Decisions instead of debates
Every use case comes with expected impact, cost and payback, so the roadmap discussion is about numbers, not opinions.
AI Consulting
AI strategy
A ranked portfolio of AI use cases with business cases attached. A plan your board can fund and your engineers can build.
What it is
An AI strategy engagement turns 'we should do something with AI' into a ranked list of use cases with numbers attached. We map your workflows, score every opportunity for value, feasibility and risk, and write the business case for the ones worth funding. The output is a decision document your board can act on, not a vision deck.
It runs in four to six weeks. We interview stakeholders across the business, review your data and systems, and pressure-test candidate use cases with the people who run the affected workflows every day. Senior engineers do this work, so feasibility calls are grounded in what your systems can support today, not in vendor promises.
What changes: leadership stops debating AI in the abstract and starts approving specific initiatives with owners, budgets and success metrics. The first pilot is scoped and ready to start the week the strategy is signed off, and everyone has agreed in advance what result would justify taking it to production and scaling further.
Why it works
Feasibility checked by builders
The engineers who score feasibility are the ones who would build the system. No hand-off gap between strategy and delivery.
Quick wins surfaced first
We sequence the roadmap so a high-value, low-risk pilot lands early and builds the appetite for the harder bets.
Build vs buy resolved
For each use case we compare vendor tools against a custom build on cost, control and fit, and give you a clear recommendation.
A roadmap that survives contact
Milestones, owners and metrics are set with the teams doing the work, so the plan holds up after we leave the room.
AI Consulting
How we run it
01
Assess
Stakeholder interviews, workflow mapping and a review of your data and systems. Two weeks in, the opportunity long-list is on the table.
02
Prioritize
We score each use case for value, feasibility and risk in a workshop with your team, then cut the list to the two or three worth a business case.
03
Design
For the shortlist we draft reference architectures, settle build vs buy, and estimate the cost to build and to run.
04
Commit
We write the roadmap, the business cases and the pilot plan, then present them to your leadership for a funding decision.
What you get
AI opportunity map with scored use cases
Business case for each shortlisted use case
Reference architecture for the top use cases
Sequenced adoption roadmap with owners and milestones
Scoped plan for the first pilot
Common questions
Do we need an AI strategy before running a pilot?
Not always. If one use case is obviously valuable, a pilot first is fine and we often recommend it. Strategy earns its cost when there are many candidate ideas, several stakeholders and a real budget decision to make.
Who from our side needs to be involved?
A sponsor from leadership, the owners of the affected workflows, and someone who knows your systems and data. Expect a handful of interviews and two workshops: a few hours per person over the whole engagement, not weeks of their time.
What if the honest answer is that AI is not worth it yet?
Then that is the recommendation you get, in writing, with the reasons. Usually there is a prerequisite worth fixing first, like data access or process consistency, and the roadmap says exactly when AI becomes worth revisiting.
Get a roadmap worth funding
Start with a free 30-minute call. We will tell you whether a strategy engagement or a straight pilot is the better first step.
Book a strategy call