where learners repeatedly practice, adapt, and make decisions under changing operational conditions. AI- enabled role players, dynamic injects, tailored feedback, and continuously adjusted complexity levels create learning experiences that adapt to learners in real time. AI is already used to accelerate cur- riculum development, expand access to learning, and enhance instructional delivery. While these applications are important, they largely improve the performance of the existing model. The more impactful change emerges when AI begins personalizing devel- opment around individual needs, integrating learning directly into the workflow, and adapting instruction based on learner behavior and perfor- mance. At that point, AI is no longer improving how education and train- ing are delivered; it is changing the model itself. Continuous evaluation and adap- tive learning. When people reflect on Netflix’s disruption of Blockbuster, they typically focus on streaming technology. Streaming certainly mattered, but one of Netflix’s most important innovations was its ability to continuously learn from user be- havior and adapt recommendations, creating a personalized experience that connected viewers with content they were likely to value but might otherwise have overlooked. This shift toward learning from user behavior has important implications for evalu- ating acquisition education. Much of how training effective- ness is measured still relies on trans- actional measurement models. Success is assessed through end-of- course surveys, Likert-scale satis- faction measures, Kirkpatrick Level
1 and Level 2 evaluations, comple- tion rates, and Net Promoter Scores. These approaches provide useful in- formation regarding learner reactions and short-term knowledge acquisi- tion; however, they primarily mea- sure reactions to instructional events rather than assessing how expertise develops, performance evolves, and learning transfers into outcomes in the workplace. AI makes possible a transition from evaluating learning after instruction to continuously assess learning dur- ing execution. In this model, AI ob - serves and adapts to learner behav- ior. Evaluation no longer exists as an event conducted after instruction; it becomes part of the learning process. AI-enabled systems analyze learner interactions in real time, identify developmental patterns, personal- ize instruction, recommend targeted experiences, monitor competency progression, and dynamically adapt learning pathways. AI can also func- tion as a personalized trainer, adjust- ing guidance, pacing, reinforcement, and support in real time based on the learner’s demonstrated needs and behaviors. The evolving role of faculty. The role of faculty also changes as learn- ing becomes more personalized, adaptive, and embedded within op- erational work. Instead of functioning as content transmitters, faculty oper- ate as coaches, facilitators, develop- mental guides, and orchestrators of adaptive learning environments. Hu- man expertise does not become less important; it becomes more impor- tant. AI relieves faculty of routine in- struction and administrative burdens, allowing for greater focus on mentor-
ship, judgment development, context interpretation, and coaching. The Strategic Challenge Blockbuster did not fail because it stopped innovating. In many ways, it became exceptionally good at im - proving what had made it success- ful. Blockbuster’s failure was con- tinuing to optimize the storefront model while advances in technology were reshaping consumer viewing behavior and preferences for access- ing video content. The same risk now confronts acquisition education, op- timizing a delivery model that might not meet future learning needs of the workforce. Modernization efforts such as im - proving the efficiency, accessibility, and scalability of acquisition instruc- tion through expanded certifications, enhanced digital delivery, and re- fined competency frameworks build upon the longstanding strengths of a course-centric and standardized learning model. Yet the workforce itself is chang- ing. Acquisition professionals increa-
Questions about whether traditional acquisition education and training structures will continue meeting future workforce demands are not just theoretical.
16 DEFENSE ACQUISITION MAGAZINE | JULY – AUGUST 2026
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