The hiring picture in financial services is shifting at the top of the skills ladder. In the sector, recruitment was generally for more senior, qualified roles rather than entry-level positions GOV.UK - Temporary Shortage List: Stage 2 report. That tells us employers are competing hardest for people who bring experience and judgement, not just technical throughput.
Alongside that, demand for AI skills is climbing fast. Demand for AI skills increased nearly 200 percent in a year, with London accounting for 80 percent of AI-related job postings The Register (Accenture data). Against a subdued economic backdrop, businesses took a cautious approach to hiring, but there were demand hotspots for specialist skills including AI, data and cyber security Computer Weekly (tech recruitment outlook 2026). For credit teams, that combination matters: the work is getting more technical at the same time as it gets more senior.
Agentic tools can pull financial statements, enrich data and run a first-pass risk score without a person driving every step. That doesn't remove the analyst. It moves the job towards the parts machines can't own: challenging a model's output, pricing complex or unusual deals, and explaining a decision to a credit committee. The questions get harder, not fewer.
The scale of change is real. Across AI-related occupations, the net change ranges from approximately 696,000 jobs in one scenario to 1,072,000 in another, with replacement demand of around 3,077,000 to 3,193,000 jobs AI Skills for Life and Work: Labour market and skills projections - GOV.UK. Credit analysts who learn to work alongside these tools, reading their outputs critically rather than accepting them, will be the ones in demand. Those who treat tooling as a threat risk being overtaken by those who use it to sharpen their judgement.
The clear move is towards AI literacy at every level, not just in a data team. During London Tech Week 2025, the UK government announced a partnership to upskill 7.5 million UK workers in essential AI skills by 2030, equivalent to around 20% of the UK workforce techUK. For a credit function, that means analysts who understand how a model reaches a score, where it can be wrong, and how to document an override.
Entry routes are changing too. Apprenticeships have risen from 3% of AI hires in 2020 to 19% in 2025 GOV.UK / DSIT – AI Labour Market Survey 2025 report. For credit teams, that's a practical way to bring in people who learn the tools and the risk framework together, rather than hiring only for a finished skill set that's already scarce.
Start by writing the role for where the work is going, not where it was. If routine scoring is automated, test for judgement: give someone a borderline case and ask them to defend a decision. Look for people who can explain a model's limits in plain terms, because regulators and credit committees will both ask.
Then widen the net. With senior, qualified roles in short supply across the sector GOV.UK - Temporary Shortage List: Stage 2 report, the teams that win will consider apprenticeship and conversion routes alongside experienced hires. Move quickly on strong people, keep the process short, and be clear about how the role uses agentic tooling. The best analysts want to know the technology makes their work sharper, not narrower.
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