Regulators Urged to Take Risk-Based Approach Toward AI

A recent SEC-hosted roundtable addressing artificial intelligence highlighted the risks and rewards of its usage in financial services.

Artificial intelligence is transforming nearly every corner of the financial industry, but regulators and industry leaders remain divided over how to define, govern and deploy the technology responsibly. 

Of the more than 500 firms polled in a Broadridge Financial Services survey earlier this month, 86% reported planning to increase AI investments over the next two years.  

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Regulators have struggled to keep pace with the growing use of AI and the increasing investments in the technology made by financial firms. 

At a Securities and Exchange Commission roundtable on AI in financial services in March, panelists from major financial institutions, academia and technology firms warned that the speed of innovation is outpacing traditional regulatory frameworks. The sessions focused on both the risks and rewards of AI, as well as best practices for oversight and investor protection. 

Proposed Rule Awaits Revisions 

In July 2023, the SEC proposed a rule, commonly called the “predictive data analytics” proposal, that would require investment advisers and broker/dealers to “eliminate or neutralize” conflicts of interest arising from the use of technologies like AI in investor interactions.  

Following robust industry backlash, the agency agreed to revise the proposal, according to its July 2024 regulatory agenda, but those revisions have yet to be made. 

At the March roundtable, Commissioners Mark Uyeda and Hester Peirce, both Republicans, took aim at the original proposal during their opening remarks. 

Uyeda, who was acting SEC chair from January 20 until the April 21 confirmation of SEC Chair Paul Atkins, said he has “been concerned with some recent commission efforts that might effectively place unnecessary barriers on the use of new technology.” Peirce argued the agency fell victim to the commotion surrounding AI “when [the SEC] attempted to broadly and clumsily regulate the use of predictive data analytics by broker/ dealers and investment advisers.” 

Commissioner Caroline Crenshaw, the lone Democratic commissioner until a vacant spot is filled, did not criticize the proposal directly but acknowledged that many felt it was inappropriate.  

Several panelists questioned whether regulators should even attempt to formally define AI. Gregg Berman, managing director of market analytics and regulatory structure at Citadel Securities, compared the situation to the rise of high-frequency trading, which he said ended up working fine without a concrete definition.  

“The question in my mind is not what the definition of AI is, but does it matter?” he said. 

Others, however, including Daniel Pateiro, a managing director for strategic initiatives and artificial intelligence in the office of BlackRock’s chief operating officer, said a common taxonomy could aid transparency and regulation, if it allows for flexibility.  

A definition “could be helpful in assigning and defining clear principles to help guide us forward,” he said. “I would suggest that we think about making sure that such definitions have sufficient flexibility such that we can adapt and evolve to changing capabilities that are moving at a rapid pace within this space.” 

State of Regulation 

Despite the evolution of AI, the U.S. lacks a comprehensive federal regulatory framework to govern its use, unlike the European Union, which passed the EU AI Act in July 2024. Some federal regulatory agencies, such as the Federal Trade Commission, have taken initiatives to safeguard consumers from “deceptive practices in AI applications.” 

Meanwhile, in California, the California Consumer Privacy Act set guidelines for data handling, affecting AI systems that rely on consumer data. 

The administration of President Donald Trump has pushed for a more relaxed regulatory environment, including the governance of AI. In January, Trump issued an executive order urging agencies to “remove regulatory barriers” to AI innovation and to file an inter-agency AI action plan by July2025. 

In April, the administration released two revised policies on federal agencies’ use of AI, policies modelled after Trump’s executive order. 

Internal Compliance 

Though federal regulation does not yet exist, representatives from several firms who spoke during the SEC roundtable said they have developed internal frameworks to monitor AI risks and ensure responsible deployment.  

Jeff McMillan, head of firmwide AI at Morgan Stanley, said the company uses a tiered, risk-based approach to classify use cases.  

“It’s incredibly easy to build [with generative AI] and very challenging to deploy responsibly,” he said. 

Johnna Powell, head of AI governance at the Depository Trust Co., said her company was an early adopter of an AI policy.  

“It’s really important to make sure that you have oversight of the entire life cycle of the AI technology from development to deployment,” Powell said. 

At Vanguard, Ryan Swan, its chief data analytics officer, said the firm created an “AI Academy” to build internal literacy and tailor its governance based on data sensitivity.  

Hilary Allen, a professor at American University’s Washington College of Law, encouraged the agency to hire more technologists and noted that a significant challenge of AI is admitting that the technology can sometimes be wrong. 

“We tend to think anything spit out of a computer is better than what we come up with ourselves,” she said. “It takes a lot to be able to say, ‘No, the machine is wrong.’” 

Nearly all participants agreed that a principles-based, risk-focused regulatory framework—along with clear communication and ongoing education—will be essential as AI becomes further embedded in the financial system. 

Firms Using AI Focus on Internal Operations 

Although regulatory oversight of AI remains light for the moment, in a sense, so has its usage. Nearly every firm representative at the SEC roundtable said the best usage of AI has come by making their internal operations more efficient.  

Douglas Hamilton, head of AI engineering and research at Nasdaq, said the exchange has deployed AI for internal productivity, index creation and institutional trading execution. At BlackRock, AI tools are used to optimize trading strategies and streamline operations such as reconciliations and corporate actions.  

“This AI moment is actually bringing to light not only AI solutions, but also non-AI solutions that, when strung together, are achieving greater results for our teams and, ultimately, our firms and our clients,” BlackRock’s Pateiro said. 

Speakers also said their companies evaluate the return on investment in AI through a combination of efficiency, alpha generation, revenue growth and risk reduction.  

