When we look back on notable insurance industry technology shifts, the 20s will no doubt be marked by the rise of AI. While not “new,” the technology has quietly become so advanced and astoundingly proficient that companies are being forced to take notice.
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Insurance is both a business of statistics and one of people. The business is so data-driven on the product side that it practically begs for a human element on the delivery side. In the insurance industry, leaning too heavily on either side can be detrimental to the business. While there will certainly be a natural urge to test the boundaries of AI’s reach, there’s a point at which the wisdom and decorum of a person won’t outweigh that of efficiency.
The voice of insurance professionals will be more important than ever as the industry navigates this shift. Companies that integrate AI based on theoretical use cases without factoring in the decision-based wisdom of the people it’s designed to think like can be a setup for chaos. At the same time, by being open to these new models of operation that AI can deliver, insurance professionals can realize welcome opportunities for an improved experience for themselves and customers. Done well, AI in insurance can afford industry experts to do more of the work that energizes them and sets them apart in the industry.
The Rise of AI in the Insurance Industry
The very nature of the insurance product itself relies on detecting patterns among large averages and making accurate data-based predictions. As more types of data can be gathered through input from interconnected devices, the ability to leverage AI to identify trends and make decisions and predictions based on so many granular pieces of raw data has fascinating potential. Tighter premium ratings and an increased ability to prevent fraud mean more competitive premium rates, better products, and healthier profit margins.
In the claims handling arena, AI can translate images and video from a customer’s phone into digital claims reports that once took hours to collect, research, and write. AI’s decision-based programming can translate certain visual properties about what is “seen” in a photo (distances, depth, fracture patterns) into a report in a way that replicates that of the human eye and mind. With this data, AI can quickly generate damage reports and calculate repair cost estimates, then find a local shop with availability, schedule the appointment, and notify the customer, without these tasks piling up on the claims adjuster’s desk.
Integrating AI into specific customer touchpoints to meet them precisely where they’re at and quickly collect the information that moves the interaction forward are opportunities to improve the customer experience while also drastically increasing efficiency. Whether it’s service calls, quote inquiries, or claims reporting calls, there’s a lot of tedious work in the process that can be collected using AI before an industry professional enters with their professional discretion and expertise.
As in any business, making more effective predictions, quickly identifying unusual activity or signs of fraud, and employing more productive use of time is critical to the bottom line. These are areas where AI is finding a natural fit in the insurance industry.
The Limitations of AI in Insurance
Knowing how to apply the findings is a different aspect altogether. While we can robotize and make calculations about all of human behavior based on data sets, it doesn’t mean that we should or even legally can. There’s an opportunity for inferences made from data to be wildly off. As the saying goes, “garbage in, garbage out.” If we just let AI loose on the town to both collect and then analyze and make predictions based on its own findings, the results can become like a snake eating its own tail, using circular logic to prove its own and spiraling off track.
There’s a deeply human element inherent in the very nature of insurance that AI may assist people with but will be hard-pressed to replace.
The Human Touch in Insurance Expertise
Insurance touches people at some of the most vulnerable times of their lives. It’s a product people buy in hopes they’ll never have to use it. Insurance policies hinge on risk and lifestyle factors that force people to analyze the value of their lives in ways that can be difficult to process, accept, or even understand. The importance of human interaction can’t be overlooked as a factor when selling, servicing, or delivering on a product as intimate as insurance.
Although technology has greatly improved in the area of intent recognition, there are still inherent gaps in AI detecting the appropriate solution. A customer may be inquiring about one product that has a solution in a completely different product silo. The ability of a subject matter expert to hear and diagnose the customer’s primary issue and provide a personalized explanation and recommendation is paramount in an industry like insurance where there is inherently a great deal of complexity and confusion.
In an industry that is rife with frustration and general distrust, where small details make critical differences, and where laws, limitations, and products are continually changing, the need for relationships founded on trust and rapport is unlikely to be replaced by AI anytime soon.
The Hybrid Approach: AI and Human Expertise
The solution lies somewhere in between. It will be critical for AI programmers to learn from insurance professionals in order to get this right. The nuances of insurance are many and will require looping experts into the pattern recognition and solutions-pairing process.
By combining AI’s efficiency with human judgment, we can begin to see real, intuitive shifts in the industry. This evolution will require a bridge between programmers and insurance professionals. Empowering insurance professionals to use AI tools while also providing boots-on-the-ground users a way to provide feedback will make or break the success of AI in different cases.
Establishing metrics of success that are tied not only to task-efficiency data but also to what it truly means to hear and serve the customer will be essential to successful AI integration at deeper levels in the insurance industry. Viewing this not as a point that we “reach” but as a process of continual improvement will be the difference between those that achieve temporary versus true long-term success with AI in insurance.
Looking Forward
There’s little doubt that AI is here to stay. Companies that adopt it are poised to see exponential growth rivaling that of the industrial revolution. It’s that significant. As we move forward through this “catching point,” two things will be essential:
- First, insurance professionals will need to learn to accept, use, and adapt to the idea of this technology.
- On the flip side, AI programmers will need to adopt a culture that embraces user feedback and have a system for obtaining that feedback from actual users of the technology.
Technologies that reduce tedious tasks, prepare more comprehensive reports, find new customers, and prioritize and streamline tasks allow professionals to do more of what they love while allowing companies to become more efficient and profitable. It’s a win-win for everyone.
Insurance pros can have an important role in shaping when and how AI can be useful at various touchpoints. The integration of AI doesn’t need to be a hostile takeover of humans by computers. Behind the programs are people — programmers. AI is only as good as the people who program it. Insurance professionals and the wisdom they hold can expect to be an integral voice in that process.
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