Amy Friedrich has spent 20 years trying to solve the same problem. Small businesses need great benefits just like large businesses do - but they have rarely had access to the tools, the data, or the personalized guidance that makes those benefits work.
AI, she believes, is finally changing that. And the brokers who understand it earliest will define the next era of group benefits for America's small employers.
Friedrich, President of Benefits and Protection at Principal Financial in Des Moines, Iowa, oversees a portfolio spanning approximately 180,000 small businesses whose average employee count sits at 35 to 40 people. In-force premium for that segment has grown from a few hundred million dollars to approximately $4 billion over two decades - growth Friedrich attributes in large part to the depth of trust that brokers and carriers build with small business owners when they show up consistently, early, and with genuine expertise.
That trust, and the opportunity it creates, sits at the center of Principal's 2026 Global Financial Inclusion Index (GFII), released in October 2026, which tracks financial inclusion across 42 markets worldwide.
For Insurance Business Benefits US (IBB), Friedrich unpacks what the data means for US benefits brokers and why she believes the industry is at an inflection point.
The headline finding of the 2026 GFII is not encouraging for US employers. Employer support for financial inclusion declined for a fourth consecutive year in the US, falling 1.7 points to a score of 61.1 and slipping two places to 14th globally on that pillar.
The decline was driven primarily by falling pension contribution support among large and medium-to-large employers - down 8.0 and 7.5 points respectively - although employer insurance plan scores improved across every business size segment.
In the US, perceived employer support has held up better than any other pillar over five years, falling 17 percentage points since 2022, compared to a 32-point collapse in perceived government support.
For Friedrich, that resilience is not surprising and reflects something she has watched play out across hundreds of small business relationships over two decades.
"Small business owners are ranked among some of their employees' most trusted people," she said. "They're not just influential in giving them a paycheck. They're influential in having conversations about education, career advancement, parenting, elder care - business owners are ranked among some of their most trusted people in their sphere."
What makes this particularly relevant for benefits brokers is what Friedrich describes as the small business owner's decision-making instinct. Most small employers do not approach benefits through an economic lens first.
"They're not predisposed to have their first screen always be an economic screen," she said. "Often their first screen is that employee welfare screen. That's an interesting lesson I learned early, and I've seen it play out hundreds of times in my career."
That welfare-first instinct makes small business owners unusually receptive to brokers who can demonstrate genuine expertise in workforce wellbeing and unusually loyal to those who deliver it. Friedrich notes that many small businesses do not intend to stay small: a client with 14 employees this year may have 100 within 12 months.
"If they begin to understand how you can help them and they begin to feel that sense of loyalty, they often stay with you as a source of information and knowledge as they grow," she said. "They tend to be a bunch that really rewards if you have been with them at the start of their journey."
Principal's 2026 GFII found that 70 percent of US businesses surveyed are using AI to identify gaps in benefits uptake among employees, with 33 percent of businesses doing so as part of regular human resources operations.
But Friedrich draws a distinction that the headline adoption figures do not capture.
"It's not even an efficiency play," she said. "That's an effectiveness play - if I have a certain amount of dollars I'm going to spend for my own employee population, spending them this way is the best. I'm going to do things that increase the likelihood that they'll actually be utilized by this employee population."
The practical mechanics, as she describes them, are simpler than most small business owners assume. Leading benefits brokers are loading client census files - age, gender, enrollment data, spousal and family coverage - into basic generative AI tools and running targeted prompts ahead of annual plan reviews.
"The best brokers are coming to reviews saying: I took your census file, I put it through some basic generative AI - Copilot or Claude or whatever you prefer - and let me tell you the prompts I used," Friedrich said. "One prompt was: in my size industry and region, what are the products that would be most utilized for this employee population? I want to show you what I got from that, and I want to talk to you about how there's a disability coverage you don't offer. I put in a prompt on paid family and medical leave: give me the basics of this coverage and how could this employee population use that."
That kind of analysis was simply not scalable a few years ago. Brokers serving small businesses typically manage between 500 and 1,200 clients. Manual preparation of tailored recommendations for every account was prohibitively time-intensive and a gamble. If a client declined to act, the broker had little to show for the work.
"If they did it 100 times and it didn't get used 95 of the times, they'd be like, this took me forever," she said. "Now the risk isn't as big to put these things together."
The best brokers, Friedrich adds, do not stop at the plan review. They leave clients with three or four replicable AI prompts to run against their own census files between meetings - effectively turning AI into an ongoing financial education tool, and setting up the next review conversation in advance.
"Even leaving them with a replicable prompt to use against that dataset is starting to become the delivery mechanism of financial security for those employees," she said. "They'll actually have a benefit package that is tailored to the population."
The personalization benefit is concrete and consequential. A workforce primarily in their 20s and 30s warrants prioritizing paid family and medical leave. A workforce aged 45 to 60 calls for elder care coverage. Without AI-assisted analysis of a census file, most small employers - without an HR department to run that analysis - would not make those distinctions at all.
