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The Trust AI Framework™
Resilient AI Governance.
Strategic Clarity.
Human Judgment.
AI adoption is moving faster than traditional governance can follow, creating "Cognitive Debt" and enterprise risk. We help APRA-regulated institutions navigate AI compliance through a structured, methodology-led approach.
Stay Human in the AI Revolution.
01 — The Problem
Cognitive Debt Is the Hidden Risk
on Your Balance Sheet
on Your Balance Sheet
Most
APRA-regulated entities are adopting AI tools
faster than governance frameworks can mature
faster than governance frameworks can mature
0
number of "AI accountability" exceptions
under the FAR personal liability regime
under the FAR personal liability regime
Boards are signing off on AI strategies they cannot audit. CROs are inheriting risk profiles they cannot map. And under CPS 230 and the Financial Accountability Regime, personal liability doesn't pause while governance catches up.
Cognitive Debt™
The accumulating gap between the pace of AI adoption and the organisation's capacity to govern it. Left unaddressed, it compounds — creating regulatory exposure, decision fragility, and operational blind spots that no single audit can resolve.
02 — The Intellectual Property
Three Pillars of the Trust AI Framework™
A codified system for governing intelligent systems — built from decades of enterprise transformation experience in financial services.
Pillar I
AI Governance
The Controls.
Codifying oversight for enterprise AI. We map your AI stack to regulatory requirements — CPS 230, FAR, BFIM duty — to ensure operational resilience and third-party risk mitigation.
Outputs
AI Governance Readiness Scorecard, Regulatory Gap Analysis, Accountability Mapping
Pillar II
Responsible Innovation
The Velocity.
Accelerating GenAI adoption without compromising ethics. We build the safety nets that allow your team to move fast without breaking compliance — including safety wrappers for member-facing AI.
Outputs
GenAI Safety Wrapper, Ethical Use Policy, Innovation Guardrails
Pillar III
Human Judgment
The Clarity.
Protecting the "Human-in-the-Loop." We provide the cognitive tools and frameworks to ensure AI augments — rather than replaces — critical executive decision-making.
Outputs
Cognitive Clarity Toolkit, Decision Integrity Framework, Executive AI Literacy Program
03 — The Methodology
Four Phases. One Transformation.
The Trust AI Framework™ is deployed through a structured engagement model — from initial diagnostic to embedded capability.
01
Assess
Map the terrain.
AI Governance Readiness Scorecard across 11 pillars. Baseline your cognitive debt. Identify regulatory gaps and accountability blind spots.
Typical: 2–3 weeks
02
Activate
Build the controls.
Design and implement governance structures, accountability maps, and compliance frameworks tailored to your regulatory obligations.
Typical: 4–6 weeks
03
Embed
Change the culture.
Train your teams. Install decision frameworks. Build the internal muscle for ongoing AI governance — not just a one-time fix.
Typical: 6–8 weeks
04
Scale
Compound the advantage.
Extend the framework across business units. Establish independent verification. Position governance as a competitive differentiator.
Typical: Ongoing retainer
04 — The Diagnostic
The Fiduciary AI Health Check
Every engagement begins with the AI Governance Readiness Scorecard — an 11-pillar diagnostic that maps your institution's AI maturity against regulatory expectations.
The scorecard produces a clear, board-ready view of where cognitive debt has accumulated and where governance gaps create personal liability exposure under FAR.
APRA CPS 230Operational Resilience
FARPersonal Liability
BFIM DutyBest Financial Interests
SPS 515Strategic Planning
AI Governance Readiness
Sample OutputAccountability Mapping
Third-Party AI Risk
Model Governance
Ethical AI Policy
Board-Level Oversight
Data Governance
Human-in-the-Loop
Incident Response
Regulatory Alignment
Change Management
Innovation Pipeline
The Architect
Built from decades of high-stakes financial services transformation.
17+
Years in Enterprise Tech
EY
Technology Consulting
IBM
Enterprise Delivery
MIT
Digital Business Strategy
"After 17+ years leading enterprise transformation across global consulting and technology firms, I recognized a growing gap: organisations were prioritising AI speed over cognitive safety. The Trust AI Framework was developed to bridge that gap."
Anam Munshey Thomas is the founder of Trust AI™ and architect of the Trust AI Framework. A senior leader in technology consulting across global firms including EY and IBM, she holds an MBA and studied Digital Business Strategy at MIT Sloan.
The Framework is a codified methodology born from decades of high-stakes financial services experience — designed to give leaders the "Cognitive Clarity" required to govern intelligent systems effectively.
Author: "The AI-Friendly Wellness Journal"
Begin
Your AI governance gap
is someone's personal liability.
The Trust AI Framework™ starts with a single conversation. A 30-minute Framework Alignment Session to assess where your cognitive debt sits — and what it will cost if it compounds.
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