Predict, prevent, personalize: AI's growing impact on the insurance industry

Insurance is a product designed to minimize risk and hedge one's bets against catastrophe. But when it comes to bets, the smart money is on artificial intelligence (AI) and its potential to transform the insurance sector in positive ways.

Across the industry, AI is increasingly being deployed behind the scenes to automate manual processes and improve decision-making. Many carriers use it to power risk assessment, fraud detection, and underwriting. Meanwhile, consumer-facing applications — including chatbots and personalized product recommendations — make interactions faster, more tailored and more transparent.

Personally, what I find most exciting about this technology in the insurance arena is its ability to transform the industry from being perceived as transactional to value-driven through increased transparency and consumer education. AI can enable a two-way conversation, helping carriers uncover blind spots and explore new approaches, while helping to demystify insurance jargon for consumers. This conversational style helps people interact with AI similarly to how they would with a human, which empowers consumers to make better-informed decisions. In other words, AI tools supplement expertise rather than replace it. It's this combination of predictive intelligence, personalization, and human judgment that has the power to transform our industry, improving both customer outcomes and operational efficiency.

AI's current frontlines

AI adoption is growing fastest in claims automation, underwriting and customer experience. Claims processes remain highly manual, even in the wake of other recent technological improvements. This offers AI substantial opportunities to streamline workflows and improve efficiency. By leveraging AI to gather and structure data, summarize claims and assist with initial assessments, carriers can significantly decrease task times. What once took an adjuster an hour can now be completed in minutes. Shorter task times can mean shorter wait times for customers to receive the result of their claim.

Underwriting is beginning to integrate AI for risk assessments and data summarization. Full automation is not yet widespread, but AI can augment human underwriters, empowering them to process information faster and make more informed decisions. Similarly, tools such as personalized quote recommendations and policy suggestions improve customer engagement while efficiently highlighting a customer's range of options.

At present, the most impactful uses of AI are in these back-office operations — that's where carriers can demonstrate clear ROI while mitigating risk. Claims automation, fraud detection and automated underwriting support quickly improve efficiency and cost savings. AI is best at digesting unstructured data, summarizing claims with clear references, and flagging potential issues for human review. That means employees are free to concentrate on complex cases and provide a human touch where it matters most.

Reading the tea leaves on AI

AI is poised to pivot insurance from reactive to proactive. Traditionally, insurers react to losses, analyzing data only after events occur. But predictive models should allow carriers to engage customers proactively by helping them understand and mitigate risks before claims happen.

Imagine a near future where AI can provide insights on which car models are more prone to accidents, costly to repair or carry higher premiums. Or AI-generated guidance for prospective homeowners about flood zones, storm exposure or structural mitigation strategies, such as reinforced foundations or impact windows. Informed customers can make smarter choices, which decrease potential losses for insurers and foster trust and transparency.

AI is also poised to enhance the customer journey. It's no surprise that consumers increasingly want personalized, contextually relevant solutions rather than generic recommendations. AI will enable personalization at scale, matching coverage options to an individual's risk profile, assets, and needs. It should also simplify the shopping process by suggesting the right products more quickly and providing ongoing support with timely reminders and insights. Coupled with human agents, AI will help maintain trust, empathy, and connection while improving operational efficiency.

Through 2026, I foresee AI adoption continuing to scale in proven areas like claims automation, underwriting support and chatbots. Over the next five years, I expect broader applications, including proactive risk prevention and intelligent, embedded insurance experiences. I'm confident these innovations will feel seamless, matching products to customers' risk tolerance and needs in real time.

Challenges and risks

These opportunities come with caveats, however. Insurance remains highly data-driven and traditionally relies on transparent, deterministic processes. Generative AI, by contrast, is non-deterministic and can produce unexpected outputs, which may concern carriers who are accustomed to full visibility into their models. From bias in data and non-transparent decision-making to regulatory compliance issues, the risks are real. AI cannot replace licensed agents for selling policies, so human oversight remains essential, especially during sensitive claims events. And collaboration with compliance, legal and information security teams will be critical to ensure AI is deployed safely and responsibly.

Consumer acceptance is another hurdle. While many customers prefer digital interactions, they still want contact with a real person during critical moments, such as filing claims. TheZebra.com recently polled insurance consumers and found that more than 74% prefer working with a human over AI in the event of an accident. The survey also found that only 36.7% were comfortable using AI to manage their insurance policies and recommend coverage options. The bottom line? AI cannot replace the human element, nor should it. Its true power lies in augmenting humans. This allows adjusters, agents, and customer service representatives to focus on high-value, empathy-driven tasks while AI handles the tedious, data-intensive work.

Where to begin

Here's my advice to insurance leaders eager to implement AI capabilities: start small. Begin with a use case that improves efficiency or the customer experience. Then measure the results and build internal expertise. Back-office automation, claims processing and underwriting support are ideal starting points. As your confidence and skills expand, branch out to consumer-facing applications, gradually expanding your capabilities and revisiting the guardrails as appropriate.

Most importantly, don't fear failure. Experimentation is essential, and setbacks are part of the learning process. Value AI as a tool to empower – not replace – your people. Aim for the ultimate goal of enhancing human capability and you'll reap the benefits of improving efficiency, risk management, and customer experience. AI adoption is a marathon — not a sprint.