Friedrich is also watching chatbot-assisted enrollment scale downmarket. Technology previously limited to large enterprises with custom-built human resources systems is now reaching companies of 25 to 50 employees.
"Some brokers are even investing in their own technology so that for small employers, they don't have to wait for that to be built for them," she said. "I'm seeing way more options for what I would call assisted enrollment - not just plan design or plan selection, but assisted enrollment and education as well."
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The AI-driven narrowing of options also addresses one of the most persistent problems in small group benefits: decision paralysis
"We know what too much choice yields, and it actually yields worse results," Friedrich said. "When you have a prompting system using information specific to that population and prompting for recommendations, it takes away the 17 things you could do, and it helps narrow it down to the two or three things that would be most recommended or most highly utilized."
Adding benchmarking data alongside a census file into an AI prompt, she notes, produces an even stronger output - giving brokers the kind of targeted recommendation that previously required significant manual analysis.
The conductor analogy Friedrich responds to most strongly captures both the AI opportunity and the enduring value of broker expertise. When a small business owner comes to a plan review asking for dental insurance because employees have requested it, a broker armed with AI-driven census analysis can redirect that conversation with evidence.
"Sometimes that broker tells them: right now, dental shouldn't be your top priority," Friedrich said. "You should really worry about making sure there's income replacement for the people who couldn't go two weeks or two months without a paycheck. Those are the types of conversations that when AI is used well, I'm seeing them as more likely to happen, and happen with more frequency, and happen with more follow-through."
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For all the opportunity, the 2026 GFII reveals a significant and widening divide.
Approximately 51 percent of businesses with two to ten employees use AI to support employee benefits or financial wellbeing, compared with around 78 percent of firms with 1,000 or more employees. Around one in five micro-businesses say they do not currently use AI at all, compared with only 4 to 7 percent of firms with 101 or more employees.
The gap is widest for more sophisticated applications. Only 15 percent of businesses with two to ten employees use AI for financial education, compared with 46 percent of businesses with 1,000 or more employees. For understanding employees' financial needs and tailoring benefits accordingly, the split is similar: 19 percent of micro-businesses versus 44 percent of large employers.
Friedrich said she found the micro-business adoption rate "shockingly low," given how accessible the underlying tools already are.
"Even using a large language model, attaching your own company census file, and using a set of basic prompts takes very little education," she said. "It takes very little unique access to information or file structure, and it should be highly available and highly understandable."
She attributes the gap not to technical complexity but to a failure of translation - small business owners have not yet made the leap from viewing AI as a personal productivity tool to recognizing it as a business productivity tool.
"I think a lot of people hear a whole different set of language around agentic AI and orchestration," Friedrich said. "And the stuff I'm describing - that's using basic generative AI tools in a way that's really productive and personalized for your organization. You don't have to have enterprise-level agentic AI capabilities to truly take advantage of some of the things that have become pretty commonplace."
The role of the benefits broker, she argues, is to bridge that gap - arriving at a client meeting not just with product recommendations but with a demonstration of what basic AI analysis of that client's own census file can reveal. That demonstration, more than any abstract argument for AI adoption, is what moves small business owners.
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One of the most common objections Friedrich hears to AI adoption is the fear of job displacement. Principal’s Financial Well-Being Index - a quarterly study tracking US employer sentiment, with Wave 3 fielded June 22 through July 13, 2026 - addresses that concern directly.
Most businesses surveyed expect AI adoption to support stable or growing staffing levels and wages, with that confidence running even stronger than when the same question was asked in October 2025. Principal’s own customer data shows overall employment growth within its employer base remaining stable, with customers continuing to report increasing wages.
“Much of the public conversation around AI has focused on potential job losses, but employers are telling a more nuanced story,” Friedrich said. “We’re seeing broadening AI adoption alongside relatively stable staffing levels and continued investment in talent. The focus is less on workforce reduction and more on using AI to increase productivity, support employees, and help drive business growth.”
The Well-Being Index Wave 3 also found that 69 percent of businesses report seeing an increase in employees delaying retirement because of financial security concerns - with cost of living, savings, and healthcare topping the list - a finding that makes the AI-assisted personalization Friedrich describes not a luxury but a practical necessity.
Friedrich closes on a note that is equal parts commercial and civic. For Principal, a small employer that uses AI to build a benefits package genuinely matched to its workforce is more likely to offer coverage, more likely to see that coverage utilized, and more likely to remain a long-term client. But the stakes she describes go beyond any single carrier's book of business.
"In my mind, that's how AI is democratizing the best personalized advice for smaller employers," she said. "And it's exciting to me because when business owners take care of their employees better, you tend to see the economic fortunes of those communities rise with it. There's a true economic value to that."
The translation from personal productivity tool to business productivity tool, she acknowledges, has not happened yet at scale among the smallest businesses. But she is confident about what happens when it does.
"I think when we do make that leap for smaller businesses," Friedrich said, "we'll see some of those financial security numbers really pop.”
