By Earnix Strategy Director Marcus Looft
Louis Theroux, the renowned documentary maker and journalist, made a thought-provoking observation at our recent London Summit: “I hear a lot about people being afraid of losing their jobs to AI, but it seems to me that the reality is AI won’t take anyone’s jobs. But those humans that can use AI better than their competitors certainly will.” This sentiment resonates deeply in the insurance sector, where the potential for artificial intelligence (AI) to revolutionise operations is becoming increasingly apparent.
The 1% Better Phenomenon
The concept of “The 1% Better Phenomenon” emphasises how small, incremental improvements can lead to significant long-term gains. The average adult makes around 35,000 decisions a day, spanning everything from everyday tasks to more critical work-related choices. If we could improve our decision-making process by just 1% each day, the cumulative effect over time would be transformative. A 1% daily improvement doesn’t seem substantial at first, but over the course of a year, it results in a staggering 37-fold increase in capability.
This principle is particularly relevant in business, where success often depends on continuous improvement and refining strategies, processes, and decision-making. In this context, AI plays an increasingly vital role. By assisting with data analysis, predicting outcomes, and automating routine tasks, AI can enable organisations to make more informed, faster decisions. These technologies can contribute to the 1% daily improvements by optimising processes, identifying patterns that humans may overlook, and allowing business leaders to focus on more complex, high-impact decisions. Over time, AI-driven enhancements can lead to exponential growth in efficiency and decision-making quality, helping businesses gain a competitive edge.
Addressing Climate Capacity Challenges
A key real-world application of this 1% better idea involves one of the most pressing challenges the insurance industry faces: the impact of climate change on risk assessment and capacity. Recent hurricanes, such as Hurricanes Helene and Milton, have caused staggering economic losses, with estimates indicating insured losses from both catastrophes run into the tens of billions. As the frequency and intensity of such storms increase, insurers are compelled to reassess their risk models and coverage options, particularly in vulnerable coastal regions.Here, AI can play a critical role. By analysing vast datasets – including climate patterns and historical loss records – AI can help insurers identify nuanced risks and develop tailored solutions that better align with the realities of climate change.
The Need for Real-Time Adaptation
Insurers often find themselves using overly broad exclusions to manage climate risk, which can lead to detrimental consequences for both the market and consumers. For instance, Farmers Insurance recently announced it would scale back renewing home insurance policies in Texas due to climate risk factors, raising concerns about the potential inefficiencies of such blanket exclusions. Lloyd’s of London CEO John Neal has also warned that weather disasters in Europe are set to push up insurance prices.AI can mitigate these issues by enabling insurers to adapt their underwriting processes in real time. Machine learning algorithms can refine risk assessments based on up-to-date data, allowing insurers to identify “good” risks within challenging environments rather than relying solely on historical data. This nuanced approach enhances insurers’ ability to provide coverage where it’s needed most, helping bridge the gap between evolving climate realities and the demand for insurance.
Navigating Regulation and Ethical AI Use
As AI continues to transform the insurance landscape, it also brings new ethical challenges, particularly concerning bias and discrimination in underwriting and pricing. Business leaders and regulators express concerns about the ethical implications of AI, and it is clear that the complexity of AI decision-making necessitates transparency and governance to ensure fair and equitable outcomes for customers.Insurers must establish clear guidelines and policies for ethical AI development and deployment, prioritising data privacy and security to protect sensitive customer information. Furthermore, involving diverse stakeholders in the AI decision-making process can help identify biases and foster trust among consumers.
The Road Ahead
Insurers are increasingly embedding advanced technology, particularly AI, into their business models. While AI has been used for years, its strategic importance has surged recently with the widespread availability of generative AI tools, sparking a wave of experimentation and adoption. Even traditionally cautious insurers are now investing heavily in AI.. Earnix’s 2024 survey of 431 insurance executives shows 70% of insurers plan to deploy predictive AI models within two years, yet fewer than 30% have fully implemented AI today. This gap marks a pivotal moment for AI in the insurance sector.
For insurers, this shift will be vital in addressing the ever-evolving risks – including the most pressing climate related risks that are deemed “uninsurable”. By automating routine tasks, analysing vast amounts of data, and identifying patterns that humans may miss, AI can help insurers refine their operations incrementally—leading to exponential increases in efficiency, profitability, and risk management over the long term.
Those that embrace AI and its transformative potential will not only enhance their capacity and agility but also position themselves as leaders in the race toward a more resilient and efficient insurance landscape, particularly by the potential to be able to deploy more profitable insurance capacity in regions where others have withdrawn from writing business.
By staying ahead of AI developments and leveraging its power for real-time decision-making, the insurance industry will be better equipped to meet regulatory expectations and consumer needs in 2025 and beyond.The question now is not whether AI will reshape our industry, but rather how quickly insurers can adapt to leverage its transformative capabilities. By 2025, AI will not just be a tool for operational improvement, it will be a critical differentiator for insurers seeking to expand their capacity, adapt to climate-related risks, and meet increasing regulatory demands.
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