Tag: KM Strategy

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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 Feed it outdated policies, inconsistent documentation, and tribal knowledge that lives only in people’s heads — and you’ll get confident, fluent, wrong answers at scale.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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Your Organisation Has a Knowledge Management Problem. It Just Doesn’t Know It Yet

(This post originally appeared on my LinkedIn Profile.)

Ask most people what Knowledge Management means and they’ll mention a chatbot. Or a FAQ database. Or the system the contact centre uses to answer customer calls faster.

They’re not wrong. That is KM. But it’s one room in a very large house.

And while everyone’s focused on that room, the rest of the house is quietly falling apart.

The contact centre problem

Contact centre KM is visible. It has vendors. It has metrics. It has a clear ROI story — faster handle times, fewer escalations, happier customers. There are software platforms built specifically for it. Conferences dedicated to it. Entire consulting practices around it.

So when organisations say “we have KM,” they often mean “we have a tool that helps agents answer questions.”

That’s not KM strategy. That’s knowledge delivery at one endpoint.

What’s happening everywhere else

While the contact centre is meticulously managed, here’s what’s happening in the same organisation:

A senior leader retires and takes twenty years of institutional memory with them. Nobody captured it. Nobody thought to.

A project team spends three weeks solving a problem that another team solved eighteen months ago. The solution existed. It just wasn’t findable.

A proposal goes out with assumptions that contradict positions taken on a previous engagement. The left hand didn’t know what the right hand had written.

A new hire takes six months to reach full productivity because the knowledge they need lives in people’s heads, not in any system.

None of this shows up in a contact centre dashboard. All of it is a knowledge management failure.

The invisible KM problem

Contact centre KM is visible KM. It has a home, a budget, and a team accountable for it.

Everything else is invisible KM — the organisational knowledge that lives in people, relationships, past work, and institutional memory. It has no home. No owner. No metrics. And so, no urgency.

Until someone leaves. Until a bid is lost. Until a mistake is repeated. Until the organisation realises it keeps reinventing the wheel because nobody was minding the wheel.

KM is a whole-organisation discipline

The international standard for KM — ISO 30401 — doesn’t mention contact centres. It talks about strategy, culture, learning, leadership, and governance. It defines KM as a management discipline that helps organisations create, retain, share, and apply knowledge to achieve their objectives.

APQC, one of the most respected research bodies in the field, frames KM across five pillars: strategy, process, content, culture, and technology. Technology is one pillar. The contact centre sits inside technology. That’s a lot of building left unattended.

The questions that reveal the real problem

You don’t need a formal audit to see where your organisation’s invisible KM is failing. Just ask:

  • What happens when your most experienced person walks out the door?
  • How long does it take a new hire to become genuinely productive?
  • How do you capture what worked — and what didn’t — at the end of a major project?
  • Can you find your organisation’s best thinking on any given topic in under five minutes?
  • Do your teams build on each other’s work, or do they start from scratch every time?

If those questions make people uncomfortable, that’s not a contact centre problem. That’s a knowledge strategy problem.

What to do about it

Start by separating the tool from the discipline. Contact centre software is a tool. KM is a discipline that applies across every part of an organisation — from how you onboard people to how you run retrospectives to how you capture competitive intelligence to how you make expert knowledge accessible to everyone who needs it.

Then look at where knowledge is genuinely at risk. Who are your critical knowledge holders? What happens when they leave? Where does important knowledge live that isn’t written down anywhere?

You don’t need a massive programme to start. You need someone asking the right questions. And you need leadership that understands that knowledge isn’t just a contact centre asset — it’s the organisation’s most valuable and most under protected resource.

The contact centre KM is working fine. That’s not the problem.

The problem is the illusion of coverage it creates. The belief that because one type of knowledge is well-managed, the rest is too.

It isn’t. And the cost of that gap shows up slowly — in turnover, in repeated mistakes, in lost bids, in the quiet erosion of things that once worked.

KM done well is invisible too. You notice it in how fast people find what they need. In how smoothly transitions happen. In how teams learn from each other rather than around each other.

That kind of KM doesn’t live in a single tool. It lives in how an organisation thinks about what it knows — and what it can’t afford to lose.

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Your Contact Centre Has a Knowledge Base — It Probably Doesn’t Have a Knowledge Management Strategy

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

There’s a distinction that rarely gets made in contact centre operations — and it’s costing organisations more than they realise.

A knowledge base is a technology. A knowledge management strategy is a discipline. Most government contact centres have invested in the first and almost completely ignored the second.

