Sector by sector, artificial intelligence is ascending across the business landscape, with AI now prevalent in corporate fiefdoms like manufacturing, banking, and legal and compliance, among many others.
So it goes with the insurance sector, where AI is breathing new life into an older, more plodding industry.
About 50% of all US insurance companies will have at least tested AI systems and solutions, according to a new Celent survey. Another 25% will be in full AI implementation mode by the end of the year, Celent adds.
Industry observers say that while the insurance industry is in the early stages of artificial intelligence development, it’s learning some good lessons and building some high expectations for the technology when it’s fully 100% up and running.
“The insurance industry, along with many other sectors, is currently experiencing a sea change,” says Christopher Freese, managing director of Boston Consultant Group’s insurance practice in a recent BCG question and answer session. “GenAI is not just an improvement on traditional machine-learning models used for natural language processing or computer vision, for example.”
According to Freese, Gen AI “democratizes access to the larger AI ecosystem,” simplifying the interface so profoundly “that anyone, regardless of programming expertise, can leverage AI’s power.”
In that light, Freese says he’s reminded of the iPhone and its app store rollout, which “paved the way” for a whole new ecosystem of applications and services.
“This marks a fundamental difference from the advent of traditional AI,” Freese notes. “While virtually all insurance companies are using AI today, its impact has fallen short of the transformative change that many had hoped for. Traditional AI has been restricted largely to an approach based on use cases, optimizing niches of existing operating models, rather than fundamentally transforming them.”
Now, senior executives at the top branded insurers are beginning to see the potential of GenAI as a transformational catalyst.
“They’re looking beyond individual use cases, focus on the big wins, and deploy GenAI to redesign their operating model end to end,” he says. “By embracing this transformative approach, these leaders are rapidly pulling ahead of their competitors.”
Creating New Paths
Insurance companies are leveraging AI in two specific ways, Freese says.
— For day-to-day tasks: “The first is to focus on a few game-changing applications and scale them across the value chain,” he says. “For large parts of the company, these GenAI applications have a substantial impact on day-to-day operations.
Two early examples are knowledge assistants and coding assistants, Freese notes.
“Knowledge assistants dramatically cut the time required to research documented knowledge. Using a chatbot interface, they provide agents with information from policy documents, wiki sites, and process manuals,” he says. “Similarly, a coding assistant accelerates software development by offering autocompletion, code translation, and debugging capabilities. It has the potential to remove bottlenecks in IT capacities throughout the value chain and help address the difficulties of dealing with legacy code and mainframe programming languages.”
— For transforming individual verticals: AI has given Insurance companies the luxury of imagining new customer journeys and new operational opportunities.
One example of that scenario is the end-to-end automation of the claims process in auto insurance, Freese states.
“Every step in the journey is revised, from first notice of loss to settlement,” he notes. “Using an uploaded image, GenAI can automatically generate an instant settlement offer, relying on an archive of millions of vehicle damages photos and incident reports.”
In the first phase, a human team member is tasked with reviewing the AI’s work, but even that process is “radically simplified.,” Freese points out.
“This significantly enhances many customers’ experiences, eliminating the need to endure lengthy processes with assessors,” he says. “For insurance companies, it’s a substantial opportunity to reduce cost.”
Freese says insurers who do the job right and “embrace an AI transformation” will generate
“substantial efficiency gains and cost savings”.
The biggest savings, ranging from 40% to 60%, are expected to come from productivity gains in customer service, where approximately 35% of customer service agents’ time is spent collecting data on policies, terms, and other insurance-related documents.
“In such tasks, GenAI can more than double agents’ productivity,” Freese says. “Agents can query these documents directly—for instance, to check a specific policy’s coverage conditions—and get answers in seconds.”
Brian O’Connell, a former Wall Street bond trader and best-selling author, is a prominent figure in the finance industry. With a substantial background as an ex-Wall Street trader, he has authored two best-selling books: ‘The 401k Millionaire’ and ‘CNBC’s Creating Wealth’, demonstrating his profound knowledge of finance and investing.
Brian is also a finance and business writer for esteemed national platforms and publications, including CNN, TheStreet.com, CBS News, The Wall Street Journal, U.S. News & World Report, Forbes, and Fox News.
