As artificial intelligence becomes embedded in enterprise operations, organizations are moving beyond simple tool adoption to develop comprehensive frameworks for building internal AI expertise. Rather than mandating that employees use AI, companies are now asking a more strategic question: how do we create a workforce capable of building AI-powered solutions? Mike Lewis, Chief AI Architect at TiER1 Performance, outlined this shift in a discussion of the L0–L3 proficiency framework, which maps organizational AI capability from basic literacy through expert system builders. The framework represents a significant evolution in enterprise AI strategy, particularly around identifying and developing non-technical builders who can create AI-powered solutions without deep machine-learning expertise. Rather than assuming technical teams alone will drive AI transformation, organizations are recognizing that subject-matter experts and domain practitioners often have the tacit knowledge necessary to turn into scalable, AI-enabled processes. This approach addresses a persistent challenge: AI resistance within organizations, which often stems from unclear value propositions and top-down mandates rather than genuine resistance to the technology itself. The shift reflects a maturing AI economy where competitive advantage increasingly depends not on adopting AI tools, but on demonstrating measurable business value from those tools. By codifying proficiency levels and identifying the right people to build solutions, companies can transform tacit knowledge into durable processes while building organizational capability that compounds over time.