I’ve seen this pattern repeatedly in my work with public sector clients: a KB that was built with good intentions, populated in a flurry of activity at go-live, and then largely left to drift. Articles go stale. Ownership blurs. Agents stop trusting the content and start working around it — calling a colleague, improvising an answer, or escalating unnecessarily. The KB becomes a liability dressed up as an asset.

The Real Cost of Undermanaged Knowledge

Here’s what undermanaged knowledge actually looks like in practice:

  • The majority of KB articles in a typical contact centre are rarely or never accessed by agents — not because the need doesn’t exist, but because the content isn’t trusted, findable, or current
  • A significant portion of agent time on any given call is spent searching for information rather than using it — a direct consequence of poorly governed knowledge
  • Training costs multiply when knowledge isn’t structured — new agents take longer to ramp, and the learning is inconsistent
  • Compliance risk accumulates quietly — outdated content in a regulated environment isn’t just inefficient, it’s a governance problem

None of this is inevitable. It’s the predictable result of treating knowledge as a byproduct rather than managing it as infrastructure.

Where Most Contact Centres Actually Sit

When I assess contact centre KM maturity, I use a five-level model:

Level 1 — Reactive: A KB exists but it’s unstructured, inconsistently used, and has no governance. Knowledge lives in people’s heads or tribal networks.

Level 2 — Managed: Content standards are beginning to emerge. Ownership is being assigned. Review cycles exist on paper if not always in practice.

Level 3 — Defined: KM is integrated into agent onboarding, quality assurance, and performance frameworks. Knowledge-Centred Service (KCS) methodology may be in scope.

Level 4 — Optimised: Continuous improvement loops are running. Agents actively create and flag knowledge as part of their workflow. Metrics drive decisions.

Level 5 — Strategic: Knowledge management is a competitive differentiator. The KB feeds self-service channels. AI-assisted tools are deployed on a well-governed foundation.

The majority of government contact centres I encounter are operating between Level 1 and Level 2. They have the technology. They lack the strategy, the governance, and the culture to make it work.

What Moving Up the Maturity Curve Actually Requires

There is no shortcut from Level 1 to Level 4. But the path is well understood, and each step produces real, measurable value.

Start with an honest diagnostic. Before proposing solutions, you need to understand where the gaps actually are — not where leadership assumes they are. A structured KM health check covering content quality, governance, agent culture, technology integration, and measurement gives you a baseline and a prioritised roadmap.

Fix the content before you fix the culture. Agents won’t trust a KB they’ve learned not to trust. A content audit — systematically assessing quality, relevance, and alignment with how customers actually query — is often the fastest way to rebuild confidence and demonstrate early wins.

Build governance that outlasts any individual. The most common reason KM investments decay is that accountability wasn’t designed in. Without clear roles (who owns what domain, who approves what content, what the review cycle is), even excellent knowledge management falls apart when key people leave. And in contact centres, people leave.

Consider KCS when the conditions are right. Knowledge-Centred Service is the industry-standard methodology for embedding knowledge creation into resolution workflows — so that KB maintenance becomes a natural output of doing the work, rather than a separate burden. It’s transformative when an organisation is ready for it. A readiness assessment determines whether yours is.

Why This Matters More Now Than It Did Five Years Ago

There are two trends that make knowledge management infrastructure more urgent than it’s ever been.

The first is AI readiness. Every contact centre AI tool — virtual agents, agent-assist copilots, automated knowledge surfacing — depends on a well-structured, well-governed knowledge base to function. Organisations that invest in KM maturity now are building the foundation for AI deployment. Those that don’t will find that AI amplifies the mess rather than solving it.

The second is workforce continuity. Public sector contact centres face persistent turnover pressures. When knowledge lives in people rather than systems, every departure is a knowledge loss event. Structured KM is one of the most practical responses to that risk.

The Business Case Is Operational, Not Theoretical

I’ve noticed that KM initiatives sometimes struggle to get funded because they’re framed as capability-building or best practice adoption — language that doesn’t move budgets in government contracting environments.

The frame that works is operational infrastructure. Knowledge management improvement reduces handle time, lowers training costs, decreases escalations, reduces compliance risk, and creates the conditions for AI deployment. Those are outcomes executives fund.

The entry point doesn’t have to be a large programme. A two-to-three week KM health check produces an executive-ready maturity scorecard and prioritised recommendations. That’s enough to make the case for what comes next — and often, it’s enough to start the conversation that should have happened years earlier.

If you’re working in or with government contact centres and recognise this pattern, I’d be glad to connect and compare notes. The gap between having a knowledge base and having a knowledge management strategy is wide — but it’s entirely closeable.

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Does Knowledge Management Really Make a Difference?

