AI Strategy and the Operating System Mismatch (with Dave West)
A conversation with Dave West at Scrum.org about the 95% AI failure rate and why organizations need a different management operating system for AI work.
Click image to open full size In a recent episode of the Scrum.org podcast, I sat down with CEO Dave West to discuss why so many organizations are struggling to turn their AI investments into business impact.
While we’ve previously discussed how your Operating System can be a bottleneck for AI, this conversation focused specifically on the mechanics of how AI adoption is shifting the boundaries of traditional IT.
The failure pattern
Dave highlighted a startling figure: 95% of AI projects fail to deliver meaningful value.
But as we explored the “why” behind this number, a pattern emerged. These failures rarely stem from the technology itself. The failure happens when organizations try to project-manage a complex, emergent technology with a 20th-century mindset.
“The key for me, what I see where people are finding gold using AI… is when they use product techniques, whether they call it product or not.”
Beyond the IT Boundary
One of the most profound insights from our discussion was that AI adoption challenges now originate outside traditional IT. We’re seeing sales, marketing, and legal departments leading AI initiatives without the necessary operating system to support the uncertainty of high-potential developmental work.
Context is the New Training Data
We discussed the concept of “Context Development.” Just as a product defines its scope and purpose, an organization must provide AI with consistent boundaries and relevant information to be effective. This is why some suggest that Context is the new Code: the performance of GenAI depends less on how you code the interface and more on the quality and specificity of the context—data, constraints, user persona—you provide it.
Key takeaways for leaders
- Differentiate work types: Don’t treat operational optimization, where the work is stable, the same as innovation, where the work is complex. AI fits better in an agile, product-oriented mindset.
- Use strategy alignment: Ground AI initiatives in real business strategy rather than technology for technology’s sake. OKRs can help if they stay tied to actual outcomes.
- Keep adapting: Your operating system must be capable of sensing, responding, inspecting, and adapting in real time. Even a traditional PMO can adapt to this reality if it shifts from schedule policing to evidence-based governance focused on leading indicators of value.
Listen to the full episode on Scrum.org: AI and the Implications for your Organization’s Operating System.
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