AI’s Evolution from Generative to Agentic Intelligence
In this Fincorporated Interview, Ronak Doshi from Everest Group joins Roshan Shetty to discuss the evolution and adoption of AI, particularly generative AI, and its impact across industries. Their conversation covers key areas, including:
Evolution and Adoption of AI
- The progression of AI spans from the early stages to the emergence of generative and agentic AI.
- Enterprise investments bring generative AI use cases to production, particularly in contact centers, customer experience, risk and compliance, marketing, and IT.
Industry-Specific Applications
- AI plays a crucial role in retail. Businesses can extend this strategy to financial services, leveraging AI to enhance personalization and product offerings.
- AI has the potential to transform financial services by enabling headless experiences through chat or voice interfaces and streamlining processes like case logging and insurance claims.
Challenges and Considerations
- Despite the potential, AI's adoption in the BFSI (Banking, Financial Services, and Insurance) industry remains limited, with less than 10% creating material changes.
- There is a need for a compliance-by-design framework to address regulatory concerns from the outset.
- The rise of smaller, more cost-efficient language models drives broader adoption of generative AI solutions, but organizations must navigate scalability and integration challenges.
Future Outlook
- Innovation centers, like Tech Mahindra's Maker’s Lab , help businesses choose the right AI models and solutions, optimize costs, and prioritize implementation.
- As AI and generative AI applications evolve alongside regulatory norms, businesses will adopt them more seamlessly and cost-effectively.