Everyone Wants AI, Just Not the Work That Makes It Work

A colleague sent me this image this morning. No commentary, no explanation, no source. And honestly, I have not been able to stop thinking about it since.

It made me laugh immediately, but in that slightly uncomfortable way where you realize it's funny because it's true.

Because this is exactly what so many organizations sound like right now.

There's this real, palpable urgency around AI. You can feel it in meetings, strategy sessions, random hallway conversations. Someone inevitably asks, "What are we doing with AI?" and suddenly the pressure is on to have an answer, preferably one that sounds bold, immediate, and impressive.

What rarely follows is any meaningful conversation about the unglamorous parts. Things like: Do we actually have usable data? Is it clean? Is it consistent across systems? Do we even agree on what our key metrics mean?

Those questions don't generate much excitement. No one wants to rally around a plan to standardize fields or deduplicate customer records. That feels like maintenance work; important, but not exactly inspiring.

So instead, the conversation jumps straight to AI. Not what the problem is we're solving, not what decision we're trying to impair, just AI as an answer in search of a question.

The line int he image that gets me every time is, "AI to do what?" followed by "We don't know!" It sounds exaggerated, but in practice it's often just a more polite version of reality. There's a lot of enthusiasm without a clear use case attached to it.

And then there's the timing: "When do we want it?" --> "Right Now!" That part feels especially familiar. Even when the groundwork clearly isn't there, the expectation is still speed. Start a pilot. Show something quickly. Demonstrate value. We'll figure out the rest later.

Except later doesn't happen.

The slightly painful truth, which the meme captures perfectly, is that AI doesn't magically fix underlying issues. It tends to surface them faster and more visibly. If the data is messy, AI just makes the mess more obvious, and sometimes more consequential.

None of this is to dismiss the excitement. The excitement is warranted. AI can absolutely create value. But it's not a shortcut around the fundamentals. It depends on them.

That's why the organizations that are actually making progress tend to look a bit less dramatic than the meme. They're not necessarily the ones shouting loudest about AI. They're the ones quietly doing the less exciting work: cleaning up key datasets, aligning on definitions, choosing a specific problem to sole, and starting there.

It's not as meme-worthy, but it works.

Still, I have to give my colleague credit. The image might the most accurate summary of the current AI moment I've seen, and I have a feeling I'll be pulling it into a presentation or two!