The Fiduciary Vacuum: AI Adoption, Trust Law Erosion, and the Governance Gap in Family Enterprise Succession

What happens when artificial intelligence meets a rapidly evolving fiduciary landscape? In this issue, Matthew Erskine explores the emerging “fiduciary vacuum”—a convergence that may reshape accountability in family enterprise governance.

This article examines implications for advisors working at the intersection of trust design, technology, and family enterprise systems.

FAMILY FIRM INSTITUTE- Two converging trends create an underexamined governance risk for family enterprises: the rapid integration of artificial intelligence into fiduciary decision-making and the systematic erosion of fiduciary protections through interstate trust law competition.

Their intersection produces what this article terms the “fiduciary vacuum”—a structural accountability gap in which AI-powered decision-making operates with diminishing human oversight inside trust frameworks that simultaneously eliminate meaningful consequences for fiduciary failure. For family enterprise advisory teams, this convergence can no longer be ignored.

The AI Transformation of Fiduciary Practice

AI adoption in trust administration and family office operations has accelerated sharply. The UBS Global Family Office Report 2025, drawing on 317 single-family offices averaging more than $1 billion AUM, found that more than 80 percent expect to invest in AI within two to three years, with only 6 percent anticipating no adoption within five years.[1] The RBC and Campden Wealth North America Family Office Report 2025 documented a tripling of AI usage for operational purposes relative to 2024.[2] Current applications span portfolio analytics, automated reporting, scenario modeling, and investment decision support.

“The fiduciary vacuum is not a future risk—it is a present structural condition.”

In legal practice, the Federal Bar Association’s 2025 Legal Industry Report found individual AI usage among trusts and estates attorneys at approximately 25 percent, with firm-wide adoption at 18 percent.[3] The trajectory matters most for governance: commentary increasingly anticipates a shift from AI-as-tool—where a human professional uses a system to support judgment—toward AI-as-agent, where the system initiates, decides, and executes with minimal human involvement.[4] The ABA’s Formal Opinion 512 (2024) holds attorneys fully responsible for AI-assisted work product.[5] These regulatory frameworks, however, assume a functioning fiduciary structure—an assumption that is increasingly unfounded.

The Erosion of Fiduciary Protection in U.S. Trust Law

Interstate competition for trust business has produced systematic legislative erosion of fiduciary protections.[6] The erosion takes several interconnected forms with direct relevance to AI governance.

Elimination of good faith as a mandatory duty. Tennessee has explicitly removed good faith from its list of mandatory fiduciary duties. South Dakota, Delaware, and New Hampshire have adopted formulations that permit trust terms to expand, restrict, or eliminate fiduciary obligations entirely.

Expansive exculpatory provisions. Delaware permits exculpation of trustees for all conduct short of “willful misconduct,” defined so narrowly that it effectively insulates trustees from liability for gross negligence and recklessness—the categories of conduct most likely to characterize inadequate AI oversight.

Directed trusts and fragmented accountability. Forty-seven states authorize directed trusts, appointing third-party “trust directors” to control discrete trust functions. In many jurisdictions, the director need not be a fiduciary, while the directed trustee is exculpated for following the director’s instructions, creating a structural gap in accountability that AI adoption will exploit.

The Fiduciary Vacuum: Where AI Meets Eroded Trust Law

Consider a scenario entirely permissible under current law in several jurisdictions: a corporate trustee administers a perpetually silent, directed trust holding a family’s operating business and investment portfolio. The trust has eliminated good faith, includes broad exculpatory provisions, designates a nonfiduciary trust director for investment decisions, and waives all beneficiary disclosure. The trust director deploys an AI platform that reallocates assets algorithmically without individualized human review. When the AI harms beneficiaries—through algorithmic bias, flawed data, or failure to account for family values—accountability fragments entirely. The trust director is not a fiduciary. The directed trustee is exculpated. The AI is a tool, not a legal person. The beneficiaries do not know the trust exists. No one is responsible.

Behavioral economics deepens the concern. Automation bias, the well-documented tendency to defer to automated systems even when they produce erroneous results, is amplified when governance removes consequences for inadequate scrutiny. Moral hazard intensifies when exculpatory clauses protect fiduciaries from all but willful misconduct: the fiduciary can point to the AI’s recommendation; the AI cannot be held accountable; beneficiaries have no standing to challenge. Silent trust provisions create extreme information asymmetry, and AI opacity adds a second layer: even if beneficiaries had access to information, the system’s reasoning may be opaque to all parties, including the fiduciary who deployed it.

