The people you hired to think about the game spend most of their time not thinking at all.

Last week I watched an analyst spend four hours manually building an excel dataset. Not analysing. Not strategising. Just fixing data someone else exported wrong.

This is the hidden tax your department pays every day.

For years, every technological "advance" demanded more from analysts. Video meant tagging systems. Excel meant spreadsheets. Then Python. R. SQL. Telestration. BI. Visualisation tools. Custom applications.

Each tool promised efficiency. Each delivered burden.

That pattern just broke.

AI doesn't add another layer. It absorbs the layers. Code becomes disposable. Cheap to create, cheap to discard. The distance from question to answer collapses.

But speed isn't the real story. Presence is.

Your analysts have been trading visibility for output. They've had to choose between being in the room and doing technical work alone. The burden made them invisible when visibility mattered most.

Now they can be in the meeting, not chained to the spreadsheet. Seen as analytical minds, not IT support.

The tempo shifts too.

Before, the ambitious questions had to wait. Off-season projects. Student dissertations. By the time insight emerged, the window had closed.

Now a Tuesday hunch becomes Thursday insight. A pattern in match footage gets validated before the weekend.

And because the cost drops, exploratory work becomes possible mid-season. Test ten ideas knowing eight might lead nowhere. Previously, only safe questions got asked. Now analysts can afford to be wrong quickly. That's how they find what's right.

This shift is already creating separation.

For brilliant analysts at under-resourced clubs, AI closes the gap. For organisations that invested in great talent and data culture, AI multiplies everything.

But departments that mistook managing complexity for creating value? AI offers no rescue. It might expose that the expensive team wasn't producing insight at all, just managing plumbing that no longer needs managing.

When technical burden stops equalising everyone, thinking becomes the differentiator.

One caution: speed without understanding is still exposure. The technology that builds can also be used to understand. But that takes intentional learning. Analysts who treat AI as a shortcut rather than a foundation will find themselves caught out.

Worth considering:

The analyst I watched last week is already making the shift. The four hours he used to curate the CSV, now go into the room, into the conversation, into work that actually moves the needle.

When the barriers fall away, what will your analysts do with what's left?

Make sure the answer is "think."