Aon's review of 300+ AI-related disputes landed quietly but landed hard: insurers are now facing claims across crime insurance, IP insurance, cybersecurity and technology E&O policies because of AI incidents. The conclusion matters: AI developer executives cannot be entirely free from liability for damages their systems cause. For UK legal, insurance, financial services and accountancy firms, this is not academic. It means the AI tool you buy — whether it's Harvey, Legora, Luminance or an enterprise deployment of Microsoft Copilot — arrives with an embedded liability chain. Your firm sits in the middle. If that AI makes an error, misfires on sensitive data, or produces misleading output, you are exposed. Your professional indemnity insurance, your regulatory standing with the FCA, SRA or FRC, and your firm's reputation are all in play.

This story is the logical endpoint of a year of AI incidents in professional services. We have seen generative AI hallucinate case law, confidently invent legal precedent, and produce document analysis that failed basic fact-checking. The industry sold 'AI efficiency' while treating governance as optional. Firms deployed systems without clear audit trails, without documented guardrails, without understanding what the model was actually doing under the hood. Insurance companies are now paying for that negligence. The liability cascade is starting: developers face claims; insurers demand better controls; regulators (including the FCA under Consumer Duty PS22/9 and the SRA Code) will demand proof of competent implementation; firms without that proof will find insurance harder and more expensive to secure.

The problem is not that AI is inherently unsafe. The problem is that most AI implementations in professional services treat the tool as transparent when it is opaque, and treat deployment as binary when it is incremental. Harvey and Legora have built specific legal training into their models, which is honest work. But a general-purpose LLM running inside Microsoft Copilot, or a third-party AI bolted onto your case management system, does not know your firm's risk tolerance, your clients' specific needs, or your regulatory obligations. That's not the vendor's fault. That's deployment malpractice. Trovix's approach — implemented through Trovix Audit, our AI governance and compliance dashboard — starts from the principle that every AI system in a regulated firm must be documented, monitored and controlled. Not locked down. Controlled. You need to know what the AI is doing, why it did it, and whether it stayed within your guardrails. That's non-negotiable now.

Here is what mid-market firms should do immediately. First: audit what AI you actually have in production. Second: document it. Create a register under your ISO 42001 framework (if you have one; if not, start). Third: establish whether your professional indemnity insurance covers AI-generated output, and under what conditions. Fourth: implement monitoring. You need Trovix Watch or equivalent — regulatory change tracking that tells you when the FCA, SRA, FRC or ICO release new guidance on AI governance. Fifth: where you have high-risk AI use (case analysis, financial advice, underwriting), add human oversight with a documented sign-off process. This is not anti-AI. It is pro-regulation and pro-client. The firms that survive the liability wave ahead are the ones that implement AI competently, document that competence, and can prove it to a regulator or a claimant.

Source: SBS News