Videos
AI, Retirement Readiness, and Responsible Transformation
Insights
- Rising longevity, healthcare costs, and financial complexity are increasing demand for better retirement planning and guidance.
- AI can improve participant experiences, planning outcomes, and operational efficiency, but data readiness and governance remain critical barriers.
- Successful AI adoption requires clear business outcomes, human oversight, workforce AI literacy, and responsible deployment practices.
Senthil Velumani, Portfolio Head, Insurance at Infosys explores the growing challenges individuals face as they take on greater responsibility for securing their financial futures amid rising costs and increasing complexity. He explains how insurers and retirement providers are using AI to enhance participant experiences, improve planning capabilities, and deliver more personalized support. The discussion highlights the importance of moving beyond AI experimentation by focusing on business outcomes, redesigning processes around AI, and selecting the right combination of automation, generative AI, and agentic AI. Senthil also emphasizes that trust, workforce preparedness, and strong governance frameworks will be essential to scaling AI while managing reputational and regulatory risks.
Senthil Velumani:
Saving for retirement and financial security at the time of retirement is a great source of anxiety for Americans. There are a few factors in play here. The first is there is increased longevity and an escalating cost, cost of living, healthcare cost, and long-term care cost. The second is the shifting of the burden for saving from the employers or the government into the individuals. And then the third factor is they are having to prioritize the current cost over the savings for retirement, paying for the mortgage, paying for the college kids, saving up for a big event, all of which are higher priority than saving for retirement. So they are tending to put off retirement savings much longer. And finally, the rules around retirement saving are fairly complex. There are many instruments available, and there are different tax codes and regulations that they need to carefully consider. All of these are sources of anxiety. The retirement companies and the financial planners have a responsibility to help educate the individuals, help them learn and understand, and save towards their retirements.
The leaders in the insurance and retirement sector are approaching AI with a lot of optimism as well as with caution. On one hand, the AI use cases are presenting great potential. There are plenty of opportunities around planning experience, participant experience, and hardship withdrawal that make a great case for AI adoption. On the other hand, they are also pulling back as a result of concerns around having the right data, they are not quite organized with the right data. The second concern is responsible AI application and governance, and they are also concerned about some of the compliance risks that come along with AI adoption. They are struggling to move their POCs into production-grade AI applications. This requires a holistic approach to solve the problem.
Start with the business outcome that you want to achieve. Re-imagine your process using a domain-driven approach with AI at the center of it to ensure you have the right process design. And then the third is to carefully pick the right application of GenAI. In some cases you may require deterministic automation; in some cases it is robotic automation; in other cases you may require GenAI; and in some other cases it could be agentic AI. Picking the right application is important for successful AI adoption. And they need to carefully insert the human in the loop to ensure that there are guardrails protecting the application of AI for real production use. One thing is clear, the AI use cases are real and the value and benefits are material.
The biggest opportunities in 2026 are around the experience design. We talked about planning experience, participant experience. The second is around participant service operations, hardship withdrawal, loan processing presents great opportunity. And finally, compliance presents a great opportunity for AI adoption. The process of ensuring that you have a higher compliance as well as reducing your operating cost or real benefits that can be accomplished in 2026.
