Overcoming Digital Debt and Embracing AI in the Workplace
This Friday, I’ll be speaking at my first AgentCon event, part of the Global AI Community that runs gatherings for practitioners and builders all over the world. My stop is AgentCon Dallas 2026 (https://globalai.community/e/5o6jg5d0), happening June 26 in Plano, and I could not be more excited to be in a room full of people who are actually putting AI to work rather than just talking about it.
My topic is one I spend a lot of my professional life on: helping organizations move past digital debt so they can embrace AI in a way that actually sticks. It sits right at the center of the training and adoption advisory work I do with clients, and it is the difference between buying a Copilot license and genuinely transforming how people work.
So let’s talk about what digital debt is, and why it quietly stalls so many transformation efforts.
Two kinds of debt, one drag on progress
When most people hear “digital debt,” they think about systems. Outdated platforms, brittle integrations, the workflow nobody wants to touch because it might break six things downstream. That’s organizational digital debt, and it’s real. It shows up as decreased productivity, higher maintenance costs, security exposure, and a slow erosion of an organization’s ability to innovate. The tricky part is that it compounds. The longer it sits, the more expensive and disruptive it becomes to unwind, which is exactly why so many teams keep deferring the fix.
But there’s a second kind of debt that gets far less attention, and in my experience it’s the one that does the most damage to AI adoption. I call it individual digital debt, the personal version of the same problem. It’s the inbox a person can never get to the bottom of. The pings across six different apps. The hour lost every morning just reorienting to where things stand. When the volume of digital work coming at a person outpaces their capacity to process it, they fall behind, and they stay behind. That’s the debt, and most knowledge workers are carrying a heavy balance.
Here’s why this matters for AI…
We tend to assume the barriers to adoption are technical. In practice, they’re rarely just technical. When you drop a powerful new tool on top of someone who is already underwater, you don’t get transformation. You get one more thing to learn, one more tab to manage, one more source of guilt about the feature they “should” be using. The debt doesn’t disappear. It just gets a new interface.
Why this stifles real transformation
Organizational and individual digital debt feed each other. Outdated systems and inefficient processes generate friction, that friction lands on people, and people respond by building workarounds that quietly become the next layer of debt. Round and round it goes. Meanwhile leadership is wondering why the AI investment isn’t showing up in the numbers.
The honest answer is that you cannot automate your way out of a foundation problem. AI is extraordinary at removing repetitive work, surfacing insight, and giving time back. But it delivers those gains on top of whatever foundation you give it. Point it at messy data, undocumented processes, and an untrained workforce, and it will faithfully accelerate the mess. True digital transformation isn’t about layering AI on top of the debt. It’s about using the move to AI as the forcing function to finally address the debt underneath, in your systems and in your people’s day-to-day experience of work.
That second part is where I see the biggest gap. Organizations will fund the platform and skip the fluency. They’ll buy the seats and assume adoption will take care of itself. It won’t. The teams that get real return are the ones that pair the technology with deliberate training, clear use cases, and a culture that gives people permission to experiment. That’s how you pay down individual digital debt instead of adding to it.
Where I can help
This is the work I do, and it’s what I’ll be digging into Friday in Dallas (without a sales pitch, of course).
If your organization is ready to build genuine AI fluency, I deliver hands-on workshops ranging from 4 to 16 hours, with Microsoft-focused and Google-focused tracks as well as technology-agnostic sessions for teams that want the strategy before the tooling. These are practical, practice-heavy, and built around the real work your people do.
And for eligible organizations with 500 seats or more looking at broader Copilot adoption and strategy, I also offer Microsoft-funded engagements that can significantly reduce the cost of getting started.
If either of those sounds like where your team is headed, reach out. I’d love to talk through what paying down your digital debt could look like, and what becomes possible once it’s gone.
