners. They’re suspicious of consultants.

3. Make trust the visible difference

Here’s what I’ve observed: organisations that fail at KM typically have a trust problem they don’t know they have. Information gets hoarded. Knowledge is buried behind permission structures. Sharing is punished or seen as losing advantage.

You can’t recognise knowledge management in that environment because the conditions for knowledge to actually travel don’t exist.

The organisations I’ve seen shift? They model something different. Generosity. Honesty. The willingness to say “I don’t know” without it costing you. Inquiry before judgment. These aren’t soft skills. They’re the infrastructure that makes knowledge move.

And if you’re driving KM, you have to model them first.

4. Celebrate the human story, not the system

People don’t care about your knowledge base. They care that they’re not reinventing the wheel at 3 p.m. on a Friday, or that someone remembered a client context that completely changed the conversation.

Recognition happens when you celebrate the person who shared as much as the knowledge that was shared. When you tell the story of how an idea travelled across teams and landed somewhere unexpected. When you highlight the person who documented their thinking so clearly that six months later, someone else could understand the reasoning behind a decision.

Make knowledge sharing visible as a human thing, not a compliance requirement.

5. Make it a leadership conversation

KM recognition happens when your executive team starts talking about knowledge as how we work here—not as a project sitting in a corner.

This means asking leadership questions:

  • Are decisions documented in a way that the logic is actually recoverable?
  • Do people have permission to ask questions without it being seen as weakness?
  • Is failure treated as learning, or is it buried?
  • Do you privilege speed over understanding, or vice versa?
  • Does your culture reward knowledge-hoarding or knowledge-sharing?

These aren’t KM questions. They’re leadership questions. But they’re the ones that determine whether knowledge management actually takes root.

6. Measure what actually matters

Forget knowledge base articles indexed. Forget training completion rates. Those metrics measure activity, not impact.

Track what actually shifts:

  • How much faster are people becoming capable?
  • Are the same questions still cycling through support?
  • Do ideas travel between teams that normally don’t connect?
  • Are decisions getting revisited repeatedly, or is the reasoning clear enough that people move forward with confidence?

Be rigorous about it. “We saved time” is vague. How much? For whom? What else did they do with the time they reclaimed?

Here’s the uncomfortable truth: Recognition follows credibility, and credibility comes from solving real problems quietly and consistently.

The organisations that genuinely “get” knowledge management didn’t get there through programme launches and change management initiatives. They got there because someone in a position of influence—often a team leader, sometimes a practitioner—demonstrated that knowledge actually matters to outcomes. And that became the way things worked.

Stop announcing KM. Start showing what happens when knowledge moves the way it should.

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Why Your Knowledge Management Strategy Needs the Arts

(This post was originally shared on my LinkedIn Profile.)

Most knowledge management strategies focus on systems, processes, and technology. But what if the missing piece is a scribble drawing?

Knowledge Work Has a Creativity Problem

We have built our organisations around efficiency metrics and linear processes — get from A to B to C in the most direct line possible. But knowledge work does not actually work that way. It requires curiosity, reflection, and iteration. It demands that people make unexpected connections, ask uncomfortable questions, and see the bigger picture.

Those capacities are not switched on by yet another technology upgrade.

This is the premise of Radical Knowledge Management — a framework developed to bring creativity and arts-based interventions (ABIs) deliberately into KM practice. The definition of KM at the heart of this approach is broader than the traditional one: rather than merely connecting people to documented knowledge, it focuses on enabling people to find and create the knowledge they need to do their jobs — including through continuous learning and new ways of thinking.

What Are Arts-Based Interventions?

Arts-based interventions are activities that use an artistic medium or discipline to improve a process or situation. In organisational settings, the most common artistic modalities include drawing, painting, photography, theatre, music, poetry, improvisation, and storytelling.

These are not team-building novelties bolted on to the end of a strategy day. Used deliberately, they are instruments for culture change, innovation, leadership development, problem-solving, and organisational transformation.

There are at least twelve use cases for ABIs in organisations:

  1. Culture change
  2. Innovation
  3. Wellness
  4. Getting unstuck
  5. Sustainable leadership
  6. Team building
  7. Collaboration
  8. Problem-solving
  9. Amplifying learning
  10. Transformation
  11. Creating community
  12. Employee engagement

Because of the interconnected nature of these activities, focusing on ABIs for one use case tends to positively affect the others as well.

Why ABIs Belong Inside Your KM Strategy

There is a tendency to think of creativity as a bolt-on — something for design or marketing, or perhaps for the occasional off-site. The argument for placing ABIs firmly within KM rests on something more fundamental.

