If you find value in content like this, sign up for my Talent Edge Weekly newsletter.
As AI agents evolve from passive tools to active collaborators, they are reshaping how work gets done, who does it, and how teams are structured. Scaling this capability across an organization, however, is complex and requires careful consideration. This 30-page report outlines three essential components for scaling agentic AI and turning it into a true performance enabler: 1) the chassis, or the strategic technical framework, which provides a secure and open foundation connecting agents, models, and systems enterprise-wide to support orchestration, interoperability, and scalability; 2) the fuel, or the high-quality, well-governed data streams that power adaptive decision-making through integration, accessibility, and real-time flow across the enterprise; and 3) the powertrain, or the human–AI collaboration that converts potential into measurable outcomes by aligning actions to KPIs and embedding accountability. The report explores each component in depth, and starting on page 21, introduces an Action Guide designed to help put these ideas into practice. For example, to enable continuous data flow to and among agents, one recommended action is to conduct a quick audit of your data governance framework to identify bottlenecks that slow access to high-quality data and pinpoint the high-impact data sources most critical to agent decision-making. Other ideas are discussed. As a bonus, I am resharing the McKinsey article, The Agentic Organization: Contours of the Next Paradigm for The AI Era, which offers considerations for enabling agentic AI.
