The UK labour market is cautious. Recruiters describe it as 'low hire, low fire', with weaker recruitment but only slight increases in redundancies, and vacancies now sitting below pre-pandemic levels the Low Pay Commission's 2025 report. That backdrop shapes how finance leaders plan headcount: fewer speculative hires, more targeted ones.
There are still clear demand hotspots. Businesses took a cautious approach through 2025, yet held strong appetite for specialist skills in AI, data, enterprise applications and cyber security according to Computer Weekly's 2026 tech recruitment outlook. Finance operations sits right in the path of that shift, because so much of the work now runs on data and automated systems.
The pull towards AI is sharp. Demand for AI skills rose nearly 200 percent in a year, with London accounting for 80 percent of AI-related job postings The Register reported, citing Accenture data. For a sector as concentrated in the capital as financial services, that signals where the next wave of finance roles is heading.
Agentic AI, software that can plan and carry out multi-step tasks with limited supervision, is taking on the repeatable parts of finance operations: matching invoices, flagging exceptions, drafting reconciliations and pulling reports. That doesn't erase roles. It changes what a good hire looks like. The value moves from doing the task to checking, correcting and improving the system that does it.
You can see the pressure on early-career routes across the wider economy. UK entry-level job postings have dropped 30 percent since ChatGPT launched, leaving graduates in the toughest market since 2018 techUK reported, citing Adzuna data. The gap between junior and senior demand is widening too: in engineering, entry-level hiring has fallen to -19 percent while senior hiring sits at -10 percent a GOV.UK snapshot of entry-level hiring found. Finance operations teams face the same question: how do you build the next generation of controllers if the routine work that trained them is automated?
One answer is already visible in AI hiring itself. Structured, on-the-job routes are becoming a practical way to grow people into oversight roles rather than hoping to hire them fully formed.
Start by rewriting the role around outcomes, not tasks. If an AI system handles first-pass reconciliation, the person you hire should be judged on how well they spot the errors it misses, question its logic and tighten controls. Prioritise financial judgement, data literacy and the confidence to challenge a machine's output over speed at manual processing.
Move quickly when you find the right fit. Specialist demand remains competitive even in a subdued market, with AI, data and cyber skills named as the hotspots Computer Weekly's 2026 outlook notes. Hard-to-fill vacancies are a real risk in adjacent technical fields: 70 percent of cyber firms reported at least one hard-to-fill vacancy the AI Labour Market Survey 2025 found. A slow process loses the people who can bridge finance and AI.
Keep an eye on the broader jobs pulse as you plan, using regular market reads such as the KPMG and REC UK Report on Jobs to time your hiring against demand.
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