Knowledge is created by people. It is intangible, complex, and deeply social. In our increasingly volatile, uncertain, complex, and ambiguous (VUCA) world, the knowledge we most urgently need cannot be captured in a database. It lives in the capacity of people to think differently, collaborate across silos, and remain curious even under pressure.

ABIs directly support those capacities. They help people tap into skills and behaviours that formal education and career pressures have pushed into dormancy. They encourage people to get out of their comfort zones, see the bigger picture, and ask different questions. In doing so, they create new knowledge — and they shift organisational culture towards one that supports knowledge sharing rather than knowledge hoarding.

As Albert Einstein observed, imagination is more important than knowledge; knowledge is limited, whereas imagination embraces the entire world. Arts-based interventions are one of the most reliable ways to fuel imagination in the workplace.

The MAGIC-SH Framework

For organisations ready to take this seriously, the Radical KM framework provides a practical structure organised around the acronym MAGIC-SH:

S & H — Sustainable and Human. This is the foundation. ABIs make organisations more sustainable because they help people see the interconnectedness of things and develop sustainable leadership behaviours. They also reinforce the humanity of work — critical at a time when technology threatens to crowd out the very qualities that make people valuable.

The Nine Cs. The middle layer of the framework encompasses the concepts that ABIs develop and evolve:

  1. Creativity — producing novel ideas and approaches
  2. Collaboration — building the trust that makes real knowledge sharing possible
  3. Communication — developing empathy and purposeful expression (improv theatre is particularly powerful here)
  4. Content — shaping what knowledge is captured and how
  5. Critical thinking — challenging the “that’s how we’ve always done it” assumption
  6. Conversation — opening new avenues for dialogue and insight
  7. Culture — shifting the organisation towards one that values learning and sharing
  8. Confidence — building the self-belief to ask for help, try new approaches, and share imperfect knowledge
  9. Change management — supporting the cultural shift that ABIs require

A, G, I — ABIs, Ideas, Innovation and the Guerrilla approach. These represent both the outputs sought (fresh ideas and innovation) and the practical approach recommended: starting small, positioning ABIs as experiments, and growing support iteratively.

M — Metrics. Measurement comes last — not because it is unimportant, but because defining metrics too early can constrain the very creative exploration that makes ABIs valuable.

How to Start: Two Practical Pathways

There is no need to overhaul your entire KM programme. Radical KM explicitly recommends starting small and iterating.

The Icebreaker stream begins at the individual or team level with short, low-stakes activities: a guided visualisation at the start of a meeting, a scribble drawing exercise during a workshop, an improvisational warm-up before a strategy session. These take as little as five minutes, but they shift the energy and engagement in the room, build psychological safety, and begin to normalise the idea that creativity belongs at work.

The Studio stream takes a larger, more structured approach — dedicated sessions, longer interventions, and formal integration into KM processes such as knowledge capture workshops, after-action reviews, or communities of practice.

In both cases, the implementation approach is the same: treat it as an experiment, start with early adopters, debrief afterwards, and iterate based on what you learn. Change management is essential — people have often been educated to believe that the arts are wasteful, and that belief takes time and consistent experience to shift.

The Hardest Part

The biggest obstacle to incorporating ABIs into a KM strategy is not logistics. It is the stories we tell ourselves about why we cannot — or should not — do it. What will my colleagues think? Are the benefits really there? Is this really my job?

Those doubts are understandable. Most of us had our creativity criticised or ignored somewhere around adolescence, and we learned to put it away as unprofessional.

But look around your team. Someone is doodling during calls. Someone uses role-play to prepare for difficult conversations. Someone plays an icebreaker game at the start of team stand-ups. The arts and creativity are already finding their way into your workplace — unconsciously. Radical KM simply asks you to be more deliberate about it.

The first time you try a scribble drawing exercise in a knowledge management workshop, you may be pleasantly surprised. The energy and engagement in the room shifts. Responses become more thoughtful and detailed. People make connections they would not otherwise have made. The knowledge that flows is richer.

A Final Thought

In a world shaped by AI, automation, and relentless change, the knowledge and capabilities that most need managing are the human ones: curiosity, resilience, empathy, imagination, and the willingness to keep learning. Those are not developed by better taxonomy.

They are developed through practice — and arts-based interventions are one of the most evidence-supported ways to practise them.

Your KM strategy does not need an overhaul. It needs a scribble drawing, and the courage to see what happens next.

