Thirty percent of AI projects die at proof of concept. Not because the technology failed. Because nobody asked whether the problem was worth solving with AI in the first place.

30%of GenAI projects abandoned after proof of concept

1%of companies consider their AI strategy mature

$4.4Tin annual value unlocked by AI — for companies with a plan to capture it

Most companies do not build an AI strategy. They build a vendor-influenced roadmap: capabilities listed in search of problems, budget attached to buzzwords, and no accounting for what any of it will cost to maintain past quarter one.

We start from the other direction. The bottlenecks costing money. The decisions that take weeks when they should take hours. The manual processes that scale linearly while the business scales exponentially. AI is one possible fix. Often it is not the best one. The strategy's job is to make that call before a line of code gets written.

We assess readiness across four dimensions: data maturity, organizational capacity, technical infrastructure, and the economic case for each use case. The output is not a slide deck. It is a sequenced plan with dollar values on each initiative, requirements mapped against the current stack, data gaps flagged with remediation timelines, and a cost model that includes the ongoing operational spend most AI business cases leave out.

We have killed more AI projects than we have greenlit. That is the point.

The survivors share three things: clean data access, a measurable business outcome, and an organizational owner who will use the output. The ones we kill would have consumed six months of engineering time before reaching the same conclusion. We would rather deliver that verdict in a two-week assessment than watch it play out over two quarters.

What separates a strategy that ships from one that stalls is specificity. Not "implement machine learning across the organization." This model, trained on this data source, replacing this workflow, cutting processing from four hours to twelve minutes, at a build cost of X and a run cost of Y. We get that precise because we have built these systems. We know what is hard, what is fast, and what is not worth the time at any price.

The first project ships within 90 days. That win funds the credibility and the budget for everything after it.