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As AI agents evolve from passive tools to active collaborators, they are reshaping how work gets done, who does it, and how teams are organized. However, extending this functionality across your organization is complex and requires careful consideration. An overview of this 30-page report: Three essential components for scaling agent AI And turn it into a true performance enabler. 1) Chassis, or strategic technical framework; It provides a secure, open foundation for connecting agents, models, and systems across the enterprise to support orchestration, interoperability, and scalability. 2) Fuel, or a high-quality, well-managed data stream. Power adaptive decision-making through enterprise-wide integration, accessibility, and real-time flows. and 3) Powertrain or human-AI collaboration Align actions to KPIs and build in accountability to transform potential into measurable results. The report examines each component in detail, Starting on page 21, you'll find an action guide designed to put these ideas into practice. For example, one of the recommended actions to enable a continuous flow of data between agents is to conduct a quick audit of your data governance framework to identify bottlenecks slowing access to high-quality data and identify high-impact data sources that are most important to agent decision-making. Other ideas will also be discussed. As a bonus, I'm resharing the McKinsey article. The Agentic Organization: Contours of the Next Paradigm for The AI Era provides considerations for making agent AI a reality.
