How insurers can quantify EBITDA uplift from AI investment

Artificial intelligence (AI) is already redefining the insurance landscape by transforming how insurers operate and how customers interact with insurance services. From underwriting and claims processing to customer service and fraud detection, AI is revolutionising every aspect of the industry.

As AI experiments spring up across their institutions, insurance executives are seeing a lot of activity and distraction – but very little sustained, tangible value. Insurance teams are finding considerable immediate potential for AI and generative AI (GenAI) to optimise costs and uplift productivity. But investment is sporadic and poorly structured. Efforts are tactical – not strategic.

AI can solve many operational problems for insurers in a value-accretive manner. But not all of these investments yield a worthwhile return on investment – especially if they are not deployed at scale. There’s little value in using AI to deliver efficiencies to just one person or one team.

Executives are also concerned about the consequences of the undisciplined dissemination of AI and GenAI. What if these intelligent tools are being rolled out in a way that will add cost over time? How can they be prevented from creating uncontrolled (and unquantifiable) data quality, privacy or cyber risks?

High-value AI investment opportunities for insurers

For most insurers, the process reveals that the biggest potential for immediate value creation lies in cost optimisation across risk and compliance. For example, we see a lot of value embedding GenAI in compliance functions to allow full population testing and to move from post-event detective controls towards real-time preventative controls. The more accurate identification and prioritisation of risk allows compliance teams to effectively deploy existing human capital to investigate the areas of greatest risk.

Equally, GenAI can speed up the time it takes to assess insurance claims and review outcomes – a huge issue when the people involved can be quite distressed.

Embedding AI within first- and second-line risk functions takes compliance to another level. Teams can understand the value of risk sitting outside tolerance levels. Managers can make sophisticated, quantified trade-off decisions: “Do I deploy GenAI-enabled risk-based solutions, keeping the same quantum at risk with half the human capital – or could I further reduce residual risk with the same amount of human capital?”

An expedited path to determine net ROI from AI and GenAI

The EY.ai Insurance Value Accelerator helps insurers to rapidly prioritise AI value cases and define a pragmatic roadmap, so executives can focus investment on what matters most to stay ahead of the curve. It also quantifies the financial commitment required for sustainable and scalable AI adoption – including uplifting organisational readiness.