Solving the AI talent problem isn’t just about hiring—it’s about building the internal systems to grow, distribute, and sustain AI expertise across the organization. Start by mapping which roles need deep AI fluency (e.g., ML engineers, data scientists) and where you need AI literacy—especially among decision-makers, operators, and policy leads.

The Six Layers Framework™ helps you approach talent development strategically:

• Layer 4 (Services): This is where AI transformation becomes real. Build training programs, internal communities of practice, and integration teams that combine technical, operational, and compliance expertise. If AI lives in silos, it dies in production.

• Layer 5 (Influence): Shift the narrative: AI isn’t just for specialists—it’s a core competency for modern leadership. Use influence channels (town halls, executive briefings, onboarding) to make AI capability part of your organization’s identity.

• Layer 2 (Models) and Layer 3 (Applications): Adopt tools and platforms that lower the barrier to entry. Democratizing AI starts by making it usable—not just by data scientists, but by frontline staff through intuitive applications and copilots.

The Framework ensures you’re not treating talent as a narrow HR issue—it becomes a strategic lever woven through how you build, scale, and lead with AI. Ultimately, the goal is not just to have AI experts—but to become an AI-capable organization at every layer.