Five years ago, there was no conflict in Ukraine. People went into offices for work. No one was fighting over toilet paper. Everyone’s concept of AI was loosely anchored by Hollywood films like Terminator or War Games.
And, insurers enjoyed relatively stable profits, consistent inflation/interest rates, and manageable change volume.
The truth today boggles the mind – a year’s worth of rain falls in a single day at Dubai airport, extinction-level web disruption brought on by Crowd Strike, and risks are evolving at a geometric rate thanks to AI.
Not unlike World War II, which forced creation’s hand and gave humanity the power of the Atom, COVID drove insurers and financial institutions through a decade-long innovation cycle in just a few weeks. Employees who were going into offices in February 2020 suddenly found themselves as permanent work-from-home associates.
Fast forward five years, it's now 2025, your Y2K baby just graduated from college, and explaining a “dial-tone” to someone who grew up only knowing iPhones makes your brain hurt.
And now you have AI to deal with (smh).
In order to take advantage of the GenAI inflection point (see Amara’s Law), we need to focus on the problems we’re trying to solve with AI (not focus on AI first and shoehorn it into workflows and processes). It’s critical in this moment to not become distracted with the baubles and bits. Rather, make a deliberate and concerted effort to start with the fundamentals of your business.
So, let’s examine three futures insurance experts at SAS believe our community will need to address (and how) in 2025 and beyond.
Examining the future of work
“50% of insurance professionals will retire in the next 5 years. Technology must be a part of the solution to addressing the talent gap.” James Ruotolo, Sr Director of Financial Services, SAS
It’s true. Our industry’s “silver tsunami” threatens the very existence of our business. Let’s agree, we’ll use AI (I already know 92% of you reading this are budgeting for AI, so let’s not argue on this point). Let’s also agree not all AI is created equal. There are two truths in the cloud: power and compute (how big, how fast).
You can get more done faster, you can save money doing it, or you can do both. Choice of AI matters, greatly. And once you’ve made that choice, you’ll need to implement it (because it doesn’t matter how cool the car is if no one can drive it).
McKinsey calls for a “domain-based” approach when implementing AI. Results show an 80% successful intervention rate for struggling transformations when taking a step back and “re-anchoring” against a well-defined domain.
For insurers, a well-defined “domain,” can be a function like underwriting, claims, or sales. It could also encompass a line of business such as Personal Lines or Commercial Lines.
Take the example of Ant Group, which recently deployed an “AI-powered life assistant” on the company’s digital life platform, Alipay. Customers now have robust options for AI agents. This is an example of a well-defined domain (the digital platform) and an AI use case (improving the user experience).
Once you’ve established the domain(s), you’ll need to ensure your talent believes in the approach and how these AI tools can help them not only get more done but also make themselves more valuable on their development journey.
According to a recent LinkedIn and Microsoft survey, 54% of early-career employees state AI tools influence employer choice.
What better way to kill two flies with one swat (in this case, addressing the talent gap and implementing AI)? The very technology you’re investing in can fill the gap in your underwriting, claims and/or sales departments because working with AI is THE SKILL of the future.
Before we move on from this first of three tri-force insurance trends, I’ll remind the reader of this quote from Jensen Huang, CEO of Nvidia: “AI won’t take your job, someone who knows how to use AI will.”
Remember where you came from
“Usage of telematics and IoT in Auto / Home, Neural networks in fraud prevention or anti-money laundering, cyber or embedded insurance: amounts of investments remain askew when compared to real change. And real change is what we need, then the results will come.” Nilanjan Mukherjee, Sr. Manager of Risk Consulting, SAS
Generations from now, our story will be told. And the title of that story will not be “This telematics product was better than that,” or “Wow, check out that AML solution!” No, it will be a story about “insurers return to their roots through technology.”
This is a data story that reveals your organization’s identity.
In my prior life, I was an underwriter at a company rooted in farming communities, whose agents often represented the rural cross-section of Americana so many yearn for with deep, and wide-eyed nostalgia… recent decisions to depart from that identity, transforming into a soulless financial services firm felt like a betrayal to many who spent decades within her four walls.
Let’s remember the Simon Sinek quote: " People don’t buy what you do; they buy why you do it. " This truth is no different in insurance.
