In 1989 Gloria Gery introduced the Electronic Performance Support System (EPSS) as a framework for eliminating unnecessary training while bolstering on-the-job performance through real-time support. Tools and practices evolved through personal computing, mobile technology, the Internet, and human-centered design. It was a significantly new approach to employee onboarding and upskilling to new tasks, jobs, and responsibilities, shifting focus from up-front learning to just-in-time knowledge within a human-centered workflow. Performance support systems significantly reduce cognitive load, cost and effort of achieving worker competency and productivity. Today generative AI (genAI) produces quality text, images, audio, and video via natural language prompts, further fulfilling performance support promises. However, the potential of enterprise performance-centeredness remains unrealized in the AI-integrated workplace. Specific processes, tools, and analytics are needed to optimize AI’s role in supporting human and organizational performance. Besides notable benefits, AI raises new concerns, including alignment challenges between humans and machines (aka “The Alignment Problem”), questionable claims of artificial general intelligence (AGI), fears of intelligent machine takeover, cheating, and marketing hype that confounds responsible adoption. The paper reexamines successful, tailored performance-support solutions, then explores both the opportunities and challenges AI introduces. It addresses concerns in education, workplace learning and performance, cognitive science, neuroscience, and substantial resource demands. Balancing AI’s benefits with these challenges is critical to responsibly integrating AI into effective performance-centered systems. The paper serves as a primer for practitioners across this spectrum of education, learning, and performance that aim to harness artificial intelligence.