Dec 16, 2024

Are AI and Insurance ready for 2025?

Synopsis

Insurance has undergone a transformation. The industry has faced demographic changes, rapidly evolving customer expectations, advancements in digital technology and analytics, and the challenge of maintaining a continued focus on innovative risk prevention. It is becoming increasingly important for carriers to elevate technological and operational excellence, innovate product solutions, and broaden the insurance value proposition—making the insurance safety net more reliable, accessible, and resilient.

Over the past decade, particularly in the last few years, it has been an exhilarating and challenging time for an industry that is traditionally risk-averse and slow to change. As we look to 2025 and beyond, insurers must harness the momentum they’ve gained to meet a host of new difficulties. While turbulence in the market is expected to prevail in coming years, insurers cannot rely on continually rising premiums, or a continuation of today’s hard cycle, to drive premium growth. That’s why it’s a critical time for them to reassess how they will capture growth profitably as they navigate this shifting landscape.

McKinsey’s 2025 Global Insurance study cites that an insurer’s operational strategies account for 60% of its overall performance, leaving just 40% influenced by the specific lines of business it writes. Leading insurers achieve loss ratios that are, on average, six percentage points better than their competitors. In addition, they are nearly twice as likely to have prioritized significant investments in their underwriting operations compared to those in the bottom quartile.

McKinsey also states that while leveraging technology to enhance underwriting capabilities is not a new concept, recent advancements have significantly accelerated progress and broadened the possibilities, even as insurers navigate the challenges posed by legacy systems and inefficient workflows. Top-performing insurers are reimagining their end-to-end processes by utilizing diverse data sources, generative AI, and traditional AI and machine learning technologies. These tools enable them to build distinctive decision-making frameworks that improve both efficiency and scalability. To remain competitive in their chosen markets, insurers must prioritize substantial investments in underwriting innovation as a critical component of their operational strategies.

Last year, insurers were largely looking for education—especially around the heavily hyped and emerging generative AI. Now, carriers are looking to see how GenAI is operationalized—and circling back to other forms of artificial intelligence that will work in concert to produce the technology infrastructure of the future.

Based on research from various industry, in 2025, insurance organizations will focus on developing holistic AI-based products and services, ecosystem value proposition and orchestration to achieve revenue growth or cost savings while going past the challenges of product-market fit, workforce, and change.

Getting Ready to Realize True Potential of AI

The Forrester report “Predictions 2025: Insurance” indicates that insurers are expected to pass rising claims expenses on to customers next year, a trend likely to enhance profitability and drive increased technology investments in innovation, data, artificial intelligence (AI), and automation. Insurers have been working with AI tools for several years. However, until very recently, many insurance leaders may not have seen the need to focus on strategically embedding AI throughout the organization.

With the rise of various publicly accessible generative AI tools over the past two years, AI is experiencing what many are calling its “iPhone moment.” According to a June 2024 survey conducted by the Deloitte Center for Financial Services, 76% of 200 surveyed U.S insurance executives reported that their organizations have already integrated generative AI into at least one business function. While many insurers remain in the proof-of-concept stage, some are starting to integrate gen AI into prioritized areas like claims and customer service. These use cases may provide better risk-reward and scalability opportunities in the short term, both from a regulatory perspective and acceptance within insurance organizations. Insurers are deploying generative AI in commercial lines to automate algorithmic underwriting, implement chatbots that embed institutional know-how in underwriting workflows, improve the underwriting submission process, and streamline market intelligence to enable more efficient portfolio management.

AI’s promise of transforming underwriting, claims, and customer experience remains untapped, and only a tiny fraction of insurers will harness its full potential by 2025. Tech-driven product innovations such as embedded insurance and usage-based insurance may yield faster results, but long-term AI gains remain on the horizon. Despite the excitement around AI, fewer than 5% of insurers are expected to see direct, tangible gains next year from the technology. Over the next few years, realizing efficiencies and enhancing experience (for both customers and employees) could turn out to be more important than measuring direct business growth.

Getting a strong foundation for AI

Before implementing additional gen AI use cases, carriers must be able to create an efficient end-to-end operating model, scale it, and automate it to maximize flexibility as they adapt operations and address future challenges. This will matter even more if rates soften. Further, insurers may not be able to realize business value without accurate underlying data to train and feed the models.

While insurers have prioritized building the data foundation over the last decade to enable analytics and digital capabilities, the focus is now on enabling their data ecosystems to be able to support and scale AI. A significant portion of insurers’ current efforts is still focused on driving operational efficiency as opposed to creating new value. Insurers need to pivot to leveraging digital investments for differentiating products, solutions, partnerships, and engagement models.

Many insurers will continue to invest in AI for internal automation, but the true potential of AI, such as improving underwriting or claims accuracy, will remain elusive for most. Insurance tech teams should focus on provisioning high-quality data, partnering with vendors that can provide AI skills or applications, and adopting AI for specific use cases. These steps will still leave most insurers looking for direct gains from AI.

Capitalizing on the full potential of AI requires organizations to implement processes and adopt a mindset that encourage growth with AI. There needs to be support systems to nurture a culture that promotes curiosity, design thinking practices, and co-creation. Processes that reward risk taking and experimentation and data-driven decisions need to become standard. It’s important to establish an agile culture that fosters internal and external collaboration. Organizations need to invest in capabilities and culture that truly adopt a digital mindset. Insurance companies shouldn’t chase AI to replace human decision-making. They should race to capture and replicate the expertise of their most experienced underwriters, claims adjusters, and risk assessors before it walks out the door.

It is essential to simplify and harmonize business processes. Take the time to document, streamline and standardize at least 80% of a process, ensuring that each step is well-defined and easy to follow. By developing clear, repeatable procedures, organizations can maximize the benefits derived from gen AI.

Conclusion

To be leading players in the future of the industry and capture profitable growth, insurers must focus on establishing distinct capabilities and double down on how they play in addition to where they play. Doing so requires establishing clear and targeted strategies, modernizing their underwriting capabilities, and optimizing the efficiency of their operations. In an industry in which winners keep winning, inflection points such as the current one present the chance for insurers to separate from the pack.

The promise of AI is real, but achieving long-term success requires patience and persistence. Avoid being swayed by promises of immediate, dramatic gains. Instead, create a streamlined path for success across your organization. You need to invest the time and resources to clearly define the problem, curate the ideal environment for success and then implement a tailored AI solution.

2025 is a year for insurers to streamline business processes with proven AI use cases and solutions, strengthen the data foundation for advanced GenAI, and establish a strategy to align AI capabilities and organization goals for the future.