Why so many AI pilots never ship
Across the engagements we see, the majority of stalled AI initiatives fail for organizational reasons, not technical ones: unclear ownership, no defined success metric, or a pilot scoped around a demo rather than a real workflow.
What the companies seeing ROI do differently
They start with a narrow, measurable workflow instead of a broad platform. They assign a single accountable owner. And critically, they budget for the unglamorous work — data pipelines, evaluation, monitoring — not just the model.
What changes heading into next year
We expect the gap to widen further between companies treating AI as core infrastructure versus a bolt-on feature. The former are building evaluation and data capabilities now that compound; the latter will find themselves re-platforming in 18 months.
Adrian Kessler
Chief Executive Officer