Banks hit an AI plateau
A recent industry read finds 80% of banks report no measurable bottom-line impact from AI pilots, blaming surface-level deployments and weak data foundations. The finding frames a gap between AI experimentation and enterprise-scale transformation in financial services. (asianbankingandfinance.net)
McKinsey’s “McKinsey Talks Operations” episode titled “The paradigm shift: how agentic AI is redefining banking operations” aired Jan. 23, 2026 and featured Senior Partner David Deninzon and Partner Abhilash Sridharan discussing AI adoption in banks. (omny.fm) Speakers in that episode argued current banking deployments largely sit in a “copilot” phase—narrow point solutions—rather than full agentic-AI rewires that change end-to-end processes and decision rights. (recapio.com) Deloitte’s 2026 banking outlook flagged brittle and fragmented data infrastructure as a primary barrier to industrializing AI at scale across banks. (deloitte.com) KPMG’s 2025 “Intelligent Banking” research said many banks face the same execution gaps—legacy stacks, weak data governance, and siloed teams—that prevent pilots from radiating business-wide value. (assets.kpmg.com) A Hanover Research survey for Temenos found 11% of banks had gen‑AI live and another 43% in the pipeline, underscoring deployment activity even as outcomes lag. (bankingjournal.aba.com) Bain’s executive survey reported that while ~59% of firms are meaningfully adopting generative AI, only about 23% can directly tie those initiatives to new revenue or lower costs. (bain.com) BCG advised in May 2025 that banks which fail to move from isolated pilots to enterprise rewiring of strategy, technology, and governance risk losing competitive ground to faster movers. (bcg.com) McKinsey’s materials recommend shifting governance to cross‑functional transformation squads, building reusable AI platforms, and redesigning processes—changes McKinsey says could affect as much as 50–60% of service‑operations FTEs if fully realized. (mckinsey.org)
