A new Bloomberg LP survey of 500 London-based financial services professionals suggests AI adoption is already widespread, according to results released last week. Nearly nine in ten (88%) use AI tools daily or weekly, and not a single respondent said they haven’t begun learning to use them or believe there are no opportunities to be gained from it.
AI proficiency is increasingly treated as a baseline expectation across London’s finance workforce: 85% believe AI skills will soon outweigh traditional ones for their next promotion or career move, and 69% think colleagues who resist developing those skills have no place at their firm.
Professionals are building AI skills on both company and personal time, drawing on more than three methods on average. When asked which methods they use to build AI skills, using AI tools to learn AI came top (53%), followed by experimenting in their own time (50%), watching videos and online guides (44%), learning from colleagues (42%), and formal employer training (40%).
Amanda Stent, head of AI strategy & research in the CTO Office at Bloomberg said: “Becoming effective with AI doesn’t require a PhD in computer science — it requires curiosity and domain expertise. What’s striking about these findings is the initiative London’s financial services professionals are showing in response to the rapid evolution of AI. They’re learning by doing, experimenting, and asking the tools themselves. That kind of self-directed curiosity is exactly what thriving in an AI-driven industry requires.”
When asked to select their top three concerns about AI, the loss of entry-level and graduate roles was one of the least selected options (seventh most common out of eight potential concerns), selected by only 30% of professionals compared with 45% who selected AI-enabled cyberattacks and financial crime.
Stent added: “Removing the friction from knowledge work doesn’t remove responsibility. As AI handles more of the information retrieval and synthesis, where humans commit their time shifts from performing the manual research to acting as the ultimate arbiter. A model may detect a pattern; it takes a trader or analyst with years of experience to understand whether that pattern is a meaningful signal or just noise.”
Of those who’ve freed up time through AI, 32% said they were finishing work earlier, but the more common pattern is reinvestment: over half (51%) are redirecting time toward higher-value activities like strategy, decision-making and client relationships, 48% have reduced time on routine administration, and 36% are collaborating more with colleagues.
Despite this confidence in AI’s potential, there are clear limits to where professionals think it should operate without human input. 51% say risk and compliance is the area where human oversight matters most, followed by investment and trading decisions (40%). Only 1% believe human oversight is unnecessary in most cases.
Stent concluded: “Finance remains a fundamentally human endeavour, enhanced and empowered by technology. In a world where information is abundant, judgement and leadership are the scarce resources. What this research shows is that London’s financial services professionals understand that and are positioning themselves accordingly.”
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