LinkedIn may be full of posts by non-engineers boasting about their incredible creations with Claude Code (and the AI coding trend is a significant transition) but the research shows that enterprise AI is hitting a wall in terms of impact. IDC research found that 88% of AI proofs-of-concept never make it to production. For every 33 pilots a company launches, only four graduate to deployment. Gartner predicts that over 40% of agentic AI projects will be cancelled by the end of 2027, citing escalating costs, unclear business value, and inadequate risk controls. S&P Global reports that 42% of companies now abandon the majority of their AI initiatives before reaching production — up from 17% just one year ago.

Many have written about an impact gap or a value gap. But impact starts with the right strategy. And the main culprit for the lack of good strategy? The market is flooded with "AI strategists", inside and outside of large enterprises, who don't know their SaaS from their ELB(o). Bad strategies typically fall into two camps:

(1) The author has forgotten the meaning of strategy (a plan of action!) and instead compiles a collection of nebulous frameworks and principles with no actual plan for implementation, or

(2) They can vibe-code a prototype but their experience of building real solutions that actually work in an organisation is very limited. Without this technical knowledge, their "strategies" are often unimplementable, lack the buy-in of critical teams in the business (IT, InfoSec, ...), and are therefore useless. Would you trust a general who didn't know how a supply chain worked in practice?

On the other side there are technical specialists: the talented engineers who can build effective AI systems in the trenches. But these engineers often have a very limited understanding of how those systems will change job roles, team structures, or operational workflows — or how the reality of a new go-to-market motion will play out.

The gap between these two worlds is where AI initiatives die. But a viable, competitive AI strategy is urgent at every kind of organisation, no matter what size. We have to cross the AI strategy gap. To do that, we need a bridge that unites organisational systems design with self-sustaining AI governance.