Most AI programs fail in the same place. Not the model. Not the budget. The rollout.
A company buys the licenses, runs a pilot with enthusiasts, declares victory, and six months later wonders why usage flatlined. The technology worked. Nobody changed.
The gap is measurable. Accenture found that 94% of workers say they’re ready to learn generative AI, while only 5% of organizations are training at scale. (Accenture) The willingness is there. The program isn’t.
I’ve watched this cycle enough times to name the mistake plainly. Adoption gets treated as communications. A launch email, a training video, a champions network that meets once a quarter. That isn’t adoption. Those are announcements.
Adoption is the strategy itself. It means designing the rollout around how people already work, training by discipline instead of by tool, and measuring whether behavior changed instead of whether licenses were assigned. At Spin Master we trained the whole organization twice over: once on the foundations everyone needed, once on the workflows specific to each discipline. Designers, manufacturers, marketers, sellers. Different jobs, different training.
The uncomfortable truth for leaders: the AI is the easy part. The org chart is the hard part. Budget accordingly.