AI is rapidly transforming the annuity industry, helping automate processes but raising concerns about accuracy and transparency. Experts warn of risks like recommendation bias and lack of human oversight. Regulators are focusing on data transparency and human review to ensure consumer protection.
As artificial intelligence roots deepen in business, the annuity industry immerses itself in AI programs, products and policies in burgeoning numbers. According to Goldman Sachs, 29% of insurance companies already use AI, while 51% say they are “looking to implement AI technologies.”
Annuity providers are leaning on AI to educate the public on annuities, with technology tools like Ignitor by AIinsurMe to train financial advisors to understand fixed annuities better and show them how to make better decisions on how annuities fit in their investment portfolios. Other companies use the technology to create AI-powered indexes to analyze customer data and make more efficient annuity decisions.
With AI advancing so quickly in the annuity marketplace, concern rises over potential usage risks that haven’t been adequately vetted yet. According to Kennedys’ most recent 2025 Global Forecast Report, AI topped the list of biggest risks ranked by the study.
Industry think tanks are getting into the act, too.
Analysts at the National Association of Insurance Commissioners are studying ways to ensure annuity providers avoid using “bad data” that could undermine consumer’s annuity experiences. To get the job done, the NAIC’s Third-Party Data and Models Task Force is building a framework for proper regulatory oversight of AI-powered consumer data, analytical models and technology tools that insurers use when engaging with annuity consumers.
AI “Hard to Ignore”
With AI here for the long haul, annuity providers look for guardrails when deploying relatively untested technology tools with customers.
“AI is working its way into the annuity industry in ways that are hard to ignore,” said Ramzy Ladah, a Las Vegas-based Ladeh Law Firm trial attorney. “Companies are using it to automate customer interactions, analyze data and generate personalized product recommendations. Chatbots are handling inquiries, algorithms are scanning financial histories and predictive models are shaping how annuities are structured.”
That all sounds efficient, and in many ways, it is. But efficiency doesn’t always mean accuracy and certainly doesn’t guarantee fairness, Ladeh noted. “A customer could be given an annuity recommendation based on data patterns rather than real financial needs, leading to decisions that look good on paper but don’t work in practice,” he said. “A retiree, for example, might get pushed toward a complex annuity they don’t fully understand just because an algorithm flagged them as a ‘good match.’”
AI industry experts say those threats are all too real.
“There are some pressing concerns across annuity institutions,” said Ger Perdisatt, founder and CEO at Dublin, Ireland-based Acuity AI, an AI strategy advisory service for small and medium businesses, corporate innovation leaders, and boards. “We’re seeing recommendation bias steering annuity customers toward unsuitable products, transparency challenges where neither customers nor advisors understand the basis for AI recommendations, and ‘black box’ problems – when outcomes can’t be explained in human terms.”
Perdisatt, a former technology director at Microsoft, said customer confusion and angst over bad AI information are to be expected, and these risks materialize “when companies rush implementation without proper governance frameworks.”
While EIOPA, Europe’s insurance authority, has already classified insurance AI systems as “high-risk,” requiring rigorous controls and human oversight beyond FINRA’s current guidance, US regulators seem to be a step behind but are looking to make up ground. “We’re seeing that regulators will likely focus on three key annuity regulatory concern:”
- Explainability requirements ensuring recommendations can be justified in human terms.
- Mandatory human oversight at critical decision points.
- Clear accountability frameworks between insurers, technology providers and advisors.
“Insurers I’ve worked with have found that embracing these principles early actually accelerated their AI adoption by building trust with customers and regulators,” Perdisatt said. “This might offer a glimpse into the future for U.S. firms.”
All Hands on Deck
One of the biggest risks is AI operating within the annuity realm without human review.
“Many annuities are complex, and AI lacks the human touch to ask deeper questions that uncover a client’s true goals,” said Danny Ray, founder at PinnacleQuote, a consumer insurance services platform headquartered in Jacksonville, Florida. “In some cases, AI-generated recommendations may prioritize profitability over what’s best for the consumer. Moreover, biases in data can lead to unfair pricing or exclusions that hurt certain demographics.”
That’s why recent regulatory concerns about AI and insurance products highlight the need for responsible regulation. “The government should focus on transparency, requiring companies to disclose when AI is used in recommendations,” Ray said. “In addition, regulations should ensure that human advisors remain involved in decision-making rather than relying entirely on AI-driven models. For example, requiring AI-generated advice to be reviewed by a licensed professional before being presented to clients would add an essential layer of protection.”
Recent reports from financial industry organizations like FINRA are also signs that regulators are paying closer attention to insurance companies and that government action is inevitable.
“The challenge is figuring out how to regulate AI in a way that protects consumers without stifling innovation,” Ladah said. “One approach would be setting clear rules on data transparency, ensuring customers understand how AI influences their options. Companies should be required to disclose when an AI model is involved in an annuity recommendation and provide a human review process as a safeguard.”
There also needs to be strict oversight of bias testing. “If an AI system shows patterns of discrimination—whether intentional or not—it should be flagged and corrected before it affects real customers,” Ladah added. “Privacy protections must be airtight, with clear limits on how much personal data AI can access and how it’s stored.”
Ladah agrees that government regulators will likely focus on core issues like ensuring AI doesn’t mislead or discriminate, tightening data security and demanding transparency in AI-driven financial recommendations.
“Annuities are long-term financial commitments, and the risks of AI making flawed recommendations are too high to ignore,” he added. “Regulation won’t stop companies from using AI, but it will force them to use it more responsibly. The industry needs clear guidelines, real oversight and a recognition that while AI can be a powerful tool, it can’t replace human judgment when it comes to complex financial decisions.”
Editor Norah Layne contributed to this article.