In this September 2026 article, three partners at the McKinsey Transformation Practice argue that the transformation office, the function responsible for steering change within the company, is often one of the slowest to modernize its own tools. Hand-assembled presentations and scattered data produce late information, diverging narratives between workstreams, and parallel tools.
Two cases quantify this ceiling. In a two-year turnaround affecting 3,000 employees, more than fifteen full-time people spent half their time validating data for a report of over 300 pages produced every four weeks. In another transformation, more than 100 non-integrated documents were used for financial tracking.
The authors distinguish generative AI, which assists an individual on a task, from agentic AI, which plans, acts, and loops multi-step workflows. They describe three pillars. Performance intelligence continuously synthesizes initiative data and surfaces only exceptions; in a case involving 30,000 metrics and 900,000 data points, an agentic framework built largely with Cursor and integrated into Lilli Teamspace replaces hours of pivot tables. The single source of truth dynamically links Wave, the ERP, HR, and production tools, without a centralized data lake, and makes it possible to simulate the effect of additional funding. Conversation facilitation prepares steering committees: a five-hour analyst briefing is produced in under ten minutes, and reporting goes from twelve to three days per month in one case.
The reported gains reach 35 to 40% of time on core tasks, sometimes 70% or more. In one deployment, automating ten processes reduced the central team from one manager and nine staff to one manager and two, freeing up more than 25 days of capacity.
The article flags risks: a data error can propagate between connected agents, false alerts are numerous at first, and mitigation remains behind awareness. Every step an agent takes must be traceable. Escalations, stakeholder relations, and culture remain human.
Deployment requires mapping workflows, setting governance rules, and repositioning staff as workflow orchestrators. The early movers start with reporting, then automate cross-system actions. Without the office team's trust, manual habits return. The cases are not named.