AI Strategy
95% of AI pilots fail. Yours does not have to.
AI strategy consulting from a team that also builds. We do not just write the roadmap. We know what it takes to ship to production.
The global AI market reached $638 billion in 2024 and is projected to hit $3.68 trillion by 2034. Yet Gartner estimates 85% of AI projects fail to deliver. Only 9% of companies have fully deployed an AI use case. 47% of chief experience officers identify data readiness as the primary obstacle. The difference between the companies capturing value and the 91% stuck in pilot mode is not technology. It is strategy, execution, and the willingness to scope ruthlessly.
Why AI strategies fail
The most common failure mode is not technical. It is strategic. Companies start with ‘we should do something with AI’ instead of ‘we have this specific problem that AI is the right solution for.’ The result is a solution in search of a problem, a pilot with no success criteria, and a budget that evaporates before production.
The second failure mode is the handoff gap. A consulting firm writes a beautiful strategy deck. Then they leave. The internal team tries to implement it with insufficient resources, the wrong talent, or unclear priorities. The strategy sits in a Google Drive folder.
Our approach: strategy that ships
We start with a 2-week diagnostic. We audit your current operations, identify the highest-ROI automation opportunities, and size the investment required for each. You get a ranked list of opportunities with realistic timelines, cost estimates, and expected returns. Not a 100-slide deck. A decision-ready brief.
Then, if you engage us to build, we execute the strategy we designed. Same team, same context, no handoff. The people who identified the opportunity are the people who build the solution. This eliminates the #1 failure mode in AI consulting: the gap between strategy and execution.
What a good AI strategy contains
A clear articulation of the business problem (not ‘use AI,’ but ‘reduce claims processing time by 50%’). A prioritized list of opportunities ranked by ROI and feasibility. A realistic assessment of data readiness. A team and skill gap analysis. A phased implementation roadmap with milestones and success criteria. And an honest assessment of what AI is not the right solution for.
- Problem definition with measurable success criteria
- Opportunity ranking by ROI and implementation feasibility
- Data readiness assessment (do you have what the AI needs?)
- Build vs. buy analysis for each opportunity
- Team capability gap analysis
- Phased roadmap with quarterly milestones
- Risk register with mitigation strategies
FAQ
Fair questions.
Ask us directlyHow is this different from McKinsey or BCG AI consulting?
They advise. We advise and build. Same team, no handoff. Our strategies are grounded in what we know is buildable because we have built it. We do not recommend architectures we have never shipped.
What does the diagnostic phase cost?
From $25K for the 2-week diagnostic. You get a prioritized opportunity map, ROI estimates, and a phased roadmap. If you engage us to build, the diagnostic investment informs the implementation.
Do you only consult on AI or broader technology strategy?
Our core expertise is AI and automation. For broader technology strategy (platform selection, team structure, technical debt), we advise within the context of your AI and automation goals. We do not do generic IT consulting.
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