The Pressure Points: Legal, Compliance, Risk and Data in Financial Services
Week 3: AI Governance
Continuing The Pressure Points, my mini-series exploring what is actually happening across legal, compliance, risk and data in financial services. Each week brings together two posts: a short market view, followed by a deeper dive into the themes coming through from firms, regulators and advisory work. The aim is to keep it useful, commercially relevant, and focused on what feels real.
Market View: AI Is Becoming a Governance Issue
Next one from me in this series, and one area that feels harder and harder to ignore is AI governance.
A lot of the early conversation was about opportunity. How can we move faster? Where can we automate? How much efficiency can we unlock?
That is still part of it. But the more interesting shift now is that AI is becoming a legal, compliance, risk and data issue at the same time. Because once firms move beyond experimentation, the questions get more serious.
What data is this using? Can the output be explained? Who is accountable for it? What happens if it goes wrong? How comfortable would we be defending it internally or externally?
That is why I think AI is becoming less of an innovation topic and more of a governance topic. And whenever that happens in financial services, capability becomes a real issue. Not just technical capability. Governance capability.
People who can connect regulation, data, risk and business reality are going to become more valuable quite quickly. Feels like one of the clearest areas where the market is moving faster than a lot of team structures.
Are firms in your world treating AI as a productivity tool first, or a governance challenge first?
Deeper Dive: From Technology Discussion to Accountability Discussion
Following on from my post earlier this week on AI governance, this is the part I think matters most. In financial services, AI is moving quite quickly beyond being an innovation conversation.
The harder questions now sit around governance, accountability and control.
Because once AI starts being used in higher-impact areas, the issue is not just whether the tool works. It is whether firms can explain it, govern it and stand behind it.
That is where things get more serious.
Can the output be explained? Is the underlying data good enough? Who is actually accountable? How does it sit alongside existing model risk and control frameworks? How exposed is the business to third parties in the AI and cloud stack?
That is why I think AI is becoming such an important issue across legal, compliance, risk and data teams.
The challenge is not just adoption. Most firms want to move. The challenge is whether they have the governance in place to move with confidence in a regulated environment.
And that is where the capability gap starts to show up. Not just people who understand the technology. People who can connect regulation, governance, data, risk and business reality in a way that actually works. That feels like one of the clearest market themes right now.
AI may start as a technology discussion, but in financial services it ends up becoming an accountability discussion quite quickly. Are firms in your world clear on who owns AI governance yet, or is that still being worked through?
This is part of The Pressure Points, a weekly series exploring what’s really happening across legal, compliance, risk and data in financial services.
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