We all agree we’re in a trust business. By default, insurers must protect their data. In doing so, the same data can fuel innovation and new use cases and lead to growth. However, you can’t have a use case without the capabilities to deliver on it – which is where your experience, expertise, and identity come in.
Designing a comprehensive data strategy rooted in the organization’s culture and identity will only facilitate AI adoption in the long run and remove obstacles, such as the existence of vast quantities of unstructured data that hinder it. Remember, data is the fuel for AI, so the cleaner it is before being put in the tank, the higher the performance of the engine running the enterprise.
AI is not enough, though. Simon Sinek’s quote draws from a larger conversation in which TiVo and DVR are compared: the former, a far superior technology, lacking inspiration.
The victors of tomorrow’s insurance competitive hellscape will be those whose messages are authentic and rooted in their identities.
Today’s advertisements focusing on low-cost and great service lack inspiration. Every major carrier will wield technology to lower costs, but to the average consumer or business owner, this is table stakes. How refreshing would it be to hear a different message?
“For a hundred years, we’ve protected what matters most to you. Today’s challenges inspire us to renew and evolve our promises for the next one hundred years. Starting today, our company will protect you. No matter where you live, what you do, what your risk – you will have one policy, with one premium, no forms to fill out, no waivers to sign. Our promise is your peace of mind to simply, live.”
Before the end of the COVID decade, a major global carrier will crack the “omni-policy” code – an AI-fueled, all-encompassing blanket of protection, centered around a person, regardless of their risk.
Climate terror: Dealing with natural disasters
“You see, insurers will increase focus on sustainability, as climate change drives major shifts in risk modeling and coverage options. Efforts for automation, digital transformation, and customer centricity will continue.” Oana Avaramescu, Industry Risk Advisor, SAS
Milton used to be a character from Office Space – now it is the latest in a series of signals impossible to ignore.
Climate change is real.
SwissRe Group places the protection gap from natural catastrophes in 2023 at 62% of economic losses were uninsured ($108 billion covered). In the same publication, they conclude “impacts from natural catastrophes will only continue to grow.”
As a result, the insurance industry’s capacity to model risk must also grow. Consider Hurricane Ian (2022): Modeling incorrectly calculated the storm’s trajectory, leading to evacuation delays. Thus, investments have been made in more powerful computing, but this is not enough. We must explore deeper – for example, the use of synthetic data (a form of GenAI) can strengthen our ability to predict evolving weather patterns and losses associated with them more accurately.
In addition to advanced modeling with AI, options such as captive insurance are growing in popularity. Forming a captive can carry greater flexibility to handle nuanced risks, and as the parent wholly owns the insurer, addressing the parent’s unique needs (such as addressing gaps in coverage due to climate risk), can be an attractive option.
Ironically, with AI, there is a downside regarding climate risk, finite resources, and regression to “old ways.”
“OpenAI needs money, because AI is expensive. It’s expensive because it consumes vast resources. And the highway to the Intelligence Age will be paved with bad decisions: cool data centers in the desert with clean drinking water, to the tune of 56 million gallons annually.”
The narrative becomes even more bleak when we consider projections like “4.5% of the world’s energy production will power data centers by 2030.” As a result, continued exploitation of fossil fuels will work against progress. And the most impacted will be already marginalized populations.
We cannot throw AI at everything – in the long run it could do more harm than good.
One in 1,000-year events are becoming daily occurrences. Something must change. However, our response must be tempered. Use the right tools for the job because AI could be a sledgehammer cracking a walnut, which adds fuel to an already burning planet.
What’s the worst that could happen?
Nothing.
There’s an inertia to our actions – large organizations are much like container ships, they do not turn on a dime. Change will be hard and progress will be slow, impossibly slow.
However, inertia continues to lead us down dark roads. We're becoming increasingly taxed, tired, and tormented by increasingly weird, unprecedented events.
I mean, who could have foreseen CrowdStrike? Someone “trips over the cord” and brings down the global internet apparatus causing billions in economic losses and irreparable damage to their brand.
I’ll leave you with this thought;
“There’s a non-zero change the insurance industry collapses by 2040.” This is what happens if nothing changes. See you next year😊