Pateiro said BlackRock is using AI for algorithmic pricing and “as an investment process augmentation tool,” which helps to achieve “optimal trading strategies, which assist with achieving best execution, as well as reducing transaction costs.” 

However, not all results are positive. Allen, the American University professor, highlighted survey data showing that some tasks take longer with AI due to hallucinated or inaccurate outputs.  

“I don’t want to overstate the productivity gains from these Gen AI tools,” she said. “But sometimes they’re actually more time-consuming than just doing it yourself the first time.” 

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Beyond the Annuity Puzzle: Rewiring the Psychology of Lifetime Income

A closer look at what has been limited, so far, annuity adoption by plan sponsors and participants.

Despite record-setting inflows and a decade of regulatory tailwinds, annuities appear stalled in the behavioral blind spot of the defined contribution system.

Sales are booming—LIMRA reported $434.1 billion in annuity sales in 2024, while March 2025 set a five-year record for inflows into TIAA Traditional. Yet adoption inside retirement plans, especially establishing in-plan defaults, continues to lag.

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Experts agree on the problem, however. It’s not access. It’s not product design.

It’s perception.

“If participants don’t see themselves living a long life or don’t know how to imagine retirement, they don’t value lifetime income,” said Michael Finke, a professor of wealth management at the American College of Financial Services and the co-author of a Pacific Life research paper on retirement mindset. “We found that optimism and goal tracking—psychological traits—were stronger predictors of annuity interest than traditional demographic variables.”

This insight flips the usual narrative: Instead of trying harder to sell annuities, providers’ challenge is to reframe the emotional architecture around them.

From DB Nostalgia to DC Reality

Benny Goodman, a vice president at the TIAA Institute, highlights a fundamental contradiction in language.

“Everyone loves a ‘check for life,’” he says, referring to traditional defined benefit plans that provide regular payouts from pension funds. “Use the word ‘annuity,’ and somehow, people start thinking other thoughts.”

In other words, from the perspective of annuity providers, there may be a language problem masquerading as a product problem. That language shapes not just participant sentiment, but sponsor hesitancy, too.

“Even with the SECURE [Setting Every Community Up for Retirement] Act, one of the holdbacks is the lack of availability of in-plan options,” says Liza Tyler, head of annuity solutions at Transamerica. “There’s still a perception issue—especially around flexibility.”

The nonprofit Milken Institute proposed a structural fix to the annuity perception gap in its 2025 report, “Enhancing Retirement: Advancing Lifetime Income for All.” One of its central recommendations was to classify institutional annuities as a distinct asset class.

This would allow plan sponsors and consultants to better distinguish between low-cost, fiduciary-aligned annuities designed for institutional plans and the usually high-fee, commission-based retail products that have long clouded perceptions. Reframing annuities this way could elevate them from misunderstood insurance products to credible portfolio components within modern retirement plans.

Consultants may also play a key role in reshaping that narrative. Many plan sponsors still view annuities through a retail lens, informed by decades of opaque pricing, surrender charges and high commissions.

According to Goodman, sponsors need clarity—not just in fiduciary protection, but in understanding how today’s annuities differ from their legacy reputation. Greater understanding of institutional pricing could change the conversation.

Why the Default Matters—More Than Ever

One key is easing participants into income, not asking them to jump into a cold pool at retirement. That’s what annuity-embedded defaults do.

More than 800 employer retirement plans have adopted custom target-date strategies with embedded annuity components offered by TIAA, covering approximately 1 million participants, according to Tim Pitney, TIAA’s head of lifetime income distribution.

In most cases, these strategies serve as the default plan investment option, meaning participants begin building deferred income by default—often without realizing it. The annuity allocations, which replace some fixed-income exposure, are supported by more than 65 consulting firms and are projected to reach $60 billion in assets by year-end, he said. The annuity component provides the option—but not the obligation—to convert it into a regular payout in retirement.

Tamiko Toland, a retirement income strategist and founder of IncomePath, a market intelligence service for plan sponsors, says: “If it’s already in the plan, already in the glide path—they don’t have to opt in [to selecting an annuity] or overthink it.”

Fear of Spending: The Retirement Taboo

Sue Pimento, founder of Retire With Equity, says the behavioral challenge does not end with plan design—it deepens in retirement.

“We teach people how to save for retirement. We do not teach them how to spend for retirement,” she said. “People are afraid to spend money, even to buy money.”

Pimento compares it to dying of thirst with full bottles of water: “They’re afraid to drink because they think they’ll need it later.”

This fear—sometimes called “FORO” (fear of running out)—leads to chronic underspending, which annuities are uniquely positioned to solve.

“We are more likely to spend income than savings,” Pimento said. “Therefore, we need to focus not just on assets, but on psychological liquidity.”

Missing Infrastructure: The Distribution Disconnect

While the SECURE Act addressed provider selection by adding a safe harbor for plan sponsors selecting a product and provider, “there’s no safe harbor for distribution options,” said Toland. That absence creates fiduciary anxiety and slows innovation.

To address this, the Insured Retirement Institute is pushing for legislation requiring plans to offer lifetime income options—along with a qualified payout option framework to normalize how participants receive income. This would shift the default from lump-sum withdrawal to structured payout, aligning behavioral design with retirement goals.

Even small nudges could go a long way. Showing participants a visible estimate of monthly income—not just their account balance—could reshape their decisions. If people knew what their savings meant in monthly terms, they might be more likely to convert it into income.

In the end, many sources see the limited take-up of annuities in retirement plans as not a product problem, but a framing problem. Plan sponsors and advisers have a unique opportunity to reset the conversation—not by pitching annuities harder, but by positioning them differently.

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