The program for the recent National Association of Public Pension Attorneys (NAPPA) 2026 Legal Education Conference provides useful insight into the issues currently occupying the attention of public pension lawyers across the country.

While conference agendas never tell the whole story, the topics offer a glimpse of the legal, regulatory, governance, and investment challenges public pension systems now confront.

Held June 15-18 in Grand Rapids, Michigan, this year’s conference featured several themes: the rapid integration of artificial intelligence, growing complexity in investment regulation, heightened focus on plan governance and fiduciary duties, continued concern over funding and benefit administration, and increased attention to regulatory enforcement and litigation risk.

Artificial Intelligence Has Moved from Theory to Implementation

First and foremost, the agenda highlighted how much artificial intelligence (AI) has become a mainstream legal issue for public pensions. Where discussion once focused on whether plans should use the technology, the multiple sessions on AI at this year’s event grappled with how public funds can use it responsibly.

One general session examined how public pension systems have implemented AI while safeguarding data privacy and cybersecurity and tracking developments in the evolving state and federal legal landscape. An ethics session addressed lawyers’ professional responsibilities when using generative AI, including duties relating to competence, confidentiality, supervision, client communications, and bias mitigation. A third session focused on practical implementation of AI in investment legal review, including governance frameworks, privilege concerns, contract review processes, and AI-assisted negotiation playbooks.

Taken together, these sessions suggest that AI governance is quickly becoming a core concern for public pension counsel, who increasingly are being asked not only to understand the technology but also to help develop policies that manage legal, ethical, and operational risks associated with its adoption.

Regulatory Change and Enforcement Risk Are Top of Mind

The conference also reflected concern about shifting regulatory priorities and enforcement trends. One general session was devoted to helping attendees stay current with rapidly changing regulatory developments affecting pension systems, from ADA compliance and HIPAA updates to reporting requirements and the SEC’s policy shift in favor of forced arbitration.

Another panel, led by Cohen Milstein partner Daniel S. Sommers, examined evolving SEC enforcement priorities and the impact on institutional investors, including the resulting implications for securities litigation, corporate governance matters, and institutional investor protections. The panel highlighted ways for pension counsel to navigate the increasingly complex and uncertain regulatory enforcement environment. (See Dan’s article on the subject elsewhere in this issue.

The focus on regulatory developments suggests that public pension lawyers are preparing for a period of continued uncertainty. Changes at federal agencies, evolving securities enforcement priorities, and shifting governance expectations all have the potential to affect pension fund operations and investment programs.

Fiduciary Duties and Governance Remain Foundational

Despite the focus on emerging issues, the conference agenda demonstrated that traditional fiduciary and governance concerns remain at the heart of public pension practice.

The conference opened with a comprehensive series of introductory sessions addressing fiduciary duties, benefits administration, actuarial concepts, investment governance, and the legal framework governing public pension plans. These sessions emphasized duties of loyalty and prudence, plan administration principles, funding concepts, and the legal considerations associated with investment oversight.

The prominence of these topics reflects a continuing reality: regardless of technological innovation or regulatory change, pension boards and their counsel remain accountable for ensuring that core fiduciary obligations are met. Public pension attorneys continue to view governance excellence as the foundation upon which all other legal and investment decisions rest

Additional Issues Continue to Demand Attention

The conference also reflected the increasingly complex environment surrounding institutional investing. One prominent session addressed the impact of new laws and regulations affecting alternative investments, including outbound investment restrictions, national security-related regulations, “countries of concern” legislation, anti-boycott measures, and state laws requiring investment decisions to be based on pecuniary factors. The discussion highlighted the growing intersection of investment management, geopolitics, and public policy.

Other investment-focused sessions examined negotiating private fund documentation, while one panel explored the emergence of retail investment opportunities in private markets and the implications for institutional investors and fiduciaries. These topics underscore a broader trend: public pension attorneys are increasingly engaged in investment transactions in new ways, helping systems navigate both traditional fiduciary concerns and emerging regulatory pressures affecting private markets. Another notable theme was the ongoing focus on pension funding and benefit administration. Sessions examined strategies for reducing unfunded actuarial accrued liabilities; addressed employer withdrawals, mergers, outsourcing arrangements; and covered corrections of plan failures under SECURE 2.0, tax qualification requirements for governmental plans, federal garnishments, and IRS levies. The breadth of these sessions suggests that pension counsel continue to devote significant attention to maintaining plan qualification, ensuring accurate benefit administration, and addressing funding challenges—areas that remain central to the long-term sustainability of public retirement systems.

