How is this different from a McKinsey or BCG AI strategy engagement?

The work is led by a senior operator who has built and shipped software, not staffed by a pyramid of analysts. You get direct access, faster cycles, and a roadmap written to be executed by your teams rather than to justify the next phase of consulting.

We already have a list of AI ideas. Do we still need strategy?

A list of ideas is not a strategy. The value is in ranking them against each other, killing the ones that will not reach production, and sequencing the survivors so investment compounds. That is exactly what this engagement produces.

Do you help execute the roadmap, or just write it?

Both. Many clients move from strategy into an AI-native transformation or fractional leadership engagement so the same people who wrote the plan help land it.

For leadership teams

AI Strategy and Roadmap

Most AI strategy stalls in one of two places: a slide deck that never becomes a plan, or a pile of pilots that never reach production. We build the plan that connects the two.

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Who this is for

Executive teams and boards who need a defensible point of view on AI, a prioritized set of bets, and a roadmap their organization can actually execute.

The situation

The pressure to "do something with AI" produces motion without direction. Teams chase whatever launched last week, budgets scatter across disconnected experiments, and no one can say which efforts will matter in eighteen months. The result is spend without compounding return.

How it works

What we do

Value mapping

We trace AI to the specific places it moves cost, revenue, and cycle time in your business, not the industry in general.

Opportunity scoring

Every candidate use case is scored on value, feasibility, data readiness, and time to production, so priority is a number, not a hunch.

Capability design

We define the data, platform, talent, and operating changes each bet requires, and whether to build, buy, or partner.

Sequenced roadmap

The plan is staged around proof points and decision gates, so investment scales only as evidence accumulates.

What you walk away with

A written AI thesis: where AI changes your economics, and where it does not
A ranked portfolio of opportunities, scored on value and feasibility
A phased roadmap tied to owners, budgets, and decision gates
A build, buy, and partner view for each capability
A risk and governance posture your board can stand behind

Deliverables

AI strategy document and thesis
Scored opportunity portfolio
Phased roadmap with owners and gates
Capability and platform assessment
Executive and board briefing

Engagement

A focused engagement, typically four to eight weeks, run with your leadership team rather than delivered to them.

Questions

Frequently asked

How is this different from a McKinsey or BCG AI strategy engagement?: The work is led by a senior operator who has built and shipped software, not staffed by a pyramid of analysts. You get direct access, faster cycles, and a roadmap written to be executed by your teams rather than to justify the next phase of consulting.
We already have a list of AI ideas. Do we still need strategy?: A list of ideas is not a strategy. The value is in ranking them against each other, killing the ones that will not reach production, and sequencing the survivors so investment compounds. That is exactly what this engagement produces.
Do you help execute the roadmap, or just write it?: Both. Many clients move from strategy into an AI-native transformation or fractional leadership engagement so the same people who wrote the plan help land it.