No, I Don’t Think AI Is the Enemy. I Just Know It Isn’t the Answer

(This post originally appeared on my LinkedIn Profile.)

A colleague said something to me recently that gave me pause.

“You’re a bit of a Luddite when it comes to AI, aren’t you?”

It was said with a smile,  the kind of gentle ribbing that comes from genuine curiosity rather than criticism. But it stuck with me, because I realised I haven’t been clear enough about where I actually stand.

So let me be direct: I think AI is remarkable. I use it. I find it genuinely useful. I’m curious (and also deeply concerned) about where it’s headed. And in the context of Knowledge Management specifically, I believe it has real and growing value.

What I don’t believe, and what I’ll continue to push back on, is the idea that AI solves Knowledge Management. Because that framing, however appealing, leads organisations down a very expensive and frustrating path.

The Seductive Logic of the Tech Solution

There’s a pattern I’ve watched repeat itself across organisations for years, and AI is simply the latest chapter in a long story.

It went like this: first, we were going to solve knowledge management with intranets. Then wikis. Then SharePoint. Then enterprise social networks. Then big data platforms. Each time, the pitch was essentially the same: “This technology will finally make your organisational knowledge accessible, searchable, and usable.”

And each time, organisations discovered the same uncomfortable truth: the technology worked. It was the knowledge management that didn’t.

Files sat untagged. Content became stale within months. People reverted to emailing each other, because the system was technically available but practically ignored. Adoption curves flattened. The investment quietly became shelfware.

AI doesn’t change this dynamic. It accelerates it, in both directions. Deploy AI on top of well-structured, well-governed, actively maintained knowledge assets, and it can be genuinely transformative. Deploy it on top of the organisational equivalent of a cluttered attic, and it will confidently surface the wrong answer, twice as fast. (Wrong answers at scale, as I recently commented to another colleague.)

Knowledge Management Is a People Problem First

Here’s the thing that no vendor wants to put on a slide: most knowledge management failures are not technology failures.

They’re culture failures. Process failures. Leadership failures.

When an organisation loses critical expertise because a senior employee retires, that’s not a software gap, it’s a knowledge transfer gap that nobody prioritised until it was too late. When two teams duplicate months of research because they had no way of knowing what each other had already done, that’s a collaboration and communication failure. When a new hire spends their first three months reinventing wheels, that’s an onboarding and documentation failure.

No AI tool, however sophisticated, fixes those problems at the root. It might paper over some of the symptoms and sometimes that’s genuinely useful, but it doesn’t address the underlying conditions that created the problem in the first place.

The Five Pillars That Actually Matter

Effective Knowledge Management rests on five interconnected foundations:

People: Knowledge lives in people’s heads first. Building a knowledge-sharing culture, incentivising contribution, and reducing the friction between “someone knows this” and “the organisation benefits from this” is fundamentally a human challenge. It requires trust, psychological safety, and genuine leadership commitment.

Process: How does knowledge get created, validated, stored, retrieved, and retired? Without intentional, well-designed processes, even the best technology becomes a dumping ground. Process is the architecture that gives technology its shape.

Technology: Yes, absolutely. The right tools, well-chosen and properly implemented, are a genuine enabler. AI included. But technology is an enabler of a good strategy, not a substitute for one.

Governance: Who owns the knowledge? Who decides what’s accurate, current, and trusted? Who has authority to retire outdated content? Without governance, knowledge systems decay. This is the unglamorous work that makes everything else sustainable.

Strategy: What are you actually trying to achieve? Knowledge Management without a clear strategic anchor is just tidying. It needs to connect to organisational goals: accelerating innovation, reducing risk, improving customer outcomes, developing capability. Strategy is what makes the whole system purposeful.

These five pillars don’t operate in isolation, they’re deeply interdependent. A brilliant technology choice undermined by weak governance will still fail. Strong processes with no cultural buy-in will still fail. Strategy without execution infrastructure will still fail.

There Are No Easy Answers and That’s Important to Say Out Loud

One of the most valuable things a Knowledge Management professional can do is resist the pressure to promise simplicity.

Organisations want easy answers. They want to hear that the new platform, the new AI integration, the new taxonomy framework will sort things out. And sometimes, in the short term, a well-chosen tool can create enough momentum to feel like progress.

But sustainable Knowledge Management, the kind that actually compounds in value over time, requires patience, iteration, and a willingness to do genuinely hard organisational work. It requires leaders who understand that knowledge is a strategic asset, not an IT problem. It requires investment in people and process, not just licences and implementations.

