BNY employees increasingly describe changes that align with the AI‑driven cost‑reduction strategies McKinsey promotes to large financial institutions.
The most visible shift we see is the steady automation of repetitive, rules‑based work that RV brags about in the media — onboarding, KYC refresh, reconciliations, service requests, and exception routing. Employees report that tasks once handled by full teams are now processed through AI‑enabled workflows, reducing the need for manual roles and shrinking job families.
Decision‑support AI is also reshaping middle‑skill positions. Workers note fewer analyst roles, broader spans of control, and more “AI‑assisted” oversight, which mirrors McKinsey’s recommendation to streamline mid‑tier functions by embedding intelligence into platforms rather than people.
The Platform Operating Model (P-O-M) accelerates this transition. Employees describe work being standardized, centralized, and moved offshore once AI reduces the skill threshold required. This matches McKinsey’s model: automate first, relocate second.
The impact on employees is becoming clearer. Career paths in legacy operations, service, and processing roles are narrowing as automation absorbs institutional knowledge and reduces the value of tenure. Job security is declining in functions where work can be digitized, offshored, or both. New roles are emerging in AI governance, data quality, and exception management — but not in volumes that offset reductions.
Employee reports consistently reflect the same conclusion: AI is not just a tool at BNY; it is a restructuring engine.