IBM: Insurers Navigate Choppy Waters of Gen AI Adoption

Insurance executives are split on whether generative artificial intelligence (Gen AI) presents more risk or opportunity, according to new research from IBM.

The study, conducted by IBM's Institute for Business Value, surveyed 1,000 global insurance and bancassurance executives and 4,700 insured customers.

Gen AI, a subset of artificial intelligence capable of creating new content based on patterns in existing data, is rapidly gaining traction in the insurance sector. However, its adoption is not without challenges.

Insurers Rush to Adopt Gen AI Amid Competition Concerns

Despite the divided opinion on Gen AI's implications, 77% of industry executives believe rapid adoption is necessary to maintain competitiveness. 

This urgency is reflected in projected investment figures, with insurers expected to increase Gen AI spending by over 300% from 2023 to 2025.

Early adopters report tangible benefits from implementing Gen AI in customer-facing systems. These insurers have seen a 14% higher retention rate and a 48% higher Net Promoter Score compared to non-users.

However, the research reveals a significant disconnect between insurers' Gen AI priorities and customer expectations, which could impact the effectiveness of these investments.

Misalignment Between Insurer Focus and Customer Priorities

While insurance executives are prioritising the development of AI assistants (such as chatbots and virtual assistants) and augmented customer service, customers are more interested in Gen AI applications for personalised pricing, promotions and tailored products.

This misalignment suggests that insurers may need to reassess their Gen AI strategies to better align with customer preferences and potentially gain a competitive edge.

The study also highlights divergent concerns regarding Gen AI. Customers express worries about data privacy and the potential for AI-generated inaccuracies, issues that insurers must address to build trust in their Gen AI implementations.

Legacy Systems and Technical Debt Hamper Adoption

The insurance industry's aging technology infrastructure presents a significant hurdle to Gen AI adoption. Legacy core systems, which form the backbone of many insurers' operations, are often ill-equipped to integrate with new AI capabilities.

These outdated systems also limit the availability of high-quality training data for large language models, which are essential for effective Gen AI applications.

The impact of this technical debt is substantial, with 52% of executives citing data constraints as a factor slowing the speed to market of new products. 

To overcome these challenges, insurers are exploring hybrid-by-design architectures that can operate within existing complex systems while gradually reducing technical debt.

Operating Model Choices Impact Gen AI Success

As insurers invest in AI and customer data analytics, they face critical decisions about the most effective operating model for Gen AI development and deployment. 

The research indicates that organisations with decentralised AI operating models are outperforming their peers across multiple metrics, including speed to market and customer retention.

This finding suggests that insurers may benefit from democratising AI decision-making across their organisations while maintaining centralised governance and implementation structures.

The report states: “Democratising AI decision-making across the enterprise while retaining central governance and implementation is essential to generating real Gen AI value.”

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