The organisations that get this right don’t treat Knowledge Management as a project with an end date. They treat it as an ongoing capability, like finance or HR, something that needs continuous attention, resourcing, and refinement.

So Where Does That Leave AI?

Exactly where good tools always belong as a powerful enabler within a thoughtful, well-structured Knowledge Management strategy.

Used well, AI can dramatically improve knowledge discovery. It can surface connections between documents that no human would have the bandwidth to find. It can reduce the cost of creating knowledge assets. It can personalise the knowledge experience for different roles and contexts. These are real benefits, and they matter.

But AI doesn’t replace the need for governance. It doesn’t create a culture of sharing where none exists. It doesn’t write your knowledge strategy for you, or decide which expertise is critical to capture, or ensure that the knowledge your organisation produces is accurate and trustworthy.

Those are human responsibilities. And until we’re honest about that, we’ll keep buying technology solutions to organisational problems and wondering why the needle doesn’t move.

I’m not anti-technology. I’m anti-magical-thinking.

The organisations that thrive in the long run are the ones willing to do both: invest in excellent tools and do the harder, slower, more human work of building the conditions in which those tools can actually deliver.

That’s not a pessimistic message. I think it’s actually a hopeful one. Because it means the answer is within reach, it just takes more than a software purchase to get there.

We Didn’t Lose Productivity. We Lost Each Other.

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

There’s a feeling many of us carry into work that’s hard to name. A sense that despite the tools, the platforms, the dashboards, and the metrics — something fundamental has gone missing. That we’re busier than ever, but less effective. That we collaborate more and connect less.

The research says we’re right.


The social capital haemorrhage

McKinsey surveyed over 5,500 workers on the state of their workplace networks. What they found was striking: more than three-quarters reported connecting with others less frequently, maintaining smaller networks, and spending less time building relationships than before.

But here’s the detail that matters. Of the connections people still maintain, 57% are for sharing work-related information. 48% for career advice. Only 29% involve any kind of genuine social engagement.

What passes for collaboration in most organisations has become almost entirely transactional. Information exchange has replaced relationship. Efficiency has displaced trust.

And trust, it turns out, is not optional. Research consistently finds that mutual trust, reciprocity, and genuine collegial connection are among the strongest predictors of innovation, knowledge-sharing, and organisational effectiveness.


The silos aren’t a bug. They’re a feature of how we work now.

The most compelling evidence here comes from a 2022 Nature Human Behaviour study of over 61,000 Microsoft employees. When the company shifted to firm-wide remote work, something happened to its collaboration networks: they became static and siloed, with fewer bridges between different parts of the organisation.

The share of collaboration time employees spent with cross-group connections dropped by 25%.

This matters because of what those cross-group connections do. Sociologist Mark Granovetter called them “weak ties” — the loose connections across different teams, functions, and disciplines. They’re not where your most frequent interactions happen. But they’re where new knowledge comes from. They’re the connections that carry different perspectives, unexpected information, and creative friction.

We optimised them out of existence.


High productivity is masking exhaustion

Here’s the dangerous part: standard metrics often won’t show you this is happening.

Microsoft’s Work Trend Index, covering 31,000 workers across 31 countries, flagged it explicitly: high productivity is masking an exhausted workforce, and shrinking networks are endangering innovation.

A separate study of over 10,000 technology professionals found that after the shift to remote work, hours worked went up, output declined slightly, and productivity fell by 8–19%. More meetings. More messages. More coordination activity. Less actual work done.

More activity. Less capability.


This is what efficiency culture does

This didn’t happen by accident. It’s the predictable outcome of decades of management doctrine that treats organisations primarily as efficiency machines — measuring outputs, eliminating waste, standardising process, and optimising everything that can be quantified.

The problem is that genuine collaboration, learning, trust, and tacit knowledge are hard to quantify. So they don’t show up on the efficiency scorecard. And what doesn’t show up on the scorecard doesn’t get invested in.

UK government research on organisational effectiveness puts it plainly: the literature points to the failures of managerialism and market mechanisms to address complex challenges — and argues that those very challenges require genuine collaboration and inter-organisational cooperation to solve.

We’ve built management systems that are structurally antagonistic to the capabilities we actually need.


What this means for knowledge management

I’ve been making this argument for a long time: knowledge is not a technology problem.

Knowledge lives in relationships. It moves through trust. It surfaces in the informal conversation after the meeting ends, the cross-team question that no one put on a ticket, the senior person who explains the context behind the decision.

