AI has been a part of financial services for years, but the past two years have marked an unprecedented acceleration in its adoption. With the rise of generative AI and Agentic AI, the industry is now moving beyond simple automation toward more sophisticated, intelligent systems capable of transforming operations at scale.
Over the past decade, financial institutions have explored AI’s potential, but the true shift came with the emergence of generative AI in late 2022. AI is being adopted much faster, unlike previous technological waves such as mobile banking, cloud computing, and blockchain. Overall, 75% of financial firms surveyed by Bank of England in 2024 reported already using AI, with an additional 10% planning to adopt it within the next three years, highlighting the urgency to integrate AI-driven solutions.
The increasing focus on AI is evident in major headlines. Political and business leaders are discussing AI’s economic impact at a global level. For example, in early 2024, discussions around AI investments reached the highest levels of government, with commitments of over $500 billion and projections of 100,000 AI-driven job opportunities. Meanwhile, AI innovations like Deep Seek have significantly affected global markets, causing stock fluctuations of up to $1 trillion daily.
Many banks and financial institutions have launched AI pilots yet reports indicate that as high as 85% of these initiatives fail. This high failure rate underscores the gap between AI’s promise and its practical application in enterprise environments. AI’s potential remains significant, with projections estimating that AI could add up to $1 trillion annually in value to the global banking industry, but organizations must navigate challenges around governance, adoption, and scalability to maximize its benefits.
AI in financial services is evolving along three distinct phases:
This transition from assistance-based AI to full workflow automation is reshaping financial services. For instance, Agentic AI can now understand complex regulatory environments and execute tasks with minimal human intervention, ensuring compliance while improving efficiency. Integrating Agentic AI into lending, credit approvals, and banking operations provides a strong competitive advantage.
While banks have embraced AI to enhance customer experiences, much of their internal workforce remains burdened by manual, repetitive tasks. Historically, technological advancements, such as cloud adoption, focused on customer engagement while leaving workforce efficiency largely unaddressed.
AI is now shifting this focus, targeting inefficiencies within operational workflows. Many banking processes remain manual, with employees still relying on spreadsheets and legacy systems. AI-driven automation will allow financial professionals to spend more time on high-value, strategic work rather than administrative burdens. A Citigroup report estimates that AI could displace over 50% of banking jobs. The numbers are similar for the insurance industry, with an estimated 48% of jobs potentially displaced, shifting workforce focus to advisory and relationship-building roles.
Despite the enthusiasm for AI’s capabilities, financial institutions remain cautious about risk management and regulatory compliance. Concerns around data privacy, security, and AI hallucinations (erroneous or misleading outputs) present challenges to widespread adoption. The Financial Conduct Authority (FCA) has emphasized the importance of AI explainability, with new guidelines in 2024 requiring financial institutions to implement AI model transparency frameworks.
To address these challenges, banks need robust AI governance structures. This includes:
In addition, financial institutions are grappling with the challenge of democratizing AI use among employees while ensuring compliance. The “bring your own AI” phenomenon, where employees utilize external AI tools without governance, poses risks. Banks must implement policies that allow safe and structured AI adoption rather than outright bans, often leading to uncontrolled usage of external AI applications.
AI will become as fundamental to banking as cloud and SaaS have been over the past two decades. However, there will be distinct winners and losers in this transformation. Banks that take a proactive, strategic approach to AI adoption will gain efficiency and profitability. Meanwhile, institutions that hesitate or struggle with implementation risk being left behind.
The shift toward an “Agent as a Service” model is also emerging, where AI-driven agents manage workflows autonomously. This evolution will change how banks interact with technology vendors, moving beyond traditional software-as-a-service (SaaS) to fully outsourced AI-powered services. Fintechs specializing in Agentic AI will play a critical role in shaping this future. Companies like Revolut and Nubank have already begun experimenting with fully AI-driven operational models, setting the stage for a new banking framework.
AI’s impact on financial services is just beginning. While governance, compliance, and adoption challenges remain, the opportunity is too significant to ignore. Banks that embrace AI-driven automation, build responsible governance frameworks, and use AI to support their workforce will lead the industry into its next phase of digital transformation.
The question is no longer whether AI will transform financial services, it’s how quickly institutions can adapt and capitalize on its advantages.
Want more insights on how AI will impact financial services? Listen to FintechOS Evolv Podcast below.
On the latest FintechOS Evolv Podcast, Mark Dearman, Director of Banking Industry Solutions at FintechOS sits down with Ben Thomas (Covecta) and Michael Anyfantakis (Vigilant AI²) to explore:
🔹 Why AI adoption in financial services is still “mission incomplete”
🔹 How Agentic AI is reshaping banking operations and unlocking game-changing efficiency
🔹 The biggest risks – data privacy, AI governance, and how to use AI responsibly
🔹 What the future of AI in banking looks like – and who will come out ahead
🎧 Tune in on your favorite platform:
– Podbean
– Apple Podcasts
– YouTube
