Revolutionizing Business Operations: M&T Bank’s Enterprise AI Expansion

M&T Bank Implements AI Copilots for Over 15,000 Employees

M&T Bank has introduced AI copilots to more than 15,000 staff members as part of its strategy to leverage AI technology across various aspects of its operations. These include internal processes, customer service, software development, and risk management.

The bank’s utilization of AI extends to analyzing call-center interactions, compiling reports, automating code generation, identifying customer requirements, and flagging potential risks within its portfolio. According to Fast Company, M&T is also exploring the application of agentic AI in cybersecurity and fraud detection.

An article by American Banker in September 2025 revealed that around 16,000 out of M&T’s approximately 22,000 employees were actively utilizing Microsoft Copilot for tasks such as drafting emails and reports, as well as summarizing call-center discussions.

Prior to the widespread adoption of AI tools, M&T initially limited employee access to public large language models due to concerns about the potential disclosure of sensitive company information. Chief Data Officer Andrew Foster explained that the bank restricted the use of these tools to prevent the inadvertent exposure of confidential data through public platforms.

Subsequently, M&T evaluated various enterprise solutions and chose Microsoft Copilot, initially implementing a pilot program involving approximately 800 employees before expanding access across the organization.

Foster highlighted the efficiency gained by utilizing generative AI to summarize call-center conversations, saving an average of six minutes per call. Furthermore, software developers at the bank leverage GitLab tools to automate code generation, with employees retaining responsibility for reviewing AI-generated outputs.

The bank’s commitment to human oversight is underscored in its 2026 Code of Business Conduct and Ethics, mandating the use of approved AI tools and prohibiting the input of sensitive information into unauthorized systems. Employees are accountable for ensuring the accuracy and appropriateness of AI-assisted work.

Establishing a Strong Technological and Data Framework

M&T’s AI implementation follows a comprehensive technology transformation that commenced in 2018. At that time, over half of the bank’s technology experts were external contractors, a figure which has now shifted to an 80% in-house workforce.

Presently, M&T boasts a team of more than 2,000 technologists operating across over 300 agile teams, with the recruitment of over 1,000 technology specialists during this initiative.

As part of the overhaul, M&T has replaced numerous outdated platforms, resulting in a significant reduction in technology-related outages since 2018 and a threefold increase in the number of system upgrades completed annually.

Notably, technology expenditure exceeded $1.2 billion in 2025, nearly tripling the 2017 budget. Wisler, speaking to Forbes in August 2026, highlighted a substantial rise in the annual release of technology advancements, increasing from around 15,000 in 2018 to 65,000 in 2025.

Having joined M&T as Chief Information Officer in 2018, Wisler transitioned to the role of Senior Executive Vice President for Technology and Operations in 2025. Currently, his responsibilities encompass both technological and operational functions across the bank.

The bank’s data initiatives progressed alongside the broader technological transformation. Foster, who joined M&T in 2023, initiated a data-lineage program to track the origin, utilization, and movement of information within the bank’s systems.

According to Foster, the data-lineage framework was not solely in response to generative AI but rather a fundamental capability to enhance the bank’s data management practices. Additionally, M&T established a Data Academy focused on enhancing data governance and skillsets, with approximately 2,000 employees participating in the program.

M&T introduced an internal repository named Edison, housing authoritative documents and bank policies. Leveraging data-lineage software from Solidatus and Monte Carlo, the bank can trace data flow across databases, applications, and business intelligence systems.

The data lineage program provides M&T with visibility into the source, meaning, quality, and governance of individual data elements. Foster emphasized the application of governed data, particularly in the bank’s use of Copilot, and highlighted the use of retrieval-augmented generation with internal data.

Expanding AI Applications in Daily Banking Operations

Wisler outlined M&T’s approach to advancing generative AI through three avenues: general employee utilization, integration of AI capabilities within existing applications, and the development of proprietary systems tailored to the bank’s data and processes.

With a portfolio exceeding 1,800 applications, many sourced from third-party providers, M&T focuses on identifying valuable AI features already embedded in these applications as one pathway for AI integration.

The bank’s third pathway involves developing proprietary AI solutions aligned with its unique data and operational requirements. Early applications include streamlining operational tasks, software development, fraud detection, and cybersecurity.

Fast Company’s report in September also mentioned M&T’s ongoing assessment of both internally developed AI systems and external tools, including enterprise software and banking-specific technology.

Initial workforce applications centered on drafting, summarization, call-center support, and software development. Recent applications have expanded to include identifying customer needs and flagging risks within the bank’s portfolio.

Similar to M&T, other major US banks have integrated generative AI into their employee workflows. JPMorganChase introduced its LLM Suite platform to over 200,000 employees in 2024, with more than 65,000 staff in its Corporate and Investment Bank actively utilizing the platform by 2025. The bank reported increased transaction screening efficiency and reduced manual checks through AI-based processes.

Bank of America leverages a generative AI system called EricaAssist with over 18,000 customer service employees. The tool provides contextual guidance, reduces call times, and aims to extend its application to additional scenarios and business lines in 2026.

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