Data Foundation

M&T Bank is aggressively integrating AI, deploying AI copilots to over 15,000 employees to boost efficiency and customer service across operations, development, and risk management. The bank has built a strong technology and data foundation since 2018, significantly reducing outages and increasing system upgrades. AI applications range from content generation and summarization to identifying customer needs and flagging portfolio risks, mirroring industry-wide adoption of AI in finance. M&T emphasizes human oversight and data governance in its AI strategy.

Enterprise AI is shifting from aspirational to imperative, demanding near-perfect accuracy and robust governance. The move from 90% to 100% accuracy is existential, transforming LLMs into autonomous agents requiring rigorous management. Key challenges include agent sprawl, data foundation readiness, and intent-based interfaces. True enterprise intelligence must leverage proprietary data and structured relational models, not just generic LLMs. Competitive defense emerges from customer-specific AI, requiring embedded functionality, agentic orchestration, and industry-specific intelligence, all underpinned by strong governance.