Conclusion

The 2026 NAPPA Legal Education Conference suggests that public pension attorneys are navigating an environment characterized by rapid technological change, increasingly complex investment regulation, evolving enforcement priorities, and continuing pressure to maintain sound governance, funding, and fiduciary practices.

For public pension systems, trustees, asset managers, and service providers, the conference agenda offers a useful roadmap of the issues likely to occupy public pension legal departments and outside counsel throughout the coming year. Far from replacing traditional pension law concerns, emerging issues such as AI and geopolitical investment restrictions are being layered onto an already demanding fiduciary and regulatory framework—expanding the role of public pension counsel as both trusted legal advisor and strategic risk manager.

On a personal note, this conference marked the conclusion of my term as President of NAPPA. It was an honor to serve alongside an exceptional board and membership dedicated to advancing education, collaboration, and professional excellence within the public pension community. The discussions throughout the conference reinforced the critical role public pension attorneys play in helping retirement systems navigate an increasingly complex legal and regulatory landscape.

Reprinted with permission from National Conference on Public Employee Retirement Systems (NCPERS). Originally published in NCPERS PERSist Spring 2026 magazine.

AI capability is advancing rapidly. As it improves, pension funds and their vendors are embedding AI into core investment and operational functions to enhance returns and improve efficiencies.

AI tools now draft investment memoranda, summarize manager reports, model portfolio risk, analyze actuarial data, support benefits calculations and automate member communications. Fund staff also use generative AI to accelerate research, interpret statutes and draft internal documents.

Given these efficiencies, the question is no longer whether pension systems will use AI. It is how quickly they will establish AI governance and how often those policies should be reassessed. For pension fund leadership, AI is not simply a technology initiative. It is a fiduciary imperative.

If AI produces an incorrect benefits calculation, who catches it? If a model misinterprets statutory language governing eligibility or cost-of-living adjustments, who verifies the result? If staff upload confidential member data into a public AI tool, what are the privacy implications? If an investment decision is influenced by an AI-generated summary that omits key risk factors, how is that detected?

These risks are not theoretical. McKinsey reports that 88% of organizations now use AI in at least one business function, yet only about one-quarter have mature AI governance frameworks. That gap between adoption and oversight is particularly concerning for pension systems, which manage substantial assets and highly sensitive member data under strict fiduciary obligations.

AI Exposure Extends Beyond Investments

AI conversations often focus too narrowly on portfolio analytics. Pension system risk is far broader, extending across benefits administration, statutory compliance, data privacy and cybersecurity, investment oversight, board reporting and public disclosures. AI is already influencing each of these functions, and errors can go undetected and scale quickly.

Large language models can generate confident but inaccurate outputs that may oversimplify statutory language or summarize complex documents while missing material details. If not properly configured, they may also retain or expose sensitive data. In a pension system, such failures have tangible consequences: incorrect payments to beneficiaries, misstated disclosures, regulatory scrutiny, litigation exposure and reputational harm.

Fiduciary oversight requires understanding the tools that influence decisions, define boundaries of use, train personnel, and ensure vendor standards. Governance is not about slowing innovation; it is about preventing avoidable risk and demonstrating institutional oversight.

A “No AI” Policy Is Not a Solution

Refusing to adopt AI or discouraging its use is not effective oversight. Employees are already experimenting with AI tools. Research by Microsoft and LinkedIn found that 75% of knowledge workers use AI at work, and 78% of those users do so without employer approval, significantly increasing the risk that sensitive information will be shared with unvetted platforms.

Gartner projects that by 2030, 40% of enterprises will experience security or compliance incidents tied to unauthorized or “shadow AI” use. Prohibitions tend to drive usage underground rather than eliminate it. The absence of a policy does not prevent AI use; it prevents visibility into AI use. For pension funds, that visibility is essential.

AI Governance Is a Risk Management Function

An effective AI policy should answer three questions: Where is AI being used? What risks does that use create? Who is accountable for oversight?

Leading funds are beginning to evaluate AI use enterprise-wide and developing internal AI policies and governance frameworks. Essentially, AI deployment must be accompanied by institutional guardrails.

