Bloomberg, the financial data, media and technology firm, has published new research suggesting that competence with AI and coding tools is overtaking conventional academic qualifications as the route into quantitative and analyst careers in the City of London.
The study polled 500 financial services professionals based in London. Among respondents responsible for final hiring decisions, 94% said they would bring a candidate without a conventional finance or quant background into a quantitative or analytical position, provided that person demonstrated strong ability with AI and coding tools. More than half (54%) of these decision-makers said they had already made such a hire. AI fluency was cited by 48% as a requirement for breaking into quant investing, putting it ahead of a degree in maths, physics, engineering or computer science, which was named by 39%.
Even so, the findings indicate that the field has not become open to all. Just over half of those surveyed (51%) believe AI is broadening the mix of backgrounds able to enter quant roles, yet only 18% think no specialist grounding is required, while 32% maintain that solid numerical or analytical ability remains a must. The remaining respondents were more cautious: 36% said deep technical expertise and a particular academic profile are still needed, and 13% argued that entry has become tougher, as AI know-how is now expected in addition to technical skills.
Alongside the research, Bloomberg pointed to its recently launched BQuant Assistant, a conversational AI coding tool grounded in financial domain knowledge. Embedded within BQuant Desktop and BQuant Enterprise, the assistant lets Bloomberg Terminal subscribers use plain-language prompts to generate code, create dynamic applications and speed up their analysis of financial data.
The polling was conducted by Stack Data Strategy on Bloomberg’s behalf between 22 August and 21 September 2026. It examined how artificial intelligence is being adopted across financial services and how the technology is changing skills, career paths and client relationships.
Bloomberg head of go-to-market, BQuant Product James Jarvis said, “Technology is driving a shift in how traditional quant roles and techniques, which once demanded a highly specialised skillset, are opening up to a broader range of people with a variety of backgrounds and expertise, including those with arts degrees.
“This democratisation expands the effective talent pool dramatically and in turn drives innovation and extends the art of what is possible. However, while AI lowers the barrier to entry, it does not lower the barrier to knowing when and how to use these tools well. Judgement, critical thinking and human expertise are more crucial skills than ever.”
He added, “Domain-grounded coding tools like BQuant Assistant mean that a wider pool of financial users can now use natural language prompts to build apps and conduct quantitative research that previously was confined to a smaller subset of experts.
“With conversational AI now built directly into BQuant’s Python development environment, it has never been more accessible for users to test ideas, refine quantitative financial analyses, and build investment strategies, dashboards, and visualizations.”
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