Trust in AI: A Growing Opportunity for Insurers, But Challenges Remain
Insurance companies are eager to embrace artificial intelligence, but key hurdles persist, according to a recent report from global professional services firm KPMG. While insurers anticipate significant returns on their AI investments, concerns regarding trust and the need for clear financial results are slowing broader adoption.
The KPMG study revealed that a substantial majority of respondents—66%—expect a moderate to very high return on their AI investments, with all participants agreeing that companies actively utilizing AI stand to gain a competitive edge. Furthermore, spending on AI is poised to increase, as all surveyed firms are planning to dedicate a larger portion of their budgets to AI initiatives. Among these, 66% indicated they plan to allocate up to 20% of their global budgets for AI, while the remaining 34% intend to invest more than 20%.
Despite the optimistic financial outlook, a significant trust gap presents a considerable challenge. The study stated that 46% of industry leaders expressed reservations about the reliability of AI, with only 25% reporting full trust in AI systems within their organizations. However, a considerable 82% of respondents recognized the need for strong frameworks, policies, and processes to ensure both compliance with regulatory requirements and responsible AI implementation.
AI’s Impact on Insurance Processes
The study also explored the multifaceted ways AI is reshaping insurance processes across several key areas:
- Underwriting: AI is streamlining risk assessment through automated risk segmentation, incorporating electronic health records for more precise evaluations, and utilizing predictive analytics to refine policy pricing.
- Life Insurance: Life insurers are leveraging wearable data and wellness tracking to personalize policy pricing and incentivize healthy behaviors, encouraging policyholders to adopt healthier lifestyles.
- Claims Automation: AI is enhancing claims processing through fraud detection, analysis of documents such as death certificates, and the use of machine learning to expedite payouts.
- Longevity Modeling and Compliance: AI aids insurers in assessing life expectancy, detecting early disease onset, and optimizing risk stratification, which enables insurers to refine pricing and payout structures.
Presently, leadership goals for AI adoption are centered more on enhancing operational efficiency rather than achieving broader strategic value. To guide insurers through the AI adoption process, KPMG has identified three critical phases:
The Three Phases of AI Value
- Enable: This initial phase emphasizes creating a robust AI foundation. Key activities include appointing responsible executives, developing comprehensive AI strategies, identifying the most promising AI use cases, enhancing AI literacy across the organization, and ensuring full regulatory compliance. This phase also encompasses launching pilot programs, leveraging cloud platforms, and utilizing readily available pretrained models with minimal customization.
- Embed: This phase focuses on integrating AI into the operational workflows of the business. A crucial element of this phase is the involvement of a senior leader tasked with spearheading enterprise-wide workforce redesign, re-skilling initiatives, and change management strategies. The aim is to seamlessly integrate AI into the company’s operating models while diligently addressing ethical, trust, and security concerns.
- Evolve: This final phase targets the transformation of business models and the development of entirely new ecosystems through the strategic application of AI alongside emerging technologies such as quantum computing and blockchain. The ultimate objective is to tackle large-scale challenges, augment enterprise value, and give paramount importance to ethics, trust, and security considerations. Workforce training is also deemed essential to cultivating continuous innovation.
