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How insurers are embracing customer-facing applications for GenAI

Authors

  • Gaston Messineo

    Principal, Strategy and Execution, EY-Parthenon, Ernst & Young LLP

  • Sameer Gupta

    EY Americas Financial Services AI Leader

  • Jared Kwait

    EY-Parthenon Senior Director, Strategy and Execution, Ernst & Young LLP

Contributors

8 minute read 17 Sep 2025
Related topics
Financial services
Insurance

GenAI survey shows insurers are shifting focus from back office to front office for GenAI.

In brief

  • Insurers expect to see average cost savings of more than 20% over the next two years with AI-related productivity enhancements.

  • Enhanced marketing, personalization and customized services headline front-office insurance use cases for GenAI.

  • Predictive analytics continue to enhance insurer’s ability to manage risk and enhance revenue.

Artificial intelligence (AI) has the potential to transform productivity, workflows and operational models across the insurance industry. While industry leaders have embraced and used AI for decades, generative AI (GenAI) and agentic AI are now poised to reduce risks and drive new growth in the sector. GenAI can enhance productivity through improvements in policy review and customer service, while agentic AI can orchestrate full business processes. Together, these technologies will help insurers streamline operations, better serve customers and accelerate growth. To further explore the impact of GenAI, an EY team conducted a market research study to understand where insurers are today in their AI journeys and where they are heading across use cases, governance and value realization.

GenAI revolutionizes insurance: A shift from back-office to front-office applications

Our research uncovered an emerging shift from back-office to front-office use cases over the past two surveys (2024-2025). This indicates an increased level of confidence in the technology and a willingness to test more customer-facing applications. With enhanced controls in place for monitoring, insurers have become more comfortable with data security and with managing risks associated with AI. They’ve moved from testing data aggregation and risk analysis to experimenting with customer service chatbots, copilots, and automated onboarding for new employees and new clients.

Prioritization of investment across client-facing functions


Enhanced marketing and personalized outreach

By understanding customer preferences and behaviors, insurance companies can tailor their offerings to meet individual needs, improving engagement and conversion rates. These enhanced marketing activities include direct-to-consumer personalization of messaging, customer identification, custom landing pages and push notifications. Overall, 56% of insurers are prioritizing these front-office use cases. An even higher percentage — 63% — of property and casualty (P&C) carriers, life and annuity (L&A) carriers, group benefits providers, and brokers are making similar investments.

Customized service and human-like chatbots

L&A firms are prioritizing chatbots with a focus on enhanced underwriting and personalized product recommendations. Across all insurers, 68% are investing in chatbots to drive cross-selling and value-added products. L&A firms are leading this trend, with 76% focusing their investments on functionalities to add annuities to individual life policies or product bundling with P&C and life insurance.

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GenAI drives investment in predictive analytics for insurance: A focus on underwriting and claims

 

Insurers are investing heavily in predictive analytics, with 74% of firms identifying it as a key area for underwriting and claims functions. Commercial P&C firms are leading the charge at 78%. This shift reflects a significant response to insights from a 2024 survey, where over 50% of insurers recognized predictive risk assessments as a future priority. By leveraging AI, insurers can enhance their ability to forecast future weather-related claims and accidents, ultimately improving their risk management strategies and providing more accurate pricing in an increasingly volatile environment. This is especially true in P&C insurance, where the rising frequency of catastrophic weather events underscores the need for better risk pricing. As a result, predictive risk assessments have become a critical focus.

 

GenAI enhances insurance operations: Focus on real-time fraud detection and efficiency

 

Insurers are increasingly prioritizing the use of GenAI to enhance operational efficiency and combat fraud. Our study indicates that real-time fraud detection is a significant focus, with 78% of insurers investing in this capability to safeguard against fraudulent claims. Additionally, 68% of firms are adopting automated data entry, which streamlines processes and reduces manual errors. Enhanced data aggregation, utilized by 49% of insurers, allows for better insights and decision-making by consolidating information from various sources.

