Council Post: Roundtable Discussion on Building a Team for Generative AI

In today's rapidly evolving landscape of artificial intelligence, harnessing the power of generative AI has become a game-changer for organizations seeking to drive innovation and unlock new possibilities. Building a highly skilled team that can effectively navigate and leverage the potential of generative AI is crucial for staying ahead in this competitive arena. Such a team requires a unique blend of expertise, combining technical prowess in AI algorithms, data science, and machine learning with a deep understanding of the specific domain or industry. With the right talent in place, organizations can unleash the creative potential of generative AI, pushing the boundaries of what is possible and revolutionizing the way we approach problem-solving, creativity, and intelligent decision-making.

The AIM Leaders Council hosted a roundtable session on “Building a team for Generative AI” during MachineCon, 2023 with leaders: Anish Agarwal, Global Head of Analytics at Dr. Reddy’s Laboratories, Swati Jain, Vice President, Analytics at ExlService, Purnesh Gali, Cofounder and CEO at Actalyst, Narasimha Medeme, VP, Head Data Science at MakeMyTrip, Shirsha Ray Chaudhuri, Director of Engineering - TR Labs at Thomson Reuters, Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion, Raj Bhatt, CEO at Knowledge Foundry and Deepika Kaushal, Head-Everyday AI & Digital analytics at Piramal Capital & Housing Finance. 

Building High-Performing Teams for Generative AI: Challenges and Considerations

One of the biggest challenges faced by organisations today is to set-up a team to build and work on generative AI use cases. This problem is multi-fold. The first challenge is availability of the right skillset. Large Language models, which are the back-bone of generative AI have gained prominence in the past few months. Today, companies float job specs to hire experts in LLMs with several years of experience in LLMs which is not pragmatic. As opposed to expecting applications from seasoned professionals, it would be prudent for companies to up-skill the existing Data Scientists given they already have a good sense of business knowledge..