Specific Threat Vectors for Family Enterprises

Operating businesses. Family enterprises embody values, relational commitments, and community obligations that resist algorithmic optimization. The family business literature has extensively documented the tension between financial rationality and socioemotional wealth preservation.[7] An AI evaluating a family operating company through purely financial metrics might recommend a disposition strategy that maximizes near-term value while destroying the socioemotional wealth, stakeholder relationships, and community standing the enterprise represents—with no enforceable duty on the nonfiduciary trust director to weigh these considerations.

Art, collectibles, and cultural assets. Approximately two trillion dollars of art and collectibles are held in private collections, representing 10 to 15 percent of ultra-high-net-worth balance sheets. These assets require stewardship integrating financial management with aesthetic judgment, provenance, and cultural significance. An AI optimizing for portfolio returns might recommend disaggregating a coherent collection. In a silent trust with eroded protections, that liquidation could be irreversible before any beneficiary learns of it.

Multi-jurisdictional holdings. Families with cross-border assets face compounded vulnerability. AI tools may not adequately model the interaction of different trust laws, tax regimes, and fiduciary standards. The ability of trustees to change governing law and decant to more permissive jurisdictions means that protections embedded in the original trust design can be dismantled—silently, algorithmically, and without any beneficiary’s awareness.

Implications for Family Enterprise Advisory Teams

The fiduciary vacuum challenges core assumptions of current advisory practice.

First, trust design and technology governance are no longer separate domains. Trust instrument drafting determines whether AI-driven fiduciary conduct will face meaningful accountability. Advisors who treat these as independent exercises leave a critical gap.

Second, no single regulatory framework is adequate. The ABA, the SEC, and state trust codes each address fragments of this problem. Reliance on any one of them for comfort exposes advisors to gaps the others do not fill.

Third, the integrative advisor’s role must expand. McCullough’s concept of the “integrated advisor” emphasizes mastery, mindset, method, and maturity as the competency stack for effective multidisciplinary coordination.[8] The fiduciary vacuum adds a new dimension: the integrated advisor must now possess sufficient understanding of both AI capabilities and fiduciary erosion patterns to identify where the governance gap exists in a given family’s structure—and to coordinate the technical expertise needed to close it. Advisors who work at this intersection, understanding both the legal mechanisms of fiduciary erosion and the governance dynamics of multigenerational family enterprises, are positioned to address what is, at present, an unserved advisory need.

Conclusion

The fiduciary vacuum is a structural governance gap built from the convergence of two well-documented trends, operating today in trusts being drafted and administered across the United States. The assets most central to family enterprise continuity—operating businesses, collections, and multijurisdictional holdings—are the most vulnerable to the accountability gap this convergence creates. Advisory teams that serve family enterprises must now account for AI governance as an integral component of trust design, succession planning, and family governance work. Families that address this convergence proactively, before a crisis reveals the gap, will be those whose enterprises survive the fiduciary vacuum intact.

References

[1] UBS Global Wealth Management, UBS Global Family Office Report 2025 (May 2025).

[2] RBC and Campden Wealth, The North America Family Office Report 2025.

[3] Federal Bar Association, The Legal Industry Report 2025.

[4] ZwillGen, The Fiduciary in the Machine (2026).

[5] American Bar Association, Standing Committee on Ethics and Professional Responsibility, Formal Opinion 512: Generative Artificial Intelligence Tools (2024).

[6] Hayes, Hunt, Harrington and Lipson PLLC, “The Day That Duty Died,” citing South Dakota Codified Laws § 55-1-6; Delaware Code Annotated, title 12, § 3303; Tennessee Code Annotated § 35-15-105; and the Uniform Directed Trust Act (2017).

[7] Gómez-Mejía et al., “Socioemotional Wealth and Business Risks in Family-Controlled Firms,” Administrative Science Quarterly 52, no. 1 (2007): 106–37.

[8] T. McCullough, “The Rise of the Integrated Advisor,” The Journal of Wealth Management 26, no. 2 (2023): 50–60.