How insurers can move toward AI's benefits

Getting started with new and powerful tech like AI can be intimidating, especially for an organization with a traditionally reluctant approach to new tech adoption. However, taking a steady and intentional approach to adoption can help. Here are some fundamental steps leaders should follow as they move to integrate AI into their processes.

Understand if your problem is relevant to machine learning's capabilities — Machine learning and AI hold a lot of potential for the insurance industry, but they are not a catch-all solution. Thus, an insurer's first step should be to consider the problems they'd look to apply it to. If data is a main consideration in the problem — such as if it concerns payout values or claims processing — then machine learning likely has a logical application since it requires huge datasets in order to serve up insights. However, not all pain points can be addressed by ML, and imposing the technology where it won't drive measurable results can be a costly and time-consuming mistake.

Decide what you want the solution to the problem to be — When you identify a pain point you believe AI can assist with, you have to decide how you want to change the outcome, and to what degree. Understanding what you want the outcome to be affects how you'll teach and manipulate the machine learning. For example, if your payout values have skyrocketed in the past year, you should know if you want to return the values to their previous rate, or if you'd like to lower them further to affect the organization's budget.

Partner up with an expert — As an emerging technology, machine learning requires specialist knowledge. It's not recommended that a team spend a significant budget to DIY a machine learning solution, only to come up with subpar results. Machine learning tools often demand more specialized expertise than most in-house developers have. Therefore, a company should consider linking up with an external team of experts who have plenty of AI experience. Understand it's an investment — if you do it, be fully committed.

While insurance may be one of the more traditional industries, that's changing as emerging tech like ML and AI becomes more democratized across the business to business world. If insurance can scale the traditionalist attitudes throughout the industry, its affinity for data makes it a perfect candidate for becoming a leader in using AI to solve problems.

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