AI Use Snapshot
Which tools staff are using, where they are being used, whether leadership knows, and where the obvious risks sit.
Proof
Gives leadership visibility before risk compounds.
Two weeks. Four questions answered before you commit to anything: what AI is being used and where the risks are, what could realistically help, what should stay away from AI, and what needs to be fixed first.
Most businesses are already using AI. Staff have adopted tools nobody approved, running on data nobody has verified, in workflows nobody has documented. The question is not whether AI is in the business. It is whether the business knows where it is, what it is doing, and what needs to change.
This diagnostic answers four questions before any commitment is made: where AI is already being used and where the risks sit, where AI could realistically help, what should not be automated or touched yet, and what needs to be fixed before any AI tool can safely do its job.
No implementation. No tool recommendations. No transformation language. The output is a decision pack and a specific next step, not a strategy deck, a technology audit, or a project plan.
Every finding maps to a risk, an opportunity, or a fix-first item. If it does not change a decision, it does not go in the report.
This layout is for explaining a service as a repeatable operating shape: who it is for, how the work moves, and what the client leaves with.
Leadership has decided AI matters but the business has not translated that into a sequence of specific decisions, owners, and timelines. The pressure is real but the path is not.
AI tools are in use without approval, oversight, or any clarity on what data is being shared. You need to know what is happening before the risk compounds.
A board, CEO, or leadership team needs a defensible view of where to start, what to defer, and how the next phase will prove value.
Define the decision context, the sponsors, the constraints, and what a useful diagnostic must answer before any interviews are scheduled.
Day 01 to 02Interview staff, leaders, and operators. Identify every AI tool in use, every workflow it touches, and every risk that is currently unmanaged.
Days 03 to 07Assess where AI could genuinely help against value, feasibility, data condition, risk, and ownership readiness. Build the opportunity and risk map.
Days 08 to 10Present the findings, the recommended next step, the fix-first items, and the specific Phase One path the business should take.
Days 11 to 14Which tools staff are using, where they are being used, whether leadership knows, and where the obvious risks sit.
Gives leadership visibility before risk compounds.
The main blockers across systems, data, workflows, knowledge, governance, and staff capability.
Shows what must change before AI work can safely proceed.
Three to five realistic AI use cases, ranked by usefulness, risk, and how ready the business actually is.
Separates usable opportunities from wishful thinking.
The ideas that are risky, premature, vague, or not worth the money.
Prevents the business from funding the wrong AI work first.
One clear path forward: which service addresses the biggest gap, or whether the foundations need fixing before AI work begins at all.
Removes the "what do we do next" question entirely.