FinTech firms lead as AI becomes mainstream in finance

By Parth Prabhudesai

Artificial intelligence has become a mainstream capability across financial services, with adoption now reaching scale but outcomes increasingly tied to how deeply firms integrate and invest in the technology. A new study by the Cambridge Centre for Alternative Finance at the University of Cambridge finds that while adoption is widespread, the real differentiator is AI maturity, not mere implementation.

The report, based on insights from 628 institutions, vendors and regulators across 151 jurisdictions, shows that 81% of financial services players now use AI in some form, with 40% reaching advanced stages such as “Scaling” or “Transforming.” This reflects the industry’s growing reliance on AI to improve efficiency, strengthen risk management, and deliver personalised customer experiences.

A clear divide has emerged between FinTech firms and traditional financial institutions. FinTechs, built on digital-first architectures, are more than three times as likely to reach the “Transforming” stage, with 19% achieving this level compared to just 6% of incumbents. Traditional players remain concentrated in earlier stages such as “Exploring” and “Piloting,” reflecting challenges related to legacy systems, integration complexity, and organisational inertia.

In terms of technology adoption, machine learning remains the dominant tool, used by 75% of respondents, particularly in areas such as fraud detection, credit underwriting and anti-money laundering. Generative AI is rapidly catching up, with a 71% adoption rate, while agentic AI—systems capable of autonomous, multi-step decision-making—has already reached 52%, signalling strong momentum in advanced automation.

AI deployment is most mature in operational and back-office functions. Process automation leads with 79% adoption, followed by data visualisation and software development at 75% each. In customer-facing roles, AI-powered support is the most widely used application at 73%, alongside marketing, CRM and sales enablement tools that enhance acquisition and engagement strategies.

Crucially, the study finds that financial returns from AI depend heavily on maturity and investment. Among advanced adopters, 64% reported increased profitability, compared with just 33% of less mature firms. Similarly, firms investing over $100,000 annually in AI saw significantly higher returns than those with lower spending. Organisations that develop or fine-tune AI models in-house also outperform those relying solely on third-party solutions, highlighting the importance of control and technical capability.

The workforce impact of AI has so far been limited, with 74% of respondents reporting no major change in employment levels. However, by 2030, the industry expects transformation rather than reduction. Around 35% of firms anticipate job growth or reskilling, while a quarter expect some decline, particularly in payments.

Despite progress, challenges remain. Data quality and availability are the biggest barriers, cited across industry participants, vendors and regulators. Legacy systems, fragmented infrastructure, and limited institutional expertise further constrain adoption. Regulators also face capability gaps in talent, training and technology.

Overall, the findings suggest that AI is no longer a competitive advantage in itself, but a baseline capability. The next phase of value creation will depend on how effectively institutions scale, integrate and govern AI within their operations.