Pension system governance discussions should align with fiduciary duties: Is AI use consistent with statutory requirements? Are outputs verified before influencing decisions? Are member data protections clearly defined? Is the board receiving updates on AI initiatives and associated risks?

This requires acknowledging that AI is already embedded in work product and bringing it within formal oversight structures. In many cases, this also means engaging experienced governance and fiduciary advisors who understand both pension system operations and the legal obligations.

Practical First Steps

AI governance should be principle-based and dynamic. Initial steps include conducting an enterprise-wide inventory of AI use, clarifying privacy and confidentiality rules, establishing review protocols for AI-generated outputs and assigning executive-level accountability. Importantly, AI risk should be integrated into existing risk management and compliance structures rather than treated as a standalone initiative. The technology sector’s mantra “move quickly and break things” is incompatible with the mission of pension systems. The retirement security of public employees depends on stability, accuracy and trust. Adopting a dynamic AI policy is not about resisting innovation. It is about protecting beneficiaries, preserving institutional credibility and ensuring that technological progress advances—rather than undermines—fiduciary duty.

In September, the Securities and Exchange Commission (SEC) withdrew 14 proposed rules dating from the Biden administration. The announcement represented a significant shift in the agency’s regulatory approach to the financial sector under President Trump’s SEC Chair Paul Atkins. Specifically, withdrawing a rule that required investment advisors to “eliminate or neutralize” conflicts of interest arising from their use of artificial intelligence highlights major differences between the Biden and Trump administrations’ assessments of the threat posed by predictive analytical technologies and how best to regulate this rapidly advancing area.

Under the Biden administration, then SEC Chair Gary Gensler rang the alarm bell about the potential impact of artificial intelligence on the financial markets. Prior to becoming SEC Chair, Gensler was a professor at MIT and co-authored a research paper arguing that uniform data and model designs would result in financial market risks. He explained “models built on the same datasets are likely to generate highly correlated predictions that proceed in causing crowding and herding” leading to systematic risks that could unleash a financial crisis. As an example, Gensler cited the 2008 financial crisis, where systemic risk created by the financial sector’s heavy reliance on three major credit agencies to regulate collateral obligations contributed to a global crash. In an August 2023 interview with The New York Times, then-Chair Gensler predicted that just a few AI companies would create financial models undergirding the economic system, setting up global markets for a financial crash. “This technology will be the center of future crises, future financial crises,” Gensler said. “It has to do with this powerful set of economics around scale and networks.”

Not surprisingly, the SEC under Gensler proposed in July 2023 a rule that would have prevented broker-dealers or investment advisors from using AI that resulted in investment firms placing their own interests ahead of investors. Under the proposed rule, investment firms were also required to adopt and maintain written policies and procedures that would prevent such violation of the policy. In addition, the firm would have to comply with certain record-keeping requirements.

The proposal was criticized for several reasons. First, opponents argued the rules would place a serious compliance burden on investment firms. Second, opponents argued that such a proposal hurt the development of new technologies and innovation. Finally, opponents argued the definition of “covered technology” (as applied to AI) was too broad. For example, “covered technology” would include regulating a simple technology like Excel spreadsheets.

The Trump administration and SEC Chair Atkins have taken positions diametrically opposed to Gensler’s, focusing more on enabling innovation than on enforcement. In July, President Trump announced an “AI Action Plan” that described regulation as a barrier to AI innovation. In August, Chair Atkins announced the creation of an AI Task Force consistent with the administration’s approach. The announcement said that the Task Force would “remove barriers to progress” and “focus on AI applications that maximize benefits.” Furthermore, the SEC under Atkins is examining whether investment firms possess the proper governance procedures to monitor AI technologies as opposed to eliminating any conflicts of interests associated with new technologies.

Even those who are proponents of AI’s capabilities believe that AI poses a real threat to financial stability and continue to sound the alarm. In July, OpenAI CEO and ChatGPT co-creator Sam Altman warned about a “significant, impending fraud crisis brought about by artificial intelligence.” The effectiveness of the new administration’s focus on proper disclosure of investment firms’ AI use and governance—as opposed to eliminating conflicts on new technologies—can only be determined over the course of time.

Artificial Intelligence (AI) is transforming the way companies work by streamlining healthcare, automating financial services, and reshaping industries at a pace unlike anything we’ve ever seen. With rapid growth comes risk: some businesses may be tempted to exploit the complexity and novelty of AI to mislead regulators, harm investors, overstate capabilities, or defraud government programs. Take for example Rimar Capital USA, Delphia (USA) Inc. and Global Predictions, all of whom have incurred substantial monetary penalties for false and misleading statements about their purported use of AI.