None of that is produced by a better platform. All of it depends on social capital — the networks, norms, and trust between people that make knowledge genuinely flow.

And the evidence is clear: that social capital has been eroding, quietly, for years. Not because people stopped caring, but because the conditions for building it have been systematically deprioritised in the name of efficiency.

Knowledge doesn’t walk out the door because of inadequate tooling. It walks out because the human infrastructure that carries it was allowed to decay.


The good news is that this is reversible. But it requires treating human connection, relational trust, and genuine collaboration as strategic organisational assets — not as pleasant by-products of getting the processes right.

Because they’re not by-products. They’re the foundation.


References available on request. Key sources include Yang et al. (2022), Nature Human Behaviour; McKinsey Quarterly (2022); Microsoft Work Trend Index (2021); Gibbs, Mengel & Siemroth (2022), Journal of Political Economy Microeconomics.

The Magic in the White Space: why what we can’t measure what matters most

(This post originally appeared on my LinkedIn profile.)

We’ve optimised ourselves into a corner.

Somewhere along the way, we started measuring everything. Click-through rates. Response times. Conversion metrics. Engagement scores. Customer lifetime value. Net Promoter Scores. And in doing so, we forgot something fundamental: people aren’t data points.

I’ve been thinking a lot lately about how our obsession with technology and analytics has made us deeply, painfully transactional. Every interaction has become an opportunity to capture, quantify, and optimise. We’ve replaced conversations with touch-points. Relationships with customer journeys. Trust with sentiment analysis.

The cost? We’ve lost our ability to think holistically. And we’ve forgotten that the most important things that happen in organisations—and in life—happen in the spaces between the things we measure.

The Tyranny of the Measurable

There’s a management axiom that gets trotted out with alarming frequency: “What gets measured gets managed.” It’s usually attributed to Peter Drucker, though he probably never said it in quite that way. Regardless of its provenance, we’ve taken it as gospel and built entire industries around it.

But here’s the problem with making measurement the centre of everything: we start to believe that if something can’t be measured, it doesn’t matter. Or worse, it doesn’t exist.

Consider what happens when everything is reduced to discrete, measurable transactions. We stop seeing patterns. We stop understanding context. We stop recognising that the person on the other end of that support ticket is the same one who attended our webinar, recommended us to a colleague, and has been quietly championing our work for years. Their “customer journey” looks like a series of disconnected events in our CRM, but their actual relationship with us is something far richer—and far more valuable—than any dashboard can capture.

Strategic thinking requires us to hold complexity. To see connections that don’t fit neatly into a spreadsheet. To value things we cannot easily quantify—like loyalty, goodwill, institutional memory, and the trust that accumulates through countless small moments of being seen and valued.

What Lives in the White Space

In design, white space—the empty areas around and between elements—isn’t wasted space. It’s what makes the rest of the design work. It provides breathing room, creates emphasis, and allows the eye to rest. Without white space, everything blurs together into noise.

Organisations have white space too. It’s the corridor conversation that sparks an unexpected idea. The coffee break where two people from different departments discover they’re working on complementary problems. The offhand comment in a meeting that someone remembers six months later and applies in a completely different context. It’s the trust that accumulates not through formal processes but through countless small moments of showing up, following through, and treating people as whole human beings rather than inputs in a workflow.

None of this fits in a spreadsheet. None of it shows up in your quarterly metrics review. And yet—ask anyone where their best ideas came from, and they’ll almost never point to a scheduled brainstorming session or a formal innovation programme. They’ll tell you about a conversation. A chance encounter. A moment of connection that couldn’t have been predicted or planned.

This is where the magic happens. And we’re systematically eliminating it.

The Efficiency Trap

In our pursuit of efficiency, we’ve optimised away the very conditions that allow innovation, creativity, and genuine human connection to flourish. Every minute is accounted for. Every interaction has a purpose. Every meeting has an agenda and a hard stop.

We’ve mistaken activity for progress and transactions for relationships.

The irony is profound. We invest millions in innovation programmes while simultaneously creating cultures that leave no room for the unstructured thinking that innovation requires. We talk about the importance of relationships while treating every customer interaction as a data point to be captured and processed. We celebrate “human-centred design” while building systems that reduce humans to behavioural patterns and conversion funnels.

You can’t build a relationship in a transaction. You build it in the space between transactions. In the follow-up that wasn’t required. In remembering what matters to someone. In showing up consistently, not just when the metrics demand it.

