Source: Fortune
Summary
BNY Mellon’s CFO, Dermot McDonogh, discusses the bank’s approach to AI adoption, which focuses on outcomes rather than cost per query. Unlike some companies that track success by the volume of prompts, tokens, or agents deployed, BNY has developed an internal, LLM-agnostic platform and forged partnerships with hyperscalers and model providers. The bank has seen significant gains in AI adoption, with over 40% of code authored by AI and 50% of annual account plans drafted with AI. Revenue per employee has increased from $338,000 to $401,000, and pre-tax income per employee has risen from $99,000 to $143,000.
Our Reading
The announcement sounds familiar.
BNY Mellon’s approach to AI adoption is a departure from the “tokenmaxxing” craze, which prioritizes the volume of prompts and tokens used. Instead, the bank focuses on outcomes and has developed a platform that routes tasks to the appropriate models, ensuring efficiency without requiring employees to optimize prompts manually. McDonogh notes that the bank’s CEO-level commitment and focus on cultural adoption have been key to its success. The bank’s metrics, such as revenue per employee and pre-tax income per employee, demonstrate the impact of AI on its operations.
The numbers tell one story: BNY Mellon’s approach to AI adoption is about capacity creation, not cost savings.
Author: Evan Null
