The UK government's £200m AI skills and adoption fund is well-intentioned, but it misses the point that's killing most regulated firms' AI projects. Money and upskilling matter, yes — but mid-market law firms, insurers, asset managers and accountancy practices are not failing at AI because they lack capital or LinkedIn Learning courses. They are failing because they lack governance frameworks that actually hold up under FCA Consumer Duty scrutiny, SRA Code compliance reviews, and ICO UK GDPR enforcement. The thirty signatories sharing data (BT, Rolls-Royce, EDF, Accenture) operate in sectors with very different liability and regulatory models than financial services and legal practice. That matters. A law firm using an LLM like Harvey or Legora to draft contracts still faces the same liability question: who is responsible when the model hallucinates a clause? That question does not disappear because you have attended a government-funded AI workshop.

This fund is symptomatic of a wider policy blindspot. The conversation about AI adoption in the UK has been dominated by capacity — more compute, more talent, faster deployment. But for regulated firms operating under ISA UK, PRA SS1/23, and the emerging EU AI Act compliance requirements, capacity without governance is liability without mitigation. We are seeing this play out now: firms that rushed to adopt Copilot or Luminance without first asking how they would audit the model's decisions, retain training data, or prove non-discrimination are now scrambling to retrofit controls. The FCA's recent focus on operational resilience (ISOIEC 42001 frameworks) shows the regulator cares about how firms manage AI risk, not how quickly they deploy it. A fund that focuses on skills and upskilling without mandating governance assessment misaligns incentives.

Trovix's view is direct: the question is not whether your firm can afford AI. It is whether your firm can afford AI without breaking its compliance envelope. Most AI product marketing — including in document intelligence, retrieval-augmented generation, and agentic workflows — focuses on speed and accuracy. These matter, but they are not the hard problem for regulated firms. The hard problem is auditability. Can you prove that your document extraction via Trovix Sift met your data quality standards? Can you show that your fee-earner's RAG assistant via Trovix Aria is not training on confidential client data? Can you demonstrate that your client-facing chatbot via Trovix Reach is not giving regulated advice? These are governance questions, not product questions. They require Trovix Audit—a compliance dashboard—not just a better model. Firms comparing Harvey to Luminance to Microsoft Copilot are comparing LLMs. Firms that will survive FCA and SRA scrutiny are comparing audit trails.

If you are a mid-market regulated firm, do not wait for the government fund to be allocated before you act. Use the next six months to build a governance framework first, then overlay AI tools into it. Start with three questions: What data can this AI process without breaching client confidentiality or GDPR obligations? How will we audit the model's decisions if a regulator asks? What is our indemnity if the model makes a mistake that harms a client? Once you have honest answers, the £200m fund becomes useful — you will have the discipline to spend it on tools that fit your framework, not tools that force you to rebuild your framework around them. The firms that get this right will be the ones that sign up for the second wave of government policy consultation, not the first wave of funding allocation.

Source: Computer Weekly