Artificial intelligence has moved from being a novelty experiment to a deeply embedded part of how professional firms operate. It drafts correspondence, reviews data, summarises complex documents, and powers features inside tools your team uses every day, often without anyone thinking of it as “AI” at all.
For solicitors, accountants, mortgage brokers, IFAs, and insurance professionals, this integration has delivered genuine productivity gains. But it has also introduced a new category of risk that many firms have not yet addressed: what happens when an AI system does something it should not?
Not a hypothetical future concern. A practical, present-day question that every firm leader should be able to answer clearly.
The Speed of Adoption Has Outpaced the Speed of Governance
The adoption of AI across professional services has been remarkably swift. Teams experiment with new tools. Features powered by machine learning appear in software updates. Integrations are activated with a single click. Before long, AI is quietly influencing how decisions are made, how client communications are drafted, and how data is processed.
The problem is that most firms have not mapped this adoption with any discipline. There is no central register of which AI tools are in use, what data they access, or what decisions they influence. This is a growing concern we have already explored in our post on whether anyone is actually controlling AI at work, which highlighted how shadow AI creates hidden data and security risks across businesses.
When you cannot see where AI is running, you cannot assess the risk it introduces. And when you cannot assess the risk, you certainly cannot respond quickly if something goes wrong.
Blind Spots Create Compliance Exposure
For firms operating in regulated industries, this lack of visibility is not just an operational inconvenience, it is a compliance liability. Regulators increasingly expect organisations to demonstrate that they understand how AI is being used within their operations and that they can explain what happens when it fails.
Consider a scenario in which an AI tool, embedded within your email platform, drafts a client communication containing inaccurate information. Or a system that analyses financial data introduces an error into a report that feeds into a regulatory filing. Or a tool that summarises case notes omits a critical detail that affects advice given to a client.
In each of these scenarios, the firm bears responsibility regardless of whether a human or an AI system generated the error. The regulator will not accept “the AI did it” as an explanation. They will ask: what controls were in place? Who was responsible for oversight? And why was this not caught before it reached the client?
The Ownership Question That Most Firms Cannot Answer
One of the most revealing tests of AI readiness is a simple question: if an AI tool in your business makes a mistake, who is responsible?
In most professional firms, the answer is unclear. The assumption is often that this sits with IT, but AI touches far more than technology infrastructure. It intersects with operations, client service, finance, marketing, and compliance. It is woven into the business at a level that no single department can own in isolation.
This ambiguity slows response times. When something goes wrong, valuable time is lost establishing who should act, who should communicate, and who should investigate. In a regulated environment, that delay can be the difference between a contained incident and a reportable breach.
Governance, having clear rules, defined responsibilities, and documented accountability is not bureaucracy for its own sake. It is the mechanism that allows your firm to respond decisively when it matters most.
What an AI Emergency Response Framework Looks Like
Building an AI emergency response capability does not require complex new technology. It requires structured thinking applied to a new category of risk. Here is a practical framework that regulated firms can implement:
- Create an AI Asset Register
Document every AI tool in use across your firm. Include built-in AI features within existing software (such as Copilot in Microsoft 365), standalone tools used by individual team members, and any third-party integrations. For each entry, record what data the tool accesses, what outputs it generates, and who approved its use.
- Assign Ownership at a Senior Level
Every AI tool should have a named owner, a senior individual who is accountable for its correct operation and who has the authority to disable it immediately if required. This should not default to IT alone. Ownership should reflect the business function the tool serves.
- Define Your Kill Switch Procedure
For each AI tool, document the specific steps required to disable it. This includes technical steps (deactivating an integration, revoking API access, disabling a feature in admin settings) and procedural steps (who authorises the shutdown, who communicates the decision, who monitors for downstream effects).
- Establish an Incident Communication Plan
If an AI tool causes an issue that affects clients, data integrity, or compliance obligations, your firm needs a clear communication protocol. Who informs the client? Who notifies the regulator? What is the timeline? Having this planned in advance prevents the chaos that accompanies unscripted incident response.