AI Is Fueling New Fraud Schemes

Fraud tied to AI can take many forms. Here are a few hypothetical examples:

Healthcare & Insurance

• Scheme: Inflate bills for “AI-powered” diagnostics, imaging tools, or predictive analytics that are either unproven, don’t function as described, or replicate existing manual processes.
• Example: A company markets an AI system that claims to detect early-stage cancers with 95% accuracy, but in practice it performs no better than standard methods. Insurers and patients are billed at a premium.

Government Contracts

• Scheme: Overstate capabilities of AI to win defense, intelligence, or administrative contracts. They may claim autonomous decision-making, real-time data analysis, or superior predictive accuracy that does not exist.
• Example: A defense contractor exaggerates that its AI surveillance tool can detect threats with near-perfect accuracy, leading to a multimillion-dollar contract award. Later, the system produces error-prone results.

Financial Services & Technology

• Scheme: Misrepresent the use of AI to investors, regulators, or customers to inflate valuations, justify price increases, or secure venture capital.
• Example: A fintech firm touts an “AI-driven risk model” for loans, but the model is a basic regression analysis with human overrides. Investors are misled about technological edge and growth potential.

Data Misuse & Compliance Fraud

• Scheme: Cut corners on compliance, bias testing, or data privacy, while telling regulators and customers its AI tools are ethical, fair, and privacy-reserving.
• Example: A social media company claims its recommendation algorithm is “bias-free” and compliant, but internal audits show it systematically favors certain content and collects unauthorized personal data.

Cross-Cutting Themes

While these sector-specific examples highlight different forms of AI-related fraud, they are not isolated. Common threads run across industries:

• AI as a Buzzword: Just as “blockchain” and “crypto” were misused in past fraud waves, “AI” is being deployed as a hype-driven label to lure capital, contracts, and credibility.
• Enforcement Lag: Regulators are still developing AI-specific frameworks, creating opportunities for misrepresentation before oversight catches up.

Have You Witnessed AI-Related Misconduct?

If you have non-public information about AI-related misconduct or know of false statements made to the marketplace or government about AI products or services, your information may form the basis of a whistleblower case. Federal and state whistleblower programs and laws, including the False Claims Act and the Dodd-Frank Wall Street Reform and Consumer Protection Act, offer protections for those who come forward, and in certain circumstances, financial awards for exposing fraud.

Why act now? Because AI is moving faster than the law. Regulators and courts rely heavily on individuals who have the courage and knowledge to come forward and report wrongdoing. Whistleblowers have been essential in protecting taxpayers, patients, consumers and investors in every major wave of technological change. AI is no different and your knowledge could make all the difference.

The Summer 2025 issue of the Shareholder Advocate, our quarterly securities litigation and investor protection newsletter, features articles on:

• Managing corporate risk in the AI boom
• UFC fighters’ $375 million antitrust settlement
• The role of an amicus brief in the Supreme Court’s to dismiss an appellate review of class certification as improvidently granted
• Initial approval of investors’ $27 million settlement with InnovAge
• An interview with Fiduciary Focus columnist Suzanne Dugan on her new role as president of the National Association of Public Pension Attorneys

Christine Webber, co-chair of our Civil Rights & Employment practice, has been invited to speak at the National Employment Lawyers Association at the Marriott Baltimore Waterfront in Baltimore, Maryland from June 25-28th, 2025.  

Christine’s panel program, Transforming the Workplace: AI, Technology, and State Legislation, is scheduled for Friday, June 27th at 3:00 pm EST.  

Christine’s panel will discuss state laws governing the use of artificial intelligence (AI) technology in the workplace. Since there is no federal law establishing guidelines on AI technology implementation in the work environment, it’s up to states to address on a state-by-state basis. Employment lawyers must work to ensure that AI does not become another tool of systemic discrimination.  

