Scaling AI isn’t about doing more pilots—it’s about turning isolated successes into institutional capability. Start by selecting one or two high-impact, cross-functional use cases tied to measurable business outcomes. Then form a delivery squad that spans operations, IT, and compliance—your goal is to embed AI into workflows, not bolt it on.

The Six Layers Framework™ helps leaders move from pilot to scale by clarifying what needs to be aligned across the system:

• Layer 1 (Infrastructure): Do you have scalable compute, storage, and data pipelines to support production AI?

• Layer 2 (Models & Platforms): Are your models and platforms enterprise-grade and governable—or still experimental?

• Layer 3 (Applications): Are the AI tools designed for real users—or stuck in a lab environment?

• Layer 4 (Services): Do you have integration expertise, change management capacity, and assurance practices to deploy safely at scale?

The Framework acts as a diagnostic and planning tool: it helps you spot what’s missing, build horizontal alignment across departments, and structure repeatable playbooks for adoption. It ensures your scaling strategy isn’t just technical—but organizationally viable, trusted, and resilient.