Welcome to the New and Improved Cognita Journal

Sep 1

Longtime subscribers already know that I’ve decided to make some changes to how I handle my newsletter. Basically, I’m simplifying my workflow and optimizing my content marketing strategy by going with a blog-first approach.

That means I’ll be publishing the newsletter at www.cognita-km.com/blog, then sending it out to subscribers. I’m also going to stop publishing the newsletter on LinkedIn, though I will still be quite active there as it’s my primary social media channel for Cognita.

Let me know if you have any suggestions for improvements!

Upcoming appearances

On September 18, I’ll be speaking at the Association for Talent Development Austin Chapter’s Quarterly Chapter Meeting. Topic: From “Just-In-Case” to “Just-In-Time” – Empowering Learning & Performance with MVP Knowledge Management. Learn more

I’m excited to announce that I’ve been invited to speak at the Contact Center AI Association’s quarterly meeting in New York City on September 25. The meeting will focus on Knowledge Base Management as well as Roles and People Driving AI Initiatives. Learn more

Don't Let Your AI Trip Over its Own Two Feet: Why Trusted Knowledge is the Real MVP!

I recently came across the State of AI 2025: Mid-Year Report from eGain and Unisphere Research, and found some insights that anyone who manages a knowledge base (or cares how they’re managed) should keep in mind.

The report says that 70% of the organizations they surveyed are already piloting or having deployed GenAI. From customer self-service (cited by 45% of respondents) to human-assisted contact centers (38%), AI is quickly becoming part of how we deliver support. Even knowledge workers, including authors and managers, are significant users of GenAI output, at 45% each.

But (and it's a big one) there's a crisis of trust, which probably comes as no surprise. In the survey, 61% of respondents said they’re concerned about the accuracy or consistency of AI answers, and 54% worry about non-compliance. “Garbage in, garbage out" has never been more relevant. If your AI is built on faulty data, you can't expect reliable results.

The report points directly to the Achilles' heel of many organizations: siloed knowledge bases and failing legacy systems. A majority of companies (55%) are wrestling with three or more knowledge silos, and 51% are juggling three or more different KM tools.

As the report puts it, "Simply slapping GenAI over these silos only takes chaos to the next level.” This is exactly why a badly managed KB is worse than no KB at all—you're paying to create problems, not solve them.

If I’ve said it once, I’ve said it a thousand times: knowledge management technology and processes are the key to successfully deploying customer service AI that works (and that people want to use). It looks like 83% of the survey respondents agree. Without a robust knowledge foundation, AI struggles to understand context and intent, leading to frustration for both customers and agents. This isn't just about efficiency; it's about making sure your AI isn't messing up your AI.

So, what's the solution? A robust, well-managed knowledge base that serves as your single point of truth. The approach outlined in my book, “MVP KB: A Practical Guide for Customer Service Knowledge Management" is one way to tackle this problem.

Here’s how a trusted MVP KB and AI can create a powerful duet:

Automation for Efficiency: AI can automate the discovery, creation, curation, publication, and optimization of knowledge, potentially leading to a ten-fold improvement in the speed of knowledge creation and findability of answers. This frees up your human experts to focus on complex issues.
Empowering Your People: Even with AI, human expert involvement is critical for assuring the quality of GenAI output. Your agents are the experts, and the MVP KB empowers them to contribute, share, and provide feedback, turning tacit knowledge into explicit, valuable assets. The knowledge manager acts as a change agent, not a gatekeeper.
Single Source of Truth: Unifying your knowledge into a single, trusted hub is essential. This means better, more consistent answers for customers and faster problem-solving for agents. Currently, close to two in three respondents (64%) in the survey I talked about earlier either have no plans for consolidating their knowledge silos or are unaware of such plans. This represents a key reason for the failure of KM initiatives.
Modern Capabilities: Many companies are still not actively using GenAI for content creation and curation. However, modern KM systems offer AI-powered features for drafting articles, summarizing information, and identifying knowledge gaps, making content creation faster and easier.

Don't Be Afraid to Start!

While 62% of companies are "not in 'love'" with their current KM technology, and many are missing opportunities to leverage GenAI for content creation, the good news is that it’s fixable. Get a jumpstart on building your MVP KB by reading MVP KB: A Practical Guide for Customer Service Knowledge Management, or schedule a free, no-strings consultation with yours truly.

Take the first step toward ensuring your AI systems truly work for your customers and agents, providing accurate, relevant, and accessible knowledge every single time. Make sure your AI plays a winning tune, not just noise.

KM News

This one has 4.5

Derek Smalls being one of the greatest bass players of all time means that I have to share this story about where AI consistently comes up short.

See Me, Feel Me

If you’re not following me on LinkedIn, you may not know that I recently was a guest on the Contact Center Gurus Podcast. I’ve been working with Fred, Darren and the team at Cloud Tech Gurus since late last year. They’ve recently restarted their podcast series, and invited me on to talk about the future of knowledge management. Check it out:

Take on me

I’m not much for hot takes, but I’m of the strong opinion that AI is the ultimate KM tool (if it’s used in the right way). A recent story from AI Invest supports my contention. The AI-driven KM market is on track to be about $9.6 billion by 2025, driven by the urgent need to automate data workflows and analyze unstructured information. By freeing employees from repetitive tasks, they can focus on high-value work, becoming much more efficient. But it can only happen with robust governance frameworks and a clear strategy, turning knowledge from a liability into a genuine competitive asset.