AI adoption in financial services by type and group 2026| ��ƽ��

Active adoption of machine learning (ML), generative artificial intelligence (GenAI), and agentic AI in financial services worldwide in 2026, by AI and firm type

Characteristic	Fintechs	Traditional FIs	Regulators
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Release date

April 2026

More information

Region

Worldwide

Survey time period

October 2025 to January 2026

Number of respondents

482 respondents

Supplementary notes

The source adds the following information: Active adoption includes respondents at the piloting, scaling, or transforming stages of the AI adoption maturity framework.

Overall survey sample comprised 203 fintechs, 149 traditional financial institutions, and 130 regulators.

Regulators refers to financial regulators, supervisory authorities, and central banks with mandates spanning prudential regulation, securities oversight, payments supervision, consumer protection, and financial stability. Traditional financial institutions refers to firms operating across banking, insurance, payments, capital markets, digital assets, and other financial services sectors

Citation formats

Financial institutions surveyed in early 2026 showed near-parity in their adoption of Classical ML and GenAI, with fintechs and traditional financial institutions reporting virtually identical rates for both, at ** percent and ** percent, respectively. The adoption rate was notably lower at regulators, at ** percent. This closing of the gap was notable given that GenAI only gained meaningful traction following the launch of ChatGPT in late 2022; within just a few years, it had effectively caught up with machine learning methods that had been embedded in financial services workflows for over a decade. Agentic AI told a different story. While it had achieved rapid uptake for an emerging technology - ** percent of fintechs and ** percent of traditional FIs were piloting or beyond as of early 2026 - it remained clearly behind the other two categories and showed a sharper divergence across institution types. The 12-percentage-point gap between fintechs and traditional FIs was the widest of any AI category, suggesting that autonomous agent deployment was still concentrated among more digitally agile institutions.