90% of companies spent 2025 building AI pilots. Most of them have nothing to show for it. I have sat in enough boardrooms to know how this plays out.
The data team demos something impressive. Leadership nods. Budget gets approved.
Six months later, the question nobody wants to answer shows up: where is the return? Personal productivity gains from AI tools do not automatically translate to clear business value. And right now, boards are done waiting for them to.
Here is the uncomfortable truth most data leaders will not say out loud: The problem is almost never the AI. It is the data behind it. Most enterprises have up to 90% of their data locked away in unstructured silos.
They lack a unified governance layer. And without that foundation, there is no clear path from pilot to production. You cannot build a reliable AI system on an unreliable data foundation.
Every organization that skipped that step is finding out the hard way right now. Here is the framework I use when a data leader tells me their AI initiative is stalling: Level 1: The pilot works in demos. Data is curated, clean, controlled.
Nobody asks hard questions yet. Level 2: The pilot hits production. Real data.
Real edge cases. Real inconsistencies. The cracks appear.
Level 3: Leadership asks for ROI. The team cannot answer clearly because nobody defined what success looked like before they started. Level 4: The initiative gets defunded.
Not because AI failed. Because the foundation was never built. The gap between AI experimentation and AI outcomes is almost always a data strategy and governance gap.
The organizations pulling ahead in 2026 are not the ones with the most impressive models. They are the ones who did the unglamorous work first. Governed data.
Defined metrics. Clear ownership. That work does not get standing ovations in board meetings.
But it is what separates the teams delivering results from the ones writing post-mortems. If your AI initiative is stalling, do not look at the model. Look at the foundation underneath it.
Where does your organization sit on this right now? I would genuinely like to know. I am advising companies on AI and data strategy and exploring my next executive role.
If you are building something in this space, DMs are open.