The Team @ McKinsey & Co. posted this week a recent conversation with AWS Vice President of Global Sales Greg Pearson on how Amazon is rethinking its go-to-market organization for the agentic era, including their learnings about experimentation, simplification, change management, and translating AI into real customer and business impact.
Link to post here
Key observations:
- Anchor AI strategy on business value and a clear North Star: AWS focused its efforts on its go-to-market organization, where AI could directly shape customer outcomes. AWS defined its desired future state upfront and worked backward to guide investment and experimentation.
- Fix the data foundation before scaling the tools: Growth was constrained by fragmented data and disconnected systems. Momentum came from unifying the underlying data and workflows, so both customer teams and AI could operate from the same view.
- Redesign work, then embed agentic capabilities: AWS avoided layering AI onto existing workflows, instead redesigning work around human-agent collaboration to reduce time spent on routine activities and create more capacity for higher-value customer engagement.
- Design for adoption and connect it to value: Tracking usage provides valuable insight, but it is only one part of the equation. AWS's experience highlights the need to embed adoption into roll-out efforts from the outset and connect usage signals to measurable business outcomes.
- Move from stand-alone agents to coordinated systems: AWS believes the greatest value will come not from deploying more agents, but from enabling agents to share context, draw on common knowledge, and work together across workflows.
#AI #innovationcommunity
- Todor
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Todor Kostov
Director
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