enterprise-ai-strategy-nadella

To evaluate enterprise AI deployment opportunities, apply a three-layer platform model covering infrastructure, model, and application layers to understand how platform generations compound and identify strategic differentiation points for AI product positioning.

Deciding if the AI model is the core product or a scaffolding layer involves applying the SQL Moment Test to evaluate model economics. This determines whether to focus on model development or build first-class scaffolding systems for memory, tools, and entitlements.

The best way to manage change for enterprise AI workflows is through a dual transformation framework addressing both work artifacts and workflows. This requires forward deployment engineering and industry immersion to ensure smooth AI adoption in large organizations.

Yes, enterprise AI strategy requires organizational context, leadership input, and relevant platform and product data to generate actionable recommendations. Without these inputs, strategic frameworks cannot accurately evaluate deployment challenges or AI product positioning.

The scaffolding layer for AI products requires memory, tools, and entitlements as first-class systems. These components support the AI model by managing context, enabling actions, and securing access permissions across the enterprise platform.