When Operations Beat Tax: How AI-Ready Trust Companies Win the Next 18 Months

The Swiss referendum of 30 November 2025—rejecting a 50% inheritance tax by 78.3%—was celebrated as a victory for Switzerland's competitiveness. But as I watch the patterns shaping ultra-high-net-worth behaviour across jurisdictions, I see trustees misreading the game. The centres gaining mandate share aren't the lowest-tax; they're the most operationally capable.

While Switzerland defended its fiscal position, competitors accelerated infrastructure. Dubai added over 200 family-owned businesses in 2024, with the top 120 families now overseeing more than USD 1.2 trillion in assets. Singapore grew from roughly 400 single family offices in 2020 to more than 2,000 by 2024. Luxembourg commands EUR 8.7 trillion in fund assets. 

None of these centres won on tax rates alone. They won on digital infrastructure, regulatory clarity, and operational speed.

The message for trust company CEOs is unambiguous: mandate allocation is now driven by 48-hour formation targets for standardised structures, real-time consolidated reporting, multi-custody visibility, and AI-supported compliance workflows. Tax optimisation still matters—but it no longer decides which trustee wins the mandate.

The Operational Divide Creating Valuation Gaps

Recent transactions expose where value concentrates. JTC Group agreed to be acquired by Permira at approximately 26.2x adjusted EBITDA, reflecting its operational scale and AI-ready platform positioning. Opera Group is scaling beyond USD 71.6 billion in assets under administration through platform-first acquisitions. GTCR's purchase of Fiduciary Trust Company represents another premium-multiple transaction into the UHNW space.

The gap is explicit in recent deal ranges: high-single to low-double-digit EBITDA multiples for manual, legacy operators versus high-teens to mid-20s EBITDA multiples for scaled, tech- and AI-enabled operational platforms.

This is not a market mystery—it is an operational referendum. Acquirers are paying for operational infrastructure that scales without proportional risk increase. That infrastructure requires AI governance, not just AI tools.

I see trustees facing three paths: position for premium acquisition through technology, data architecture, and AI governance (as Vistra has done with its Cosmos platform); become the consolidator via platform-led M&A (Opera's path through its Meritus and Accuro acquisitions); or defend a niche with director-led client delivery supported by modern infrastructure (such as Sequent). Doing nothing is self-selection into the discount category.

Why Past Modernization Efforts Failed

Have you upgraded to a modern CRM? Implemented digital document management? Launched an upgraded client portal? These efforts improve efficiency—but not competitiveness. They speed up manual processes without creating intelligent operations. Did you install compliance software without machine learning? It flags risks but cannot learn patterns.

MIT Project NANDA found in 2025 that approximately 95% of enterprise AI initiatives fail to reach sustained production due to implementation and integration gaps. The trustees commanding premium valuations understood this distinction and rebuilt operational architecture with AI at the core—not through pilots that stall, but through production systems that scale.

IQ-EQ has advanced its Cosmos platform—enabling predictive analytics for cash flows and capital calls—and achieved ISO 42001 certification in December 2025, the global standard for responsible AI management. This certification demonstrates genuine AI governance beyond promises, helping build trust, mitigate risk, and scale AI initiatives with confidence. Ocorian's partnership with Landytech delivers real-time, multi-custody portfolio visibility. JTC emphasises AI-enabled efficiency in private markets. Vistra's Global Expansion Platform and AI assistant GENI support automated onboarding and lifecycle management for 30,000+ entities in 40+ jurisdictions.

This is the operational layer UHNW clients now benchmark across jurisdictions. When a Swiss bank client evaluates their trustee against Dubai or Singapore alternatives, they are not comparing tax rates only. They are comparing onboarding speed, reporting transparency, and AI-enabled compliance workflows.

How Trustees Compete Across Jurisdictions

Switzerland's strengths lie in stability, banking dominance, and brand credibility. But slower onboarding, legacy reporting, and conservative change cycles create openings. Trustees win through speed, real-time transparency, AI-driven compliance, and multi-custody analytics.

Singapore offers MAS regulation, deep family office ecosystem, and institutional credibility. Yet heavier formalism and slower adaptation cycles provide opportunities for trustees who deliver agility, personalised experience, flexible structuring, and rapid AI deployment within MAS frameworks.

Dubai brings 0% tax on most personal income, speed of establishment, and DIFC modern frameworks. However, governance perception gaps and uneven compliance sophistication mean trustees win with stronger fiduciary governance, rigorous compliance, and globally recognised reporting standards.

Across all three, trustees do not compete on tax. They compete on operational trustworthiness—the ability to deliver speed, transparency, and governance simultaneously.

What the market misunderstands

The market gap exists because the trust industry's operational transformation problem cannot be solved by generalist AI consultants,or off-the-shelf software vendors. Each approaches the challenge from the wrong angle.