- Test Your Response
An untested plan is not a plan. Run tabletop exercises at least annually. Present a scenario “The AI tool that summarises client case notes has been sending summaries to the wrong internal team for two weeks” and walk through the response. Identify gaps, assign actions, and refine the framework.
Data Governance and AI Are Now Inseparable
AI systems are fundamentally data systems. They consume data, process it, and produce outputs that influence decisions. This means that any weakness in your data governance directly amplifies AI risk.
If your firm does not have a clear picture of where sensitive data is stored, who has access to it, and how it flows through your systems, AI adds another layer of exposure. We recently examined this challenge in detail in our post on whether your data security is keeping pace with your business, which explored the widening gap between perceived security and actual governance in professional firms.
Before layering AI governance on top, ensure the foundations are solid. Know where your data lives. Know who can access it. Know whether the answers would satisfy an auditor.
The Browser Layer: An Overlooked AI Risk Vector
One area that catches many firms off guard is the web browser. Modern browsers increasingly incorporate AI features such as predictive text, smart suggestions, automated form completion, and content analysis. These features can interact with sensitive information displayed on screen without the user actively choosing to share it.
For professional firms handling client-confidential data, this creates a subtle but significant exposure. The browser effectively becomes an AI tool that no one has formally approved or assessed. We explored this risk in our article about how much your browser actually knows about your business, which highlighted why browser security should be part of any firm’s data protection strategy.
Including browsers in your AI governance framework is not excessive, it is a practical recognition of how AI is actually being deployed in the tools your team uses every day.
Regulatory Expectations Are Tightening
The regulatory landscape around AI is evolving rapidly. The UK Government has signalled a clear expectation that organisations should be able to explain how AI is being used, demonstrate that appropriate safeguards are in place, and show accountability when things go wrong.
For firms regulated by the FCA, SRA, ICAEW, or similar bodies, the implications are direct. AI governance is not a separate initiative, it is an extension of the compliance and risk management frameworks you already operate. The principles are the same: transparency, accountability, documentation, and oversight.
Firms that can demonstrate robust AI governance will not only satisfy regulatory expectations but will also build greater confidence among clients. In sectors where trust is the foundation of the client relationship, being able to say “we know exactly how AI is used in our firm, and we have clear controls in place” is a genuine competitive advantage.
Practical Steps You Can Take This Month
AI governance does not need to be a large-scale project. You can take meaningful steps right now to improve your firm’s position:
- Audit your AI footprint: Identify every tool, feature, and integration in your business that uses AI. Include the ones that feel minor, they often carry the greatest hidden risk.
- Assign accountability: For each AI tool, name a senior owner. Ensure they understand the tool’s function, its data access, and the procedure for disabling it.
- Draft a one-page AI policy: You do not need a 50-page governance document. A clear, concise policy covering approved tools, data rules, and escalation procedures is far more valuable than a lengthy policy that no one reads.
- Brief your team: Ensure every member of staff understands which AI tools are approved, what data can and cannot be shared with AI systems, and who to contact if they notice something unexpected.
- Schedule a review: AI tools update frequently. What was safe last quarter may have new features or changed data handling practices. Build a quarterly review into your governance calendar.
AI Is Not the Risk, Lack of Control Is
To be clear: this is not about avoiding AI. The productivity benefits are real, and in many cases AI is already embedded in the tools your firm relies on every day. Stepping away from AI is neither practical nor advisable.
But using AI without governance is like using a financial system without reconciliation. It might work perfectly well for months until the day it does not, and you discover there is no way to trace what happened, who was affected, or how to fix it.
The opportunity right now is to get ahead of the curve. Treat AI with the same rigour you apply to every other critical system in your firm. Build the controls, assign the ownership, and create the emergency procedures before you need them.
If you are not completely sure where your AI risks are today, that is something we can help you assess and address. Get in touch with Absolutely PC and let us help you build an AI governance framework that is practical, proportionate, and ready for whatever comes next.
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