In many cases, they’re guessing where to use AI based on the availability of data.

companies have a hard time seeing the value in their data scientists.

Choose a provider whose focus is on problem-solving and considers techniques that fit the bill.

technical advisory model.

use the consultant as a coach or an architect who provides guidance in implementing the AI solution.

working prototype model.

have the consultant build a solid working prototype, and then your engineering team further develops it into an MVP.

Because of the complexity of AI, you should never go from an idea directly to implementation.

ROAI tracks improvement over a baseline measurement. For example, what are the time savings after integrating an AI-driven automation? Or how many more tasks can you complete in an hour with the help of your AI assistant?