(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:
- 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.
- 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.
- Creating safety for dissent and iteration. Humans refine judgement through being challenged. Organisations that treat disagreement as a threat lose their smartest people.
- 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?