A senior decision layer for prioritising use cases, testing readiness, choosing build-versus-buy, and defining the controls delivery will need.
AI creates pressure to move fast — and an unusually large number of plausible wrong turns. Teams buy software before the workflow is defined. Pilots fail because the source data was never accessible. Departments procure overlapping tools that solve the same problem twice.
A prioritised, evidence-based view of where automation actually pays off — with build-versus-buy decided, risk and governance defined, and a sequenced roadmap your team can execute with confidence.
Separate credible first moves from expensive distractions.
Understand what must be bought, configured, built or left alone.
Carry requirements, controls, measures and ownership into delivery.
Opportunity audit, readiness testing, build-versus-buy analysis and a sequenced roadmap — delivered as one decision package.
Start with operating friction, value and ownership rather than product names.
Review data, systems, people, process and governance before implementation.
Compare control, time, dependency, cost and long-term operation.
Sequence enabling work and use cases by evidence, not enthusiasm.
We're not tied to a platform or a delivery pipeline to protect. The output is a clear recommendation — including where the honest answer is to wait, or not automate at all.
Representative figures observed across Silverstone AI consulting engagements.
Results vary by scope, data quality, implementation and operating environment.
A consulting route that ends in decisions, not another slide deck.
Define scope, stakeholders and evidence required.
Review workflows, data, systems, risk and ownership.
Score value, effort, risk and dependency.
Produce decisions, controls, measures and a sequenced roadmap.
Every quarter without a prioritised roadmap is another quarter of scattered, overlapping bets. The first conversation is exploratory and commits you to nothing.
