This article addresses the rapid transformation of the enterprise learning technology market under the influence of artificial intelligence, framing the shift as a move from formal, structured training toward AI-powered, dynamic, and personalized content delivery. The author, writing from the perspective of an industry analyst with disclosed commercial partnerships, argues that AI represents the optimal use-case for corporate learning and that incumbent LMS vendors face existential pressure to adapt. Key evidence is drawn from a vendor-by-vendor market scan covering learning management systems, AI-powered content platforms, skills intelligence tools, assessment technologies, and employee enablement solutions. The article identifies approximately $4 billion invested in legacy learning infrastructure as the primary barrier to adoption. Implications drawn include the eventual obsolescence of traditional course-building approaches, the emergence of 'content intelligence platforms,' and the redefinition of L&D's organizational role toward enterprise knowledge management. The piece concludes by asserting that foundational learning needs — compliance, onboarding, leadership development — will persist despite broader transformation. Key insights: Approximately $4 billion is estimated to be invested in legacy LMS systems, content libraries, and development tools, creating structural inertia against AI adoption in corporate learning. The article identifies a market trajectory in which 'course builder' companies are repositioning as 'expertise curators,' with AI handling content generation and vendors competing on content quality, labeling, and competency models. Employee enablement — historically managed outside L&D by IT, Sales, or Support functions — is identified as a major emerging use-case for AI-native learning platforms, potentially redefining the organizational scope of L&D. Practical takeaways: Organizations with incumbent LMS vendors can evaluate the pace of AI integration by assessing whether vendors have moved toward dynamic, post-SCORM content models as a signal of architectural readiness. AI-powered skills intelligence platforms are increasingly being integrated with learning systems, enabling organizations to connect granular skills assessments directly to learning recommendations at scale.