already stressing staff, skills, and the readiness of in-house and third-party AI products and services. Without effectivestrategic plans for AI, organizations risk wasting money, falling short in performance and falling behind their business rivals.“Pursue small-scale plans likely to deliver small-scale payoffs that will offer lessons for larger implementations”

“AI is just starting to become useful to organizations but many will find that AI faces the usual obstacles to progress of any unproven and unfamiliar technology,” says Whit Andrews, vice president and distinguished analyst at Gartner. “However, early AI projects offer valuable lessons and perspectives for enterprise architecture and technology innovation leaders embarking on pilots and more formal AI efforts.”

So what lessons can we learn from these early AI pioneers?

Aim for fairly “soft” outcomes, such as improvements to processes, customer satisfaction, products and financial benchmarking

When Gartner Research Circle respondents were asked what lessons they had learned from early AI projects, many urged others not to fall into the trap of seeking only immediate monetary gains. They advised instead to aim initially for less quantifiable benefits from which financial gains would eventually arise. These might come from “softer” or more “open” outcomes, such as improved marketing or brand identity, or they could lead to wider benefits altogether.

Of course, some companies need to demonstrate financial benefit in order to initiate an AI project. In such cases, it makes sense to pursue small-scale plans likely to deliver small-scale payoffs that will offer lessons for larger implementations.