Business and IT leaders alike know AI’s biggest hurdle is scalability. Across industries, organizations aren’t always positioned to start AI programs off on the right foot without clear results to showcase and earn the business buy-in needed to progress.
This age-old issue is heightened by another common mistake enterprises make — failing to simultaneously produce pilots with short-term wins while also scaling these AI projects beyond first phases and minimum viable products (MVPs). It may seem like a Catch-22.
