What AI consulting should deliver for your business
Useful advice ends in decisions, not slides. An engagement should leave you knowing which use cases to pursue first, which to leave alone, what each requires in data, integration and people, and what could go wrong. We arrive at that by looking closely at how work is actually done. We sit with the teams involved, review sample documents and tickets, and inspect the systems an AI solution would need to read from and write to.
Each candidate is then scored on the same dimensions: the effort it removes or the revenue it supports, technical feasibility with current models, the state of the underlying data, the cost of an error, and how easily it fits existing systems. Some ideas turn out to need ordinary automation rather than AI, and we say so. The result is a short, ranked list with reasoning your leadership team can examine and challenge.
- Ranked use cases with clear reasoning
- Data and integration gaps identified
- Risk assessment for each candidate
- Build, buy or wait recommendations
- Success measures agreed in advance