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AI Won’t Replace Knowledge Management. It Will Finally Force Us to Take It Seriously

(This post was originally shared in my LinkedIn Profile.)

For decades, knowledge management has been the organisational discipline that everyone agreed was important and almost no one invested in properly.

We built SharePoint graveyards. We created knowledge bases nobody searched. We ran “lessons learned” sessions whose lessons were never applied. And when things went wrong — when the expert retired, when the project team disbanded, when the same mistake happened for the third time — we shrugged and called it institutional memory loss, as if it were a natural disaster rather than a preventable one.

Then came AI.

And suddenly, knowledge management isn’t a nice-to-have. It’s the foundation everything else depends on.

AI is only as good as the knowledge it can access

Here’s what the AI vendors won’t tell you in their sales decks: a large language model deployed inside your organisation will reflect the quality of your organisational knowledge. Feed it outdated policies, inconsistent documentation, and tribal knowledge that lives only in people’s heads — and you’ll get confident, fluent, wrong answers at scale.

The organisations rushing to implement AI copilots and knowledge assistants are about to discover something KM practitioners have known for years: garbage in, garbage out is not a technology problem. It’s a knowledge governance problem.

AI doesn’t fix broken knowledge ecosystems. It amplifies them — for better or worse.

The sudden urgency is real — and welcome

I’ve sat in enough boardrooms to know that the argument “we need to capture institutional knowledge before people leave” rarely moved budgets. Neither did “we’re duplicating effort because teams can’t find what exists.”

But “our AI tool is producing unreliable outputs because our knowledge base is a mess”? That one lands differently.

AI is creating the business case for KM that practitioners have struggled to articulate for years. Not because AI is a KM solution — it isn’t — but because AI makes the consequences of poor knowledge management immediately visible and commercially painful.

That’s not a crisis. That’s an opportunity.

What AI actually makes possible

Used thoughtfully, AI tools offer genuine advances for knowledge work:

  • Surfacing what exists — AI-powered search can finally make organisational knowledge findable, cutting through the folder structures and file naming conventions that defeated traditional search.
  • Capturing tacit knowledge — Conversational AI can assist in eliciting and structuring knowledge from subject matter experts in ways that don’t require them to become writers.
  • Reducing the burden of contribution — One of the biggest barriers to knowledge sharing is the effort it takes. AI can lower that friction significantly.
  • Connecting dots across silos — AI can identify relationships between knowledge assets that no human would have the bandwidth to spot.

None of this happens automatically. All of it requires human judgement, governance, and strategy to work.

The human element isn’t optional

Here’s where I’d push back on the more breathless AI narratives: knowledge is not just information. It includes context, relationship, experience, and meaning — the things that make information useful rather than merely available.

AI can retrieve. It cannot always discern. It can summarise. It cannot always judge what matters. It can generate. It cannot replace the wisdom that comes from having lived through something.

The organisations that will succeed with AI-augmented knowledge management are those that treat the human and the machine as partners — where AI handles the retrieval, synthesis, and surface-level generation, and people contribute the judgment, the curation, and the culture that makes knowledge genuinely shared.

The moment KM has been waiting for

I started my career arguing that knowledge management deserved more strategic investment. I’m still making that argument — with AI more executives are “getting it”.

AI has done what years of best practice frameworks and maturity models couldn’t: it has made knowledge management urgent.

That urgency is an opening. The question is whether organisations will use it to build something sustainable — genuine knowledge cultures, sound governance, human-centred practice — or whether they’ll bolt AI onto the same neglected foundations and wonder why the results disappoint.

The technology is ready. The case is made. Now comes the harder work.

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Radical KM Institute Announcement

There are now three courses/programs available on the RadicalKM.Institute website.

The White Belt course has been available since earlier this year (February 2024), and is an introduction to Radical KM, it is free. You can find out about it here.

The Green Belt course has just been released (November 2024). It takes Radical KM a step further, with more complex ideas about implementing/using Radical KM. The course includes videos and other supplemental information. You can find out about it here.

Finally, an comprehensive program including 1:1 coaching. This program is designed to complete the Radical KM picture and help knowledge managers implement Radical KM in their organisation by providing in depth Radical KM knowledge and 1:1 coaching. You can check it out here.

As always, if you have any questions, feel free to get in touch, I’m always happy to talk. You can book a time with me here.

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Radical KM, Published Article

One of my articles on Radical KM has been published by the GfWM (Gesellschaft für Wissensmanagement) or Society for Knowledge Management here in Germany as part of a collection of articles celebrating the 20th Knowledge Camp. You can download the PDF or read it online, here.

