Stop Telling Me How You Are "Doing AI"

I recently spent a week with teams in several organizations, who proudly declared that they were “doing AI.” You could not move without someone telling you how wonderful it all was or how their company was “using AI,” “moving to AI,” or “building an AI strategy.” After the tenth conversation, my head felt like it might explode.

I say this as someone who has worked in technology long enough to have seen genuine innovation. I have been part of organizations that raised the bar and moved industries forward. But I am not a technologist. I am a sales leader and a people person. My curiosity is always the same. How can you do what you do better? How can I help you do it faster? How do we reduce risk? How do we free you up to innovate and outperform your competition?

How the history of buzzwords has repeated

What I heard instead reminded me of every transformation buzzword we have lived through:

• “We are doing DevOps.” Really? You have development, you have operations, you have a bit of testing, and some change control. That does not mean you are doing DevOps. It usually means you are doing the same thing, but applying a new label.
• “We are moving to the cloud.” Are you? Or did you simply announce it to the board and then find yourself knee deep in complexity, contending with a lack of personnel and a lack of understanding of the implications of shifting entire landscapes of infrastructure into a virtual sky?
• “We do cyber security.” Yes, and at one point, the biggest revelation in the industry was that the most significant threat was often inside your own walls. Hardly cutting-edge insight.

These moments are not isolated. They form a pattern that has repeated for decades. A company latches on to a buzzword, waves the banner, declares success, and then wonders why no meaningful outcomes materialize.

“Doing AI” versus achieving outcomes with AI

For far too many organizations, the same story is about to be repeated, this time with AI.

If all you have done is tick the box that says “we are doing AI,” you have already missed the point. Outcomes are everything. When you say you are “doing” something, what do you actually mean? Improve? Optimize? Innovate? Reduce risk? Reduce cost? That last one always makes me smile. Reduce cost? Do you truly understand what this is going to cost you?

AI can absolutely help you work faster. It can improve organization, boost innovation, and eliminate mundane tasks. AI can improve your benefits realization story. It can free clever people to do clever work. But it can also increase your risk dramatically if you do not approach it properly.  AI can put you ahead of your competition or put you out of business—and both outcomes can come faster than you thought possible.

Where to start: Planning and prioritizing around outcomes

So how do teams move from talking about doing AI to achieving outcomes with AI? The real work begins with planning and prioritization, not with the technology itself. You must know where to apply AI, which projects actually matter, who the stakeholders are, what resources you have, and what outcomes you are aiming to achieve.

You need the financial discipline to understand AI’s cost, benefits, and return on investment. Otherwise, you are not “doing AI.” You are spending money with impressive speed and very little direction.

While organizations rush to external data to feed AI models, I still maintain that many do not understand the data sitting right in front of them. Here are just a few examples:

• CRM platforms hold enormous corporate intelligence.
• Email systems contain some of the most critical knowledge in the business.
• Data lakes are overflowing.

Yet we ignore our own goldmine while chasing someone else’s, asking whether we trust their data when we barely trust our own.

I am excited about innovation. I am excited about freeing brilliant minds from repetitive tasks and unlocking creativity at scale. I am excited about using underutilized resources in ways we have not imagined. Am I excited about AI? Refer back to paragraph one.

In short: Have a clear outcome in mind

I welcome debate on all of this. But enter the discussion with a clear outcome in mind. Because if you are still talking about how your organization is “doing AI,” your competitors may have already turned AI into value. And by the time you notice, they will have moved on and moved you out of the way. Let’s chat.