Generative AI

But adopting generative AI models at large enterprise scale poses challenges. Companies must address the potential security issues arising from training an AI model with sensitive data. Furthermore, while there may be attractions to outsourcing some tasks to an AI, many are uncomfortable with having chatbots doing the work of professionals. And while a growing number of tasks can be outsourced to chatbots, human supervision is still required.  

Our client wanted an expert assessment of feasible use cases for corporate enterprise over the next five years. The core engagement was centered on landscaping and feasibility mapping to ensure our client could move forward with their priorities.

We assembled an expert team from industry and academia to map out six generative AI technology segments, technical overviews, associated use cases, technology effectiveness, along with future trends for areas such as enterprise departments, IT, legal, marketing and R&D.

These were then assessed against our client’s key enterprise areas to determine areas of best fit. Our experts assessed the feasibility of 31 use cases harnessing emerging generative AI products, before streamlining this long list to 15 of the use cases with the lowest barriers to adoption.  

Our analysis provided an objective assessment of the use cases with the most potential, allowing our client the chance to roadmap the best route for adopting solutions into their infrastructure.