AI Strategy & Roadmap

AI strategy is where most consulting engagements start - and where most of them end. A roadmap that sits in a shared drive is not a strategy. A prioritized, scoped, resourced implementation plan tied to specific business outcomes is. That is what we produce, and we produce it in two weeks.

What we do for clients

We work across the full AI strategy lifecycle:

• AI maturity assessment - structured evaluation of your data readiness, technical infrastructure, team capability, and organizational readiness across five dimensions
• Use-case identification and prioritization - systematic mapping of AI opportunities across your business, scored by feasibility, ROI, and time-to-value
• Build vs. buy analysis - structured framework to determine what to build custom, what to buy off-the-shelf, and what to configure from foundation models
• Implementation roadmap - a phased 12-month plan with defined milestones, resource requirements, cost projections, and risk flags
• Data readiness audit - honest assessment of whether your data can support the use cases you are considering, and what it would take to close the gaps
• Governance and compliance mapping - regulatory and security requirements identified and mapped to your roadmap before any build decisions are made

How we run an AI Strategy engagement

Every strategy engagement follows the same three-phase structure, led by a senior partner at each stage:

1. Diagnose. We interview your stakeholders, audit your data, and map your existing technical environment. We are looking for two things: where AI can create measurable value, and where the assumptions that would kill an implementation already exist. This phase typically runs one to two weeks and ends with a prioritized use-case longlist and a data readiness report. We will tell you if something is not viable before it becomes a roadmap item.
2. Design. We score and rank the shortlisted use cases against a consistent framework - business value, data feasibility, technical complexity, time-to-value, and organizational readiness. The output is a sequenced implementation roadmap with defined milestones, resource requirements, and a build vs. buy recommendation for each use case. You review and approve the roadmap before anything moves to implementation.
3. Handoff and planning. We present the roadmap to your leadership team, walk through the assumptions behind every recommendation, and produce a scoped proposal for the first implementation phase. If you move forward with us, the strategy engagement folds directly into the Diagnose phase of the implementation. If you take it in-house or to another partner, you have everything you need to do that.

The best AI strategies don't feel like consulting deliverables. They feel like a clear answer to a question your organization has been circling for months.— Dr. David Kim, Founder & CEO

Where we fit best

Most of our strategy engagements are with organizations that have meaningful AI ambitions and genuine uncertainty about where to start - typically mid-market and enterprise firms with complex data environments and $50K+ implementation budgets. We have run strategy engagements as standalone projects from $15K and as the entry phase of full implementations from $85K.

We are a particularly strong fit for:

• Organizations that have had a previous AI initiative fail or stall and need an honest assessment of why
• Leadership teams that need a defensible business case for AI investment before committing budget
• Technology and data teams that know what they want to build but need external validation and sequencing
• Companies preparing for a significant AI investment and want to de-risk the decision before contracts are signed

We work closely with your internal engineering and data teams throughout - and have a strong track record of producing strategies that internal teams can actually execute, without the friction that comes from recommendations made without understanding the existing stack.