Artificial intelligence is reshaping financial services at a pace that is difficult to overstate. The opportunities are real. So are the responsibilities that come with them.
Across the sector — from large institutions to boutique management companies — AI tools are being adopted to improve efficiency, reduce manual workloads, and sharpen decision-making. The direction of travel is clear and largely positive. But as adoption accelerates, one question keeps surfacing: are organisations building the governance frameworks to match?
In my view, this is the defining challenge for financial services professionals right now. Not whether to use AI — but how to use it responsibly, accountably, and with the right controls in place.
The Opportunity Is Genuine
For management companies administering trusts, foundations, GBCs, and authorised companies, AI holds real promise. Document processing, compliance monitoring, KYC workflows, client reporting — these are areas where AI can reduce friction, improve consistency, and free up time for higher-value work.
Used well, AI does not replace professional judgement. It supports it. It allows practitioners to focus on the decisions that truly require human insight — and to serve clients better as a result.
The institutions that will scale AI well are those that govern it from the outset — not as an afterthought, but as a foundation.
The Governance Gap
The challenge is that AI adoption and AI governance are not always moving at the same speed. Tools are being deployed, workflows are being automated, and processes are being supported by AI — often before clear policies exist to define how this should happen, who is responsible, and what safeguards are in place.
This is not unique to any one organisation. It is a broad pattern across the financial services sector, and one that regulators globally are paying increasing attention to. The message from supervisory authorities is consistent: governance must keep pace with adoption. Evidence of oversight, accountability, and control is expected — not just good intentions.
Data protection and AI governance are inseparable. Any responsible approach to AI in financial services must address both — how AI is used, and how client and organisational data is handled within those processes.
Four Pillars of Responsible AI Adoption
- 1Know what you are usingBuild a clear inventory of AI tools in use across your organisation. Understanding your current footprint is the starting point for everything else.
- 2Put a policy in placeA concise, practical AI policy — covering permitted uses, data handling, and approval processes — gives your teams clarity and your organisation protection.
- 3Assign accountability clearlyAI governance requires named owners. Who approves a use case? Who monitors performance over time? Who is responsible when something needs to change? These questions need answers before deployment, not after.
- 4Keep humans in the loopFor decisions that affect clients, regulatory compliance, or financial outcomes, human oversight is not optional. Professional accountability does not transfer to an automated process.
The Fiduciary Standard Remains Unchanged
For those of us working in trust administration, corporate governance, and client-facing fiduciary roles, this point deserves emphasis. The duty of care owed to clients has not been altered by the emergence of AI. The professional and regulatory obligations that define our work remain exactly where they have always been.
What AI changes is the way some of those obligations are fulfilled — not the standard to which they are held. Governance frameworks, policies, and oversight mechanisms ensure that the two remain aligned.
Approached thoughtfully, AI is a genuine asset for the financial services profession. The goal is to embrace it with the same rigour and care that we apply to every other aspect of our work.