I have another version that will be published in 2021, it’s a bit longer, and a third version that I keep adding to, and which is heading towards being a book, although it has a long ways to go.

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Why RADICAL knowledge management?

Why “radical” and not something else? Which definition of radical do I mean?

Radical has three definitions that are all relevant for Radical KM (taken from Oxford Learners Dictionary):
1. relating to the most basic and important parts of something; complete and detailed
2. new, different and likely to have a great effect
3. in favour of extreme and complete political or social change

Why do all three of them apply? Because knowledge management must include all aspects of knowledge (creation, curation, learning, un-learning, re-learning, and sharing), and two of the things that are most important for this are curiosity and critical thinking. Both of these have been lost through the focus on efficiency and effectiveness, and trying to be logical/rational/analytical while ignoring the creative and emotional, but if we are truly going to manage knowledge then we need to re-introduce the creative and emotional: humans are not machines.

Bringing creativity into knowledge management and helping our organisations embrace both the creative and analytical is critical to their success and the individuals who comprise them. That is radical and will have a great effect and will bring about change in ourselves and our organisations.

In addition to the 3 meanings of radical, radical has an interesting origin. From Merriam Webster, we learn that radical originally meant “root“, so by returning creativity to our knowledge processes we can consider that we are returning to our roots. Roots, which were playful and creative: that’s how we learned when we were children. It wasn’t until later, when we went to school, that this learning by doing was replaced by learning by reading. Going back to our roots means re-learning that creativity that has been ignored. Knowledge management has a role to play in that, hence Radical Knowledge Management.

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Creativity, Scrum, Agile, and Design Thinking

In the spring I completed Scrum Master certification (PSM I), and right now I am taking a design thinking course. I had delayed both of these courses because they describe the way I work anyway, and I couldn’t see the point of wasting time and money on them. So, why am I doing them now? Because they keep coming up in discussions I’m having, so I thought I would see what all the fuss is about.


They’re both frameworks/methodologies, and useful, as far as they go, but what occurred to me as I worked on the Design Thinking course, was that they are both trying to teach people to be more innovative and creative, to be more curious, however, they have taken an analytical approach to innovation and creativity, to monetize it, I suppose. These frameworks have taken the space for reflection out, the space for emotion out, just like our education systems, they have taken the creative out of being creative and made it analytical. 


If we really want to be creative, we need to engage the creative parts of our brains, not the parts that do analysis and process work. We need to engage the whole person, not just half, and that’s what Radical KM does. It recognises that the creative has been disengaged and forgotten, and it needs to be re-learned and re-engaged if we are truly going to be creative and change the ways our organisations function.


If we want our organisations to reap the benefits that agile and design thinking promote, we need to make space for true creativity, not just creativity that’s been analysed to death.

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What does it mean to integrate creativity with knowledge management?

What do I mean when I say, “integrate creativity with knowledge management”?

Well, the first thing I want to say is that in some cases I may use business/organisation instead of knowledge management, they are not necessarily interchangeable. I will tend to use knowledge management if it is specific to a knowledge management activity and business/organisation if it’s more general, in practice, they may look very similar and difficult to distinguish. That is due, in part, to the fact that I think knowledge management should be integrated with the business/organisational processes and activities and not something separate.

Okay, now on with the integration of creativity with KM/business/organisation.

Easy to do
In the simplest terms, this is doing things like quick creative ice breakers at the beginning of meetings. This includes things like a short meditation, or short drawing or improvisational games. There are all kinds of things that you can do, there are books available that are filled with possibilities, I have also created an online course which has 7-8 different activities in it that you can do online or in person.

Moderately integrated
At the next level there are longer activities that you can use for different purposes and longer meetings. The ones you choose really depend on what you are trying to achieve, and they can take from 30 minutes to 2 hours or more. My favourite book for these activities is Linda Naiman’s, “Orchestrating Collaboration at Work: Using music, improv, storytelling and other arts to improve teamwork“, which is available from her website or Amazon.

Advanced integration
Then we move to more advanced activities like setting up a studio in your office and staffing it with someone. The person acts as a catalyst/artist in residence and can facilitate workshops or coach individuals on a one-to-one basis.

You may also want to consider training, like Applying Creativity to Business

If you are curious about any of these options feel free to comment on this post or contact me directly at stephanie @ realisation-of-potential.com (take out the spaces).

See also: Radical KM and blog posts.