TCS’ CEO Vinod Kumar spoke about the challenges in the adoption of AI and generative AI technologies in enterprises. He emphasized the need for a cohesive AI strategy that balances value, complexity, and risk. He also highlighted the importance of getting multiple teams together to create a common vision. However, he noted that a small percentage of use cases are actually going into production due to a lack of engineering to a company’s needs or the absence of organizational changes to support AI deployment.
TCS has been investing in R&D, with a consistent 1.2% of its annual net revenue spent on research and development. While there is no exponential jump in this figure expected, TCS is using its R&D expenditure to develop solutions that make AI more palatable to enterprises. Vinod Kumar identified six key fields that define technical innovation demand, including sensing technologies, quantum and neuromorphic computing, data management and security, 6G technologies, AI knowledge management, and new human-computer interfaces. He also highlighted the need for AI models to be more adaptive, predictable, and explainable, and the importance of knowing when not to use generative AI.