A Different Way of Seeing

So how do we measure the magic that happens in the white space?

I think the uncomfortable answer is: we don’t. Not directly, anyway. The white space is where serendipity lives, and serendipity resists quantification. That might be precisely the point.

But that doesn’t mean we’re helpless. It means we need to shift our focus from measuring the magic itself to measuring—and deliberately cultivating—the conditions that allow magic to happen.

We can ask different questions. Do people have unstructured time to think and connect? Are there spaces—physical or virtual—where unexpected collisions can occur? Is there psychological safety to share half-formed ideas without them being immediately evaluated against KPIs? Do we reward relationship-building, or only task completion?

We can notice the outcomes, even if we can’t trace the path. Innovation doesn’t announce its origins. But we can ask: where did that breakthrough actually come from? When we bother to trace these things back, the answer is almost never “the innovation committee met and decided.” It’s “I had a conversation with someone in a completely different department” or “I remembered something a client mentioned offhand three months ago.”

We can listen for stories instead of statistics. Narrative is how humans have always captured what metrics cannot. The organisations that understand the value of white space are the ones that collect and share these stories deliberately—not as marketing material, but as genuine organisational knowledge about how value actually gets created.

The Human Imperative

This matters more now than ever. As artificial intelligence takes over more of our transactional work—answering routine queries, processing standard requests, analysing data at scale—what remains distinctly human is precisely the stuff that happens in the white space. The intuition. The empathy. The ability to hold ambiguity and see connections across domains. The relationships built on genuine understanding rather than algorithmic prediction.

If we continue to optimise humans out of the white space, we’ll have nothing left to offer that machines can’t do better. But if we recognise that the white space is where our uniquely human value lives, we can build organisations that amplify rather than replace what makes us irreplaceable.

Technology should serve relationships, not replace them. Data should inform human judgement, not substitute for it. Efficiency should create space for what matters, not consume every moment in pursuit of marginal gains.

An Invitation

Perhaps it’s time we measured what actually matters—even if that means accepting that some things can’t be measured at all.

What would it look like to run an organisation that valued the white space? That deliberately protected time for unstructured connection? That evaluated leaders not just on what they delivered but on the relationships they built and the conditions they created for others to thrive?

What would it look like to approach each interaction not as a transaction to be completed but as a relationship to be nurtured? To see the person behind the data point, the story behind the metric, the magic behind the measurement?

The magic is in the white space. It always has been.

Maybe it’s time we stopped trying to fill every inch of it with something we can count.

I am Stephanie Barnes and I am … magic


(I am like a Tardis—I look ordinary, but contain powers beyond your imagination)

I don’t fit in a box
I work in the white space between the boxes

I don’t conform
I am a leader and a follower
I am analytical and creative
I am process-driven and flexible
I do digital transformation and culture change
I am a program and project manager and a performer of tasks
I get things done and I leave them until it is time to do them
I balance people, process, and technology
I balance business and technology
I am a bridge builder and an island
I like data and I think it’s pointless
I like theories and practicality
I create strategies, I implement them, and I go with the flow
I like the simplicity of black and white, while loving the energy, chaos, and emotions of layers of colours
I am patient and impatient
I rush ahead and I wait and see
I accept the things people tell me as true, and I ask lots of questions
I love silence, jazz concerts, and the symphony
I love the stillness of nature and the buzz of city life
I like order while finding it boring
I like chaos while finding it overwhelming and requiring order
I am a twin and an individual

I am organised chaos

Why do I do these things?

Because I am an expert and a novice
Because I am experienced and skilled, collaborative and curious
Because I am searching and challenging boundaries
Because I wonder what happens if…

What do I do?

What do I do?

What box do I fit in?

I find it hard to answer these questions because what I do, to me, is nothing special, except that it is, because for a lot of people what I do is magic.

To me what I do is nothing special because it’s just the way I am, but I am magic and my magic is that I listen.

I listen to people and I solve their business problems. Their problems with processes, technology, employee engagement.

I ask questions and listen until I understand.

I ask questions, challenge assumptions, until I have a clear picture of the situation.

I ask questions and discover the underlying issues.

I ask questions.

I listen.

I suggest practical, implementable solutions.

I am magic.

I enable you to be self-sufficient and not dependant on me for what I know: I will teach you what I have learned so that you can help yourself.

I am magic.

Note: this comes as a follow-on to the video, “Don’t put me in a box“.