How this insurance exec learned to stop worrying and love AI

AI is coming for your job. Adapt or die. You are replaceable by a machine…

Do these phrases sound familiar? Chances are you’ve been hearing and reading them everywhere you look. Everyone wants you to know that your job is in jeopardy.

I’m here with a slightly different perspective. Instead of worrying about the disruption AI will cause in insurance, the way forward is to embrace the change that it offers in a way that continues to make you what you are: Human. No one expects you to be a machine.

As someone who has been following, adjacent to and at times directly participating in the AI community for more than two decades, there’s no doubt this is an exciting time for the discipline. Since the time I finished my graduate work on applied neural networks in 2003, advances in computing power and availability combined with renewed focus on these techniques have accelerated a once sleepy discipline. Now we tend to hear about the latest developments on the news, often with the doom-and-gloom angle I referenced above.

Oh, the humanity!

Technology development has always served to propel humankind forward into a more convenient, comfortable and efficient world. But it’s often in the form of a gradual evolution, not an instant transformation.

For instance, the internet boom enabled e-commerce, which was heralded as the “end of brick-and-mortar retail.” Certainly some physical storefronts have been decimated by this rise, but plenty have not only survived but thrived in this environment. This is often because these companies embrace the new technologies and use their storefronts as a way to create a human connection to their products and services.

Today, we have the opportunity to write a similar story in the insurance industry, where there are many opportunities to adopt new AI technologies across different roles within the firm. Processing information faster, finding known information in unknown documents, synthesizing large, disparate datasets; these are all excellent ways to leverage advancements in AI to deliver real value for underwriting teams, claims processors and more.

The key to success in all these use cases lies in the partnership between humans and machines.

Innovation vs. confrontation

Humans are very good at building connections with other humans, developing genuine rapport and having empathy for their needs. We have a natural curiosity and creativity. All these traits can be enhanced and brightened by leveraging tools that automate nonessential activities and enable us to focus on what will fulfill our greatest potential.

The AI systems that are available via large language models and other modern techniques are very good at synthesizing information and providing summaries (even quite creative ones). They can be trained to perform complex operations, applying given criteria to shifting situations. They will certainly continue to improve over time.

We must not allow this innovation to turn into a confrontation between the old and the new, the truly human and the singular machine. Instead, we need to be open to leveraging our skills in conjunction with the advancements in technology. With this mindset, we can embrace AI not as an existential threat to our jobs, but as a force for good that will make us more effective and efficient every day.

While the hype around AI may feel like a sea change, it is similar in many ways to past accelerations in technological progress. Excitement and expectations (not to mention capital investment) are extremely high, with significant buzz about what these advancements could mean for “every job on the planet.” Some people embrace it so fully that they completely change the way they work to accommodate the new technology. Others run for the hills and shun the newness. My advice: Proceed.

Just make sure you’re using AI only to drive real business value by augmenting your own abilities. Expecting a prompt to do your job for you will put us all on a road to nowhere.

Jeff Tyler (jtyler@insurancequantified.com) is head of Product, Data Science & Engineering at Insurance Quantified. These opinions are his own.