M&T Bank has deployed AI copilots to more than 15,000 employees, embedding the technology across internal operations, customer service, software development, and risk management. The rollout, reported by Fast Company and American Banker, ranks among the largest AI deployments by a US regional bank and reflects a multi-year technology overhaul that began in 2018.
The bank uses AI to summarise call-centre conversations, draft reports and emails, generate code, identify customer needs, and flag portfolio risks. About 16,000 of M&T's roughly 22,000 employees were using Microsoft Copilot as of September 2025, according to American Banker. The bank is also evaluating AI for IT & Development applications in cybersecurity and fraud detection through agentic AI systems.
From blocked access to enterprise-wide deployment
M&T initially restricted employee access to public large language models. Chief data officer Andrew Foster told American Banker the bank blocked the tools because employees could potentially enter sensitive company information into public-facing services. "We blocked it," Foster said. "We said, 'You can't use these tools.'"
The bank later evaluated enterprise providers and selected Microsoft Copilot, starting with a pilot involving about 800 employees before expanding access across the organisation. Foster said using generative AI to summarise call-centre conversations saves about six minutes per call. Software developers also use GitLab tools to generate code, while employees remain responsible for reviewing AI-generated work.
M&T's human-review requirement is codified in its 2026 Code of Business Conduct and Ethics. The policy requires employees to use approved AI tools and prohibits confidential, proprietary, customer, employee, or regulated information from being entered into unapproved systems. Employees remain responsible for the accuracy and appropriateness of AI-assisted work.
The technology foundation beneath the AI rollout
M&T's AI deployment rests on a technology overhaul that began in 2018. At the time, more than half of the bank's technology specialists were external workers. Today, roughly 80% of its technology workforce is in-house, with about 2,000 technologists working across more than 300 agile teams. The bank has hired more than 1,000 technology specialists during the programme and replaced dozens of older platforms.
Technology outages have fallen by more than 80% since 2018, while the number of system upgrades completed annually has increased by 300%. Technology spending exceeded $1.2 billion in 2025, nearly three times its 2017 level. Mike Wisler, who joined as chief information officer in 2018 and became senior executive vice-president for technology and operations in 2025, told Forbes that annual technology releases increased from about 15,000 in 2018 to 65,000 in 2025.
Foster, who joined the bank in 2023, began building a data-lineage programme to track where information originates, how it is used, and how it moves between systems. He told American Banker the work was not created in response to generative AI. "This was a core capability for understanding our data estate," he said. The bank uses data-lineage software from Solidatus and Monte Carlo to trace information as it passes through databases, applications, and business-intelligence systems. M&T also established a Data Academy focused on data governance and data skills, with around 2,000 employees participating.
Three pathways for scaling AI
Wisler told Forbes that M&T is pursuing generative AI through three routes: general employee use, AI capabilities embedded in existing applications, and proprietary systems built around the bank's own data and processes. M&T operates more than 1,800 applications, many supplied by third-party vendors. One pathway involves identifying useful AI capabilities already embedded within those applications.
The third pathway centres on proprietary AI development around the bank's own data. Early applications include repetitive operational work, software development, fraud prevention, and cyber defence. Fast Company reported that M&T continues to assess both internally developed AI systems and external tools, including general enterprise software and technology designed specifically for banks. The bank also uses retrieval-augmented generation with internal, governed data to ground its AI outputs.
M&T's approach mirrors moves at larger US banks. JPMorganChase launched its internal LLM Suite platform to more than 200,000 employees in 2024. By 2025, more than 65,000 employees in its Corporate and Investment Bank were actively using the platform, and more than 90% of its engineers were using AI coding assistants. Bank of America deployed a generative AI-enabled system called EricaAssist to more than 18,000 customer service employees, reducing average call times by nearly one minute and delivering contextual guidance in under three seconds.
Why this matters for finance and technology leaders
M&T's deployment demonstrates that AI adoption in financial services requires a foundation of modernised infrastructure and governed data - not just access to large language models. The bank spent seven years rebuilding its technology workforce and platforms before scaling AI across the organisation. For executives and IT leaders, the sequence matters: data-lineage work, internal policy guardrails, and human-review requirements preceded the broad rollout. The result is an approach where AI for Finance operates on known, traceable data rather than ungoverned inputs, with clear accountability resting on employees who use the tools.
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