AI-Enabled Digital Transformation: Where Should Enterprises Start?

A practical way to choose the first move — and why “start with the data” is not always the right answer.

Nearly every enterprise now has a mandate to “do something with AI” and a portfolio of transformation ideas. The hard question is not whether to act but where to start so that the first effort builds momentum rather than draining it.

Start where three things overlap

The best first move sits at the intersection of real business pain, feasible with today’s technology, and bounded enough to finish. A high-volume, rules-heavy, judgement-light process that a specific team complains about is usually a better first target than a strategic-sounding initiative with no clear owner.

Why “fix the data first” can be a trap

A full data modernization before any AI work often means twelve months with nothing visible to show. A better sequence is to pick a use case, discover exactly which data it needs, fix that slice, and ship. The narrow win funds the broader data work and proves the value of it.

Digitalise, Connect, Enable AI — in that order, locally

If the target process is still manual, digitise it first; you cannot put AI on top of a process that only exists in someone’s head. If it is digital but the data is trapped, connect it. Then enable AI on that connected slice. Applied to one process at a time, this sequence is fast; applied to the whole enterprise at once, it is a decade.

Make the first engagement an assessment

A short assessment — the Sense stage of SHARP — produces a ranked list of candidate use cases scored on value and feasibility, a prototype of the leading one against real data, and a plan. That is a far better first deliverable than a strategy deck.

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