Fewer than 9% of quantitative finance professionals believe new graduates are adequately prepared to work with artificial intelligence (AI) and machine learning tools, according to new research from the CQF Institute. The findings, released at the Institute’s Annual Quant Insights Conference, underscore a widening skills gap as AI becomes integral to the quantitative finance industry.
The survey reveals that 83% of respondents are already using or developing AI tools in their work, with leading technologies including machine learning (31%), generative AI (31%), and deep learning (18%).
Among generative AI users, ChatGPT led adoption at 31%, followed by Microsoft/GitHub Copilot (17%) and Gemini/Bard (15%). More than half (54%) of respondents use these technologies daily, primarily for coding and debugging (30%), research and market sentiment analysis (21%), and report generation (20%).
AI applications are increasingly central to quantitative finance, supporting research and alpha generation (26%), algorithmic trading (19%), and risk management (17%). Nearly half of participants (44%) reported measurable productivity gains, with one in four (25%) saving over ten hours a week through AI-assisted workflows.
However, challenges remain. Model explainability was cited as the most significant barrier to wider adoption (41%), followed by computing costs (17%) and regulatory constraints (16%). Only 14% of organisations currently provide formal AI training or certification, while 9% of graduates entering the industry are viewed as fully capable of applying these tools effectively.
Despite these limitations, momentum for AI integration continues to build. One in four firms now have a formal AI strategy, with another 24% actively developing one. Over the next year, 23% of respondents expect to increase budgets for AI talent, tools and infrastructure by at least 25% – signalling growing institutional commitment to technology-driven efficiency.
Dr. Randeep Gug, Managing Director of the CQF Institute, highlighted the importance of developing practical AI competencies. He noted that future professionals would need to hit the ground running and know when an AI tool truly adds value, highlighting that recent surveys show the industry still has significant progress to make.
To bridge the skills gap, the CQF Institute aims to drive global knowledge sharing and professional development through its Certificate in Quantitative Finance (CQF) program and events like the virtual Annual Quant Insights. Featuring 17 leading experts, including Dr. Paul Wilmott, Professor Carol Alexander, Aaron Brown, and Lisa Goldberg, the Quant Insights Conference sparked dialogue and breakthrough discussions on topics like trading, portfolio theory, AI applications, crypto microstructure and quantum finance.
“Standardised certifications and specialised courses for quantitative finance and investment banking equip quants with the essential tools to drive efficiency and results. Embracing ongoing education and innovative technologies are critical to shape the future of quantitative finance. Those who don’t move forward will be left behind.”
Dr. Randeep Gug, Managing Director, CQF Institute