Internal builds fail because trust companies lack the architectural expertise to integrate AI into fiduciary workflows without creating governance gaps. MIT's finding that 95% of enterprise AI initiatives stall reflects this reality—most organizations build AI capability without operational integration methodology.

A new category of fiduciary-operations specialists has emerged to occupy this gap—architecting AI integration specifically for trust companies. Our approach is surgical: we analyze your current operational architecture across the four dimensions that determine AI implementation readiness, identify the 2-3 immediate-impact interventions that will generate board-level ROI proof points, then design the integration architecture that layers AI onto your existing systems without wholesale replacement.

The methodology is designed for one outcome: move your trust company from the 95% that stall in pilots to the 5% that reach production—and position for premium valuation in the process.

Three Strategic Interventions

1. Understanding AI Applications in Trust Operations

KYC automation can compress 20–25-day onboarding cycles to under one week for standard cases. AML screening now uses pattern detection across transactional and relational data. Real-time multi-custody consolidation with AI-generated narratives is available through modern platforms. These are not theoretical—they are operational realities at firms commanding premium valuations. Fiduciacorp maps AI capability to fiduciary workflow, identifying where automation creates measurable advantage versus where it introduces unacceptable risk.

2. Integration Architecture That Augments Rather Than Replaces

Modern AI implementations layer onto existing systems via modular API integration: automated data extraction feeding compliance systems, AI-generated narratives enhancing reporting platforms, intelligent routing improving client service workflows. The constraint is no longer technology availability—it is strategic clarity about deployment. Fiduciacorp designs integration architecture that preserves institutional knowledge while introducing intelligent automation.

3. Cost Structures That Justify Board Approval

AI implementations that deliver measurable ROI begin with immediate-impact domains: onboarding automation, compliance efficiency, reporting velocity. Pilot programs prove value before scaling. The pattern is consistent across successful implementations: start small, prove capability, scale deliberately. Boards that understand this sequence approve budgets. Fiduciacorp structures transformation as proof-of-concept pilots that generate board-level conviction before requesting transformation capital.

Why AI Governance Now Determines Acquisition Readiness

Boards evaluating trust company acquisitions now assess AI governance before reviewing client books. The reason is structural: AI failures create existential fiduciary risk, while manual process failures create operational delays. When Permira valued JTC at approximately 26x EBITDA, they paid for operational infrastructure that scales without proportional risk increase.

Modern AI governance frameworks cover four domains. Risk appetite defines acceptable error rates and human override protocols. Model explainability ensures trustees can justify AI-driven decisions to regulators and clients. Data governance protects client confidentiality while enabling analytics. Vendor oversight manages third-party AI dependencies. IQ-EQ's December 2025 ISO 42001 certification demonstrates what board-level AI governance looks like in practice. Trust companies without comparable frameworks are not acquisition targets—they are integration risks.

The Measurement Framework CEOs Need Now

Most trustees cannot answer basic questions about their operational readiness. How long does standard onboarding take from KYC submission to entity activation? What percentage of compliance alerts require human review versus automated clearance? How many hours of senior staff time go into producing monthly consolidated reporting for a typical UHNW client?

These metrics now determine valuation multiples. The diagnostic framework trustees need measures onboarding velocity (days from complete KYC submission to operational entity, target under 7 for standard structures), reporting automation (percentage of client reporting generated without manual data consolidation, target above 80%), compliance efficiency (ratio of compliance staff to clients under administration, where AI-enabled firms run 3-4x higher ratios), and digital asset readiness (operational capability to administer digital assets by Q2 2026, with detailed implementation timeline).

Firms scoring above 70% across these dimensions are acquisition-ready. Firms below 50% face material valuation discounts unless they can demonstrate credible transformation roadmaps with board-approved budgets and timelines.

The 18-Month Window

Global AI adoption in organisations now sits in the high-70s to high-80s percent range. Yet only a minority of fiduciary firms have scaled beyond pilots. This creates the window.

During the next 18 months, formation timelines that once took weeks are being pushed toward 48–72-hour execution in leading platforms. Consolidated multi-custody reporting is becoming standard. Digital asset integration is moving from optional to expected. Boards are embedding AI governance into fiduciary oversight. The operational gap between early movers and late movers is widening rapidly.

Early movers build operational moats. Late movers inherit the narrative of inaction.

Transform or Be Consolidated at a Discount

Switzerland built trust on stability. Singapore built trust on regulatory precision. Dubai built trust on speed. Permira paid approximately 26x EBITDA for operational readiness—not geography.

The trust industry is signalling the next phase: operations beat tax. AI determines operations.

Transform in the next 18 months—and position for premium acquisition, not discount consolidation.

Frédéric Sanz is the author of “AI Unleashed for Trustees & Family Offices” and advises fiduciary boards on AI readiness and operational governance.