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.

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.

Creating a knowledge sharing culture

Are you wondering how to create a culture more conducive to knowledge sharing, collaboration, innovation, trust, and respect?

Radical Knowledge Management will do that for you.

Implementing Radical KM addresses a whole host of challenges being face in organisations and really is the silver bullet it appears to be.

ProblemSymptomArts-based Solutions
Uncertainty and exaggerated sense of urgency▸ People are stressed, worried, overwhelmed▸ Support mental health and well-being
▸ Creating space for reflection
No sense of purpose/meaning▸ Disengagement
▸ Connections have been broken
▸ No sense of belonging
▸ No empathy and compassion
▸ Build teams, connections, engagement
▸ Build a sense of belonging
▸ Build/develop empathy and compassion for self and others
Lack of Agency▸ Don’t know what they want, what they can do, what is possible
▸ People starting to think like AI/ computers
▸ Build sense of purpose and meaning, big picture
▸ Create/develop agency
Lack of critical thinking▸ Don’t know who/what to believe
▸ Lack of curiosity and creative problem solving
▸ Critical thinking to discern what is real and what is fake
▸ Support trial and error, and iteration

You can check out my recent ReWorked column for more information or watch this webinar I did with KMI.