Artificial intelligence (AI) is permeating all aspects of the legal practice, and
class litigation is no exception. Recognizing AI’s potentially harmful effects for
legal clients, the American Bar Association’s Standing Committee on Ethics
and Professional Responsibility in 2024 provided guidance in a formal opinion
for attorneys, signaling client disclosure and consent were required to employ
AI in the representation. But the ABA’s opinion did not address or apply to class
litigation, where putative class members and class counsel share no attorney-client
relationship. Indeed, class members presently have little to no means to consent to
or question class counsel’s prosecution of the litigation. AI can change this
dynamic and revolutionize class litigation. A few scholars have already recognized
AI’s potential to provide class members with a critical voice and facilitate the reso–
lution of a greater volume of class claims. But while AI stands to benefit class mem
bers, it can also diminish the quality of their legal representation and negatively
impact their litigation outcomes. Class counsel is required, under Rule 23(g) of the
Federal Rules of Civil Procedure, to adequately represent the interests of absent
class members, but with often conflicting interests, this directive is insufficient to
protect the class from class attorneys’ negligent use of AI.
This Article proposes a novel test within Rule 23(g)’s existing framework to
protect class members from class counsel’s AI misuses. It begins by addressing
AI’s potential impact on the quality of class members’ representation, translat
ing the promises and perils AI presents traditional litigants into the class envi
ronment. The Article then proposes an AI adequacy test aimed at ensuring that
class counsel’s use of AI outputs in the litigation neither negatively affects class
members’ legal representation nor otherwise harms class members. The test
directs courts, empowered under Rule 23(g)’s broad authority, to inquire into
class counsel’s past and intended use of AI in the litigation and assess whether
such use has or will impair class members’ interests. The Article also applies
the AI adequacy test to various hypotheticals and addresses potential criticisms. Ultimately, it demonstrates how the proposed AI adequacy test can provide
class members similar protections as other litigants while incentivizing class
counsel to responsibly employ AI to further class members’ interests.

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