Identifying and prioritizing areas that incur maximum costs or poses a need for improved efficiency/automation. Map this to gen AI relevance and business impact. Collect data – this will serve as the base for intelligent solution mapping. All and any decision regarding evaluating the need for gen AI, is mostly data driven.

Define what kind of productivity boost you are seeking from generative AI offerings. Is it mere automation to reduce manual, and repetitive tasks? Or does your team need to reduce errors in data management? Data optimization is a broad spectrum. Would you benefit from predictive analytics or personalized data? Work with artificial intelligence experts in the field to define it.

BFSI businesses have benefited from predictive analytics in mitigating investment risks. The telecom industry has benefited from chatbots with personalized query management with issue resolution suggestions.