AI is changing not only the way we work, but also the way we learn. Anyone looking for an explanation of safety stock, S&OP, or inventory optimization no longer has to wait for the next seminar. Within seconds, AI can explain concepts, develop examples, answer questions, or create individualized learning content.
This raises an interesting question for the learning and development industry: What role is left for instructors when knowledge is available anytime and anywhere? From our perspective, however, this question falls short. What matters much more is how people learn best and how knowledge ultimately turns into the ability to act and make better decisions.
Not All Learning Is the Same
An interesting distinction can be made between exploratory and exploitative learning. Exploratory learning is about entering new territory and discovering new concepts. Exploitative learning, on the other hand, builds on existing knowledge with the aim of deepening it and applying it more effectively.
The latter is particularly relevant in professional development. A Supply Chain Planner may want to improve forecast accuracy, an S&OP Manager may want to further develop an existing process, or a Supply Chain Manager may want to reduce inventory without compromising service levels. These professionals are not starting from scratch. They want to solve specific challenges in their own working environment more effectively.
This leads to a much more relevant question: Which learning format is best suited to which learning objective?
Building Knowledge Flexibly – and Putting It into Context
eLearning and self-study allow people to build knowledge flexibly and at their own pace. AI expands these possibilities significantly: learners can ask individual questions, generate additional examples, or have complex concepts explained from different perspectives.
Comprehensive programs such as APICS CPIM, CSCP, CLTD, or CTSC continue to play an important role. They do more than teach individual methods: they provide structure, create a broader understanding, and establish a common language for Supply Chain Management.
As information becomes virtually unlimited, this ability to put knowledge into context becomes even more important. The challenge is increasingly not to find information, but to understand relationships and use them to make well-founded decisions.
From Knowledge Provider to Facilitator
This also changes the role of the instructor. A modern seminar should offer more than simply presenting content that participants could read themselves or ask an AI tool to explain.
The strength of an experienced instructor lies in bringing practical experience into the discussion, asking critical questions, challenging perspectives, and helping participants transfer concepts to real business situations. Experienced supply chain professionals also bring considerable knowledge of their own. A good seminar uses this experience and makes the exchange between participants part of the learning process.
The instructor therefore becomes less of a pure knowledge provider and more of a facilitator of a shared learning process.
Experiencing Supply Chain Instead of Just Talking About It
The difference between knowledge and application becomes particularly clear in business simulations. Supply Chain Management is full of trade-offs: more inventory may improve service levels but increase working capital. Larger production batches may reduce costs but negatively affect flexibility and inventory.
AI can explain these relationships very well. But understanding them is different from having to make a decision yourself and then experiencing the consequences.
In our business simulations, participants take responsibility for different functions and immediately see how their decisions affect other areas and overall company performance. Theoretical knowledge is applied, discussed, and combined with experience.
The Future Lies in the Combination
From our perspective, AI is therefore not a competitor to the instructor, but another powerful tool. It can help individualize learning content, generate additional examples, and support instructors in preparing and designing seminars.
At PMI, we therefore combine different learning formats: self-study and eLearning for flexible knowledge building, APICS certification programs for structure and a comprehensive understanding of Supply Chain Management, instructors and guest lecturersfor experience, discussion, and knowledge transfer, and business simulations for learning through decisions and their consequences. AI is now becoming another element of this learning landscape.
We therefore do not believe that AI will make instructors obsolete. Their role is changing: less pure knowledge transfer and more context, discussion, feedback, and application.
Because when knowledge is available anytime and anywhere, another question becomes even more important: How do we turn knowledge into the ability to act?
This is a question we will continue to explore at PMI in our upcoming articles.
