The advent of artificial intelligence (AI) tools necessitates the development of human skills that allow workers to use these new technologies to create value that AI tools cannot on their own. Learning programs and methods need to be adapted to help humans learn in an accelerated and effective manner. There is an ongoing debate about the role technology-based conceptual learning should have in developing human capital. On one hand, these technologies can help workers acquire new skills as old skills are taken over or made obsolete by machines and software. On the other hand, experienced-based learning might be a more effective method to distinguish uniquely human capabilities from AI prowess. Such a debate may ultimately be infructuous. In the future, both modes of learning will have to be leveraged to enhance human capital abilities and distinguish these skills from what software (artificial intelligence) and machines (robots) can do. Rather than allowing learning modes to swing like a pendulum between technology-based learning and experience-based learning, companies that leverage both modes would create optimal learning environments for training the next-generation workforce.