Yes, I still get this question or some variation on it, even though there are lots of case studies and examples of knowledge management activities having a significant impact on the results of an organization.

The quickest and often the easiest way of winning over sceptics is by having the opportunity to do Knoco’s Bird Island workshop (https://www.knoco.com/bird-island.htm), I have seen more “light bulbs” come on for people in doing this 2-hour workshop than I ever would have believed.

I don’t want to give  away any of the surprise, but by using three different KM processes (After Action Reviews, Peer Assists, and Best Practice sharing) results of the activity go from abysmal to unbelievable, increasing  an average of 260%.

Even if you want to continue to be sceptical of the results that making better use of your organization’s knowledge can have and you think you can only attain a fraction of this, 10% of the result demonstrated in the workshop is still 26%. Isn’t that worth at least giving it a try?

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Importance of a KM Strategy

Why do I need a knowledge management strategy? Why can’t I just implement some technology and be done with it? Why can’t I just implement Communities of Practice or Lessons Learned and be done with it?

I hear this sometimes from managers who want a quick fix, who are under a lot of pressure from time and resources (money and people).

The answer is, you can. I have worked with many organizations that have done just that, jumped in with both feet and “just done something”. I am usually there to fix it. Fix the technology because no one understood what it really needed to do to support knowledge work within the organization; fix the process because no one understands it and it’s not aligned with the rest of the activities in the organization and it’s created extra work for already over-worked staff.

Why do you need a strategy?

Would you jump in the car and set out on a journey of 5000km/3000miles without having some idea of where you were going and how you going to get there? Making sure that you had selected the right vehicle to get you there in time and a map to help direct you along the way?

A KM strategy does just that. It helps you figure out where you’re going, and the things you need to do along the way, the processes you need to support you and that need to be supported.

That’s not to say that you won’t make adjustments along the way, just like a friend of mine who drove from Toronto to Vancouver in September 2015, who ended up “detouring” through the United States, so that she could see some different sites, but she still knew where she was going and when she had to be there by—she made it with time to spare.

Isn’t that what you want from your KM strategy? To know where you’re going and how you want to get there, to meet the goals and objectives of the organization?

Why would you put a toaster over in the car for your trip, when you really needed a camp stove?

Why would you choose one technology because “everyone else is” when another technology is cheaper and better meets the needs of the organization because it requires less customization than the more popular software?

Isn’t it time you created (or updated) your KM strategy?

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The Second KM Silver Bullet: One isn’t enough

As a friend of mine pointed out, it’s not enough to just create a strategy, it’s about the execution of that strategy.

And he’s right, strategies can sit on shelves, certainly I have had more than one client, that for various reasons did not implement the strategy we had developed together.

So what does it take to successfully implement a KM strategy?

A bunch of things, senior management buy-in and budget among them, but I would argue the most critical component, and the one that my friend posited, is Change Management.

There are many good books on Change Management by authors such as Peter Senge and John P. Kotter, to name two of my favourites. But what it all boils down to for me, is communication. Not just some manager decreeing, “thou shalt do knowledge management,” but a real conversation between the KM team and the rest of the organization. What do they need to be able to be effective in their jobs? How can the KM team help them? What do the users of the KM activities need to know about how to use the technology and the processes? What will aid them in their decision making and other things they are responsible for?

KM is there to serve the organization, to help it to be more efficient, effective, innovative, whatever the KM strategy identified as the business case for KM. It does that, in part, through the execution of the change management plan to support the transformational change that KM demands.

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The KM Silver Bullet

KM is a lot of things to a lot of people.

It seems everyone wants the silver bullet, the one “right” answer to the question of how to be successful in KM.

Or they want the one “right” answer to the question of what is KM and what’s included in KM.

Well let me save you a lot of time and heartache, there is no one right answer, the answer is, it depends.

It depends on your organization’s strategy, objectives, culture, industry, regulations, size, budget, risk profile, staffing profile, technology strategy.

Figure out what KM is to your organization and create a strategy that supports that definition, that’s the silver bullet.

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Designing a Successful KM Strategy

I guess I have been busy, it’s been 6 months since my last post. One of the things that I have been busy with is finishing the book that I have co-authored with my Knoco colleague, Nick Milton.

successful-km-strategy-2

Nick and I have written and book called, “Designing a Successful KM Strategy,” it’s being published by Information Today, Inc. Advance copies will be available at KM World, where I will be doing a workshop based on the book (Workshop W4) and a book signing.

I’ll post a link to their website once it’s available for order.

Also, I’m doing a second workshop at KM World called, “W14: Sparking Innovation: Creative KM,” in case any of you are interested in that.