Law360 examines how AI is reshaping the employee benefits landscape, featuring Darrow's Shelbi Lifshitz alongside defense attorneys who offer a more cautious view of the technology's role in ERISA litigation.
The piece is structured around three themes. The first is AI as a litigation identification tool. Lifshitz explains that Darrow uses public data to detect fact patterns indicative of legal violations across practice areas including ERISA — presenting those findings to law firms and letting them litigate. She is notably candid about the limits of this approach: on excessive recordkeeping fee cases specifically, she acknowledges legitimate criticism that the public data required to make such cases isn't available, and confirms Darrow focuses on investment mismanagement cases rather than recordkeeping fee claims.
The counterpoint comes from David Levine of Groom Law Group, who describes AI in benefits as "evolutionary, not revolutionary" — useful for auditing and automation but not a definitive answer to identifying ERISA violations. He notes that Form 5500 data fields can generate results that appear significant but are misleading without deeper context, such as distinguishing between recordkeeping fees and other service provider compensation bundled under the same code.
The second takeaway is discriminatory claims processing. Tom Hardy of Reed Smith flags growing litigation risk for health plan administrators using AI in claims decisions — raising the question of whether AI-driven claims processing can satisfy ERISA's fiduciary duty standard, particularly when the technology operates as a "black box" whose inner workings are difficult to interrogate or explain in court.
The third is cybersecurity. The expansion of AI in benefits administration brings with it a corresponding expansion of sensitive data, creating new exposure for recordkeepers and plan administrators if that data is breached.
