Buying Life Insurance in 2030: A Tale of GenAI's Potential and Pitfalls

It's 2030, and the head of sales at a large, multi-national insurance company had a problem. You see, they had gone through a large transformation over the last three years, thanks to the revolution of generative AI.

They had rebuilt their entire demand creation function, in the process replacing inside sellers and marketers with AI-based bots who sent emails and kept potential customers warm. The employee base was down 35% and that cost savings had been passed back directly to shareholders. Reports said that the new AI-based automated assistants were 90% more likely to follow up with customers, and had a 50% improvement rate in converting to new opportunities. The problem was, after every other company in the industry did the same, and the problem of mass emails had become so pervasive that no consumers checked email or social media messages anymore. The rise of automated emails from quasi-persons had sent actual, living humans into behind the firewall swarms where they could conduct their lives in peace, away from an army of bots and others, trying to entice them off their goals. It turns out, no one wanted to buy insurance and peace of mind, from an automated bot.

The head of sales had completely upended content creation. Generative AI now built their websites and collateral materials, documentation, and more. With a fifth of the staff that they used to have, they were lean and mean. In fact, they could generate every version of content that they would ever need, so that they could appeal to every consumer in a hyper personalized way. Sally would get a pitch based on being a mom of three in Michigan with a military husband. And, Jose in California, would get a different pitch as the 65-year old grandfather of a household of 5. Content that targets better converts better, that had always been the marketing rule. Except that the content looked questionable, and Jose and Sally couldn't figure it out if it was real, or fake, and felt uncomfortable by how much it knew about them. After staring at the mails for a few minutes, both became distracted with other things - their pets and children, and ignored the perfectly targeted insurance pitches.

The head of sales did have a base of legacy insurance policies in effect, those that had been written back when live agents canvassed their networks for sales in the late 2010's. Many of these policies were coming due, and when it came time to assess the validity of their claims, the insurance company had adjusted their approach there, too. A series of predictive and generative AI automations had been integrated and automated as one workflow, so that the claim could be analyzed and a result written in less than 2 hours. The entire thing was a marvel of automation. This process used to take 10 days. In all, a human being interacted only once; to review the prepared result for one final check. The company even had a quality metric, which ensured that the AI would only be over-ruled 5% of the time, or less. Because of the lack of human intervention and abidance to rules, the claims were paid out at 2x the rate from before, when claims adjusters would evaluate the situation for risk mitigation from the insurance company.

So what was the head of sales business problem? Well, they couldn't attract customers, because despite the increased amount of relevant content and touchpoints, they were having trouble convincing customers to make this purchase. And the customers his company already had were costing the company too much, because the new systems were more lenient on claims than the prior regime had been. With rising costs and dwindling sales, the head of sales needed a solution.

In a pinch, the head of sales decided to go "old school" and hire some young adults, right out of college, to reach out and talk to people, the old fashioned way, in their communities and places of being. The pitches were generally subpar and much less sophisticated than the precisely targeted scripts from the AI, but importantly it was the first time many of the prospective insurance buyers had ever interacted with the company. And those prospects, even if they understood the pitch delivered by the recent college grads was a bit rusty, were able to quickly assess what value the insurance might have to their lives in stabilizing the tough economic times (which due to increasing supply chain and oil shock volatility, were tougher than ever) and make a decision. New business started to be written, and the head of sales saw an opportunity to expand his fledgling salesforce and even made a business case for it. The business case was simple: with a sales person touch, business was likely to close faster and more profitably. And it turns out, a content audit found that 98% of the automated content and outreach was actually having no effect on sales.

What is the moral of the story? Human beings are creatures of emotion. We process information through emotion, not reason. We simply do not make economic, utilitarian decisions. Nothing, "sells itself", not even if it is free. We, as buyers, judge everything based on how it makes us feel, in addition to how it helps us solve a problem. For example, choosing to buy a coffee between two identical coffee shops might engender questions such as - which one is more ethically sourced? Whose employees are nicer and treat me better? Which one will set my day up for success?

So, generative AI has the power to simplify a lot, automate a lot, remove friction from the buying process and cost from the sale. Before generative AI, the same could have been said for e-commerce and email marketing and search marketing and telemarketing. But, I would argue, that a reimagined purchase experience is just as critical in the age of AI as the AI itself. This experience encompasses a moment of convenience that solves a problem, along with a moment of joy. The reimagined insurance buying experience might pair an in-person consultation with the precisely targeted data generated by AI, and a series of automated steps post-sale to ensure that I as a buyer have fully onboarded and realized the value of my purchase, along with regular reminders or outreaches in the years to come. That is to say, the promise of generative AI should be to cut costs out of the things that are routine, so that companies can find new and cooler brand friendly ways to be memorable to their buyers in real life.

Brands will matter more than ever in the age of AI, as will the people behind the brands, and how those brands and people engage with buyers to make them feel.