One mistake software companies often make in their AI journeys is employing discrete data scientists who work in silos to build models as proofs of concepts rather than solve real business problems. This way of working has shown that many software and digital–native companies are missing genuine business value when doing this. And that AI has a lot to offer.
In a successful AI journey, organizations create AI teams to address specific business problems. This requires including both technical and domain experts within these teams. While the technical experts will take on the brunt of model creation, they need the field knowledge of domain experts to define precise business challenges and identify the data most important to finding a solution.