Download the GenAI in insurance survey highlights

PDF (1 MB)

GenAI governance in insurance: Centralized models and strategic oversight for effective implementation

Insurers are recognizing the importance of robust governance structures for their GenAI initiatives, leading to a shift toward centralized and hybrid models. This trend reflects a desire for more cohesive oversight and strategic alignment in AI deployment. Nearly 80% of insurers have established that the head of AI will report directly to the chief technology, information or data officer, so that AI strategies are integrated with overall business objectives. To support the establishment of dedicated GenAI teams, 68% of insurers have earmarked specific portions of their IT and tech budgets for these initiatives. Since 2024, 77% of insurers have allocated up to 10% of their budget to GenAI, with expectations to increase this to up to 15% over the next two years. From a policy and guardrails perspective, 79% of insurers are looking for both monitoring and auditing of AI data, along with clear policies regarding data privacy and security to help ensure the accuracy of results and fairness of outcomes.

Realizing the value of GenAI in insurance

Most insurers have reported up to 10% in cost savings, primarily due to productivity enhancements facilitated by AI technologies. Furthermore, 47% of insurers have experienced revenue uplift within core insurance functions, largely attributed to improved customer experiences. These findings highlight the significant impact of AI in enhancing operations and customer satisfaction within the insurance industry.

of insurers have experienced revenue uplift within core insurance functions, largely attributed to improved customer experiences.

Q. “What degree of cost savings did Generative AI produce over the past 1-2 years across the following functions?” [n=100]


Looking forward, insurers are optimistic about the value they expect to achieve from AI in the coming years, with 55% anticipating cost savings of 11% to 20%. As GenAI continues to evolve, it is projected that 11% to 15% of the workforce may be impacted over the next one to two years, reflecting a shift toward greater efficiency. A significant proportion of insurers expect to realize up to 20% in benefits, including efficiencies and cost savings, within the same time frame. This optimism is further underscored by the fact that an overwhelming majority of insurers — 97% of commercial P&C, 97% of L&A and 94% of personal P&C — believe that productivity enhancements will remain a key driver for GenAI implementation. Overall, the majority of carriers foresees their average cost savings increasing from below 10% to between 11% to 20% over the next two years, highlighting a strong commitment to leveraging AI for transformative value.

Q. “What degree of cost savings do you expect Generative AI produce over the next 1-2 years across the following functions?” [n=100] 


How EY-Parthenon can help

Agentic AI in insurance – The next challenge

 

Agentic AI is top of mind across the industry with nearly half of insurers identifying agentic AI use cases currently in the early stages of testing and production. A significant 69% of insurers are focusing on leveraging agentic AI for risk assessment and mitigation, while 60% prioritize customer service and engagement, and 48% aim to enhance regulatory and compliance decisions. There is a notable shift toward autonomous agentic workflows, allowing these AI systems to operate independently across various use cases within the value chain, such as agent “bots” that can perform multiple functions rather than being limited to specific tasks. Additionally, neuro-symbolic AI is being utilized to generate precise, transparent and predictable outputs. Looking forward, 12% of insurers are concentrating on use cases that address over 50% of core insurance functions, such as underwriting and claims processing, rather than solely focusing on back-office operations. This trend indicates a strategic move toward integrating agentic AI more deeply into the core functions of the insurance industry.

 

Early progress and optimism

  • 53% of firms are in the early stages of integrating agentic AI into their workflows
  • 27% of firms indicate that agentic AI is partially integrated
  • 57% expect to have AI use cases fully built and integrated in one to two years

The way forward with GenAI in insurance

 

Based on this research and peer insights, insurance leaders should focus their efforts in five critical activities to advance and keep pace with evolving trends in AI. These should serve both as a starting point and strategic direction.


Following people contributed to this article:

  • Will Laud - Manager, Ernst & Young LLP
  • Owen Dillon - Staff, Ernst & Young LLP
  • Jacob Andrews - Staff, Ernst & Young LLP

Summary 

Insurance leaders are seeing cost savings through AI productivity enhancements and improved risk management from AI predictive analytics. As they turn their attention to the front office, they intend to leverage lessons learned and increased confidence with AI to enhance customer experiences and seek growth opportunities through automating cross-sell and personalization opportunities.

About this article

Authors

  • Gaston Messineo
    Principal, Strategy and Execution, EY-Parthenon, Ernst & Young LLP
  • Sameer Gupta
    EY Americas Financial Services AI Leader
  • Jared Kwait
    EY-Parthenon Senior Director, Strategy and Execution, Ernst & Young LLP

Contributors

Related topics
Financial services
Insurance

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