AI audit

Most organizations are already using AI in some form. A few tools here, a prompt there, a workaround someone discovered and shared. Over time, this becomes a patchwork: useful in places, wasteful in others, rarely visible as a whole.

An AI audit is a clear-eyed look at that reality. Not a technical review, but a practical one. We examine how work is actually being done: Where AI is being used, where it is quietly shaping outcomes, and where it has been introduced without much scrutiny. This includes both formal tools and informal habits that have taken hold across teams.

From there, we assess what is happening in practice. Where is AI saving time in a meaningful way, and where is it adding friction through rework, errors, or overuse? Where are people relying on it too heavily, and where might it be overlooked entirely? The goal is not to judge usage, but to understand it well enough to make deliberate decisions.

What emerges is a grounded picture of how AI fits into your current workflows: What’s working, what’s not, and what carries risk. That clarity becomes the basis for everything that follows.

From here, the next step is to rethink how that work should be structured.