TLDR: Wells Fargo is fundamentally re-architecting its operations to embed agentic AI, moving beyond simple generative AI to systems that execute tasks. This strategic shift, in partnership with Google Cloud, aims to enhance employee productivity, streamline workflows, and prepare for a future of interoperable AI agents in banking. The initiative includes deploying custom AI agents, Deep Research, and NotebookLM to thousands of employees, with a strong emphasis on governance, security, and employee literacy.
Wells Fargo is undertaking a significant transformation, re-architecting its core systems to deeply embed agentic artificial intelligence (AI) into its operational workflows. This strategic move, detailed by Tracy Kerrins, Wells Fargo’s head of consumer technology and generative AI, at a recent Money 20/20 panel, emphasizes a shift from incremental technological upgrades to a complete reimagining of banking processes. The bank’s collaboration with Google Cloud is a cornerstone of this initiative, particularly focusing on enhancing employee capabilities.
Kerrins highlighted that the strategy is divided into key focus areas, with the partnership with Google specifically targeting employee-facing AI solutions. This approach positions Wells Fargo alongside other major financial institutions like JPMorganChase, Citi, Capital One, and Goldman Sachs, all of whom are actively exploring or deploying agentic AI capabilities.
The bank’s journey into advanced AI began in 2021 with partnerships with Google Cloud and Microsoft Azure for advanced analytics. By 2022, Wells Fargo launched ‘Fargo,’ a digital assistant built on Google’s conversational AI platform. The integration deepened in 2025 with the adoption of Google’s Agentspace for developing custom AI agents and the rollout of tools like Deep Research and NotebookLM to approximately 2,000 employees. These tools are set to form the backbone of an enterprise-wide generative AI platform, which will eventually be accessible to all employees, aiming to boost productivity and provide faster access to critical information.
Agentic AI represents a significant leap beyond traditional generative AI. While generative AI produces text or answers based on prompts, agentic AI takes these outputs and executes tasks on behalf of the user. Rohit Bhatt, general manager and managing director at Google Cloud, articulated this transition as moving from ‘ask me a thing’ to ‘getting something done,’ emphasizing that successful implementation hinges on trust, credentialed transactions, and human supervision.
Early applications of agentic AI at Wells Fargo include automating tasks such as reviewing and summarizing lengthy vendor contracts, identifying ‘know-your-customer’ (KYC) requirements, and assisting with complex post-trade inquiries within the corporate and investment bank. Additionally, agents are being deployed to support branch and service staff in handling routine customer requests, such as debit card replacements, all under human oversight.
Ensuring the responsible deployment of these powerful AI tools is a top priority. Wells Fargo and Google Cloud’s engineering teams are working closely to integrate the AI platform with the bank’s stringent internal governance and risk frameworks, addressing regulatory compliance, data privacy, and security concerns. Bhatt stressed the importance of ensuring the technology is ‘adoptable in financial services with the right security.’
Complementing the technological rollout, Wells Fargo is investing in comprehensive employee education and AI literacy programs. Kerrins explained, ‘We have a whole literacy program … to try and educate and inform everyone, whether it’s from our engineers to our employees to our executives.’ The goal is to encourage employees to ‘forget about everything you know about being a banker right now. Take everything you just learned about this technology and reimagine — how would you do it?’
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Looking ahead, both Wells Fargo and Google Cloud envision a future of ‘agent-to-agent banking,’ where AI agents can interact directly and interoperably across various systems. Bhatt noted that technologies are being developed to ensure agents are ‘interoperable and integratable with a very large open ecosystem.’ Kerrins anticipates a future where ‘Pretty soon I think we’ll all have our [AI] buddy there doing business for us, and part of that business isn’t just ordering DoorDash or booking travel — it’s banking.’
