The insurance industry and Asian insurers, in particular, are experiencing a monumental shift driven by artificial intelligence (AI), with McKinsey projecting a potential annual value add of up to $1.1 trillion globally. This substantial increase could stem from advancements in pricing, underwriting, and promotion technology ($400 billion), coupled with AI-empowered customer service and personalized offerings ($300 billion). However, the insurer of the future faces significant hurdles in fully leveraging AI, particularly in Asia, where traditional organizational structures and limited tech and data resources pose challenges.
The transformative power of AI
The transformative power of AI in the insurance industry is yet to be fully realized, despite many large insurers embarking on the path to AI-enabled personalization at scale. Cross-functional investment in AI is poised to be a game-changer and a potential source of competitive advantage.
McKinsey Global Institute’s survey shows AI adoption has more than doubled in the past five years, with the most significant gains observed in entities that utilize advanced AI practices, cloud technologies, and efficient AI spending.
The critical challenge for insurers lies in identifying the optimal path from their current state to an AI-mature, enterprise-wide integrated future. McKinsey’s AI maturity assessment model provides an outline and roadmap for Asian insurers to assess their readiness for AI and transition into AI-powered insurers of the future.
The foundation of McKinsey’s framework lies in a layered approach to AI investment across four areas: engagement, AI-powered decision-making, core tech and data, and organization and operations. These interdependent layers encompass front-, middle-, and back-office functions, creating a robust structure that benefits both internal and external stakeholders.
Global companies such as Google, Netflix, Tencent, and Uber, setting the benchmarks for AI maturity and capacity, illustrate the potential gains that insurers could realize by holistically integrating AI across their organizations. For instance, Netflix’s AI tools enable personalized, digital-ready engagement and distribution channels, while Uber’s AI-powered decision-making layer enhances complex decision-making with predictive models.
The need for a modernized core tech and data layer
A modernized core tech and data layer, as demonstrated by Tencent’s WeChat app, delivers high-quality, real-time data for advanced decision-making and seamless customer experiences. It enables integration with multiple third-party platforms for data and intelligence. Lastly, Google exemplifies the organization and operating model layer, enabling the innovation, agility, and flexibility required to harness AI-powered capabilities.
The evolution of the insurance industry depends on integrating such AI advances. In the short term, organizational shifts will help insurers prepare for AI-enabled improvements. In the long term, these shifts will equip the insurance industry to realize AI-enabled gains witnessed in other sectors. However, as AI’s potential to revolutionize the industry grows, so do the challenges related to data privacy, inherent biases, interpretability, and more. Thus, strong risk management practices and proven models remain crucial to successful AI implementation and scale.