Moderator: Shelby Leighton, Senior Attorney, Public Justice

Panelists:  

• Matthew U. Scherer, Senior Policy Counsel, Workers’ Rights and Technology 

• Christine E. Webber, Partner, Cohen Milstein Sellers & Toll, PLLC  

One can hardly open the business section of a newspaper today without immediately seeing an article about Artificial Intelligence (“AI”). Companies use the term to refer to different things, but one of the most prominent and frequently discussed types of AI used in businesses today is “generative AI.” Generative AI trains AI to absorb large amounts of data patterns and structures— so-called large-language models—so that it can learn and eventually generate new data with characteristics that are similar to the original data. Generative AI tools include popular chat-bots like ChatGPT and Claude, and search engines like Perplexity. Companies such as Google, Microsoft, Apple, and Meta have also built AI functionality into their core products.

As a firm committed to advocating for good corporate governance and the rights of shareholders, Cohen Milstein has dedicated substantial resources to understanding how AI tools can be used to supercharge our work to achieve the best results for our clients. In this article, we will share insights about how AI tools can be used by legal advocates and pension funds.

Use of AI as Advocates for Shareholders

We are at the dawn of the AI age, and many law firms have begun exploring how best to use AI to advance their clients’ interests. One simple but powerful function of AI tools is to generate accurate summaries of lengthy documents. Enforcing the securities laws often involves the review of lengthy documents, such as public companies’ filings with the Securities and Exchange Commission. Generative AI tools can quickly summarize those documents and the tools can also understand natural-language questioning about those documents, which allows our attorneys and experts to put their deep substantive knowledge to use in tandem with the AI technology to efficiently identify the most salient points.

Another important role we serve is to thoroughly investigate reported corporate wrongdoing to understand whether our institutional investor clients have been impacted. AI can accelerate our ability to conduct factual research about large numbers of companies and their officers and directors, by quickly answering numerous questions. To be sure, AI’s factual output cannot be independently relied upon due to the persistent problem of “hallucinations”—i.e., the system confidently misstating the facts. Nonetheless, AI’s factual output is often largely correct, and using it as a starting point (always coupled with independent factual verification) can accelerate our research and catalyze our ability to quickly understand an industry, company, or set of individuals who may have harmed shareholders.

Use of AI Within Pension Funds

Potential applications of AI extend far beyond the legal realm, offering transformative opportunities for our clients in various sectors, including pension funds. AI can enhance investment strategies through sophisticated algorithms that predict market trends, identify investment opportunities, and manage risks with greater precision thereby enhancing accuracy, efficiency, and financial stability. AI-driven solutions can also streamline administrative processes.

One of the primary advantages of AI in pension fund management is its ability to analyze vast amounts of financial data rapidly and accurately. While not necessarily something that is possible through chatbots such as ChatGPT, AI algorithms can identify patterns and trends that human analysts might miss, enabling more informed investment decisions that can help maximize returns on pension fund investments.

Risk management is another critical area where AI can make a substantial impact. Machine learning models can simulate various economic scenarios and stress-test portfolios, helping fund managers to anticipate potential risks and adjust their strategies accordingly. This proactive approach to risk management can safeguard the pension funds’ assets, providing more stability for the beneficiaries.

In addition to investment and risk management, AI can streamline the administrative processes associated with pension fund management. Tasks such as tracking contributions, managing payouts, and ensuring regulatory compliance can be automated using AI-powered tools. This automation reduces the likelihood of human errors. Importantly, using AI does not equate to a loss of jobs for humans; instead, it enhances the roles of those previously managing these tasks and directs resources to other important work.

In conclusion, incorporating AI into pension fund management offers a range of benefits, from improved investment strategies and risk management to more efficient administrative processes. Harnessing the power of AI may help pension funds better secure the financial futures of their pensioners. As technology continues to advance and with close oversight and testing, the potential for AI to transform pension fund management will only grow, promising even greater efficiencies and financial stability for public servants, while allowing human workers to focus on other valuable contributions.

Briana O’Neil interviews Poorad Razavi of Cohen Milstein about his experience litigating vehicle cases as a plaintiff’s attorney, along with the challenges every litigator, both plaintiff and defense, will have to navigate as technology advances.  In particular, they discuss:

1. How have new automotive technologies — self-driving cars and AI impacted your practice?
2. With the rise in autonomous vehicle cases, litigators are bound to see new and unique issues. Poorad describes some of the emerging issues.
3. What do litigators need to familiarize themselves with to effectively handle these new cases?
4. When it comes to seeking experts in a case, what kind of expertise should be considered? What about new expert strategies?
5. What new challenges do you foresee in these cases and how can litigators prepare?

Listen to the Insider Tips Podcast for this timely conversation.