How is the curriculum determined in AI training?

How is the curriculum determined in AI training?

In corporate AI training, one of the most critical issues is undoubtedly the suitability of content to the organization. The main bottleneck here stems from the disconnect that arises when the training provider and the participating organization or team meet for the first time.

While pre-training meetings can help bridge this gap, this process alone is generally insufficient.

In reality, the expected outcome of AI training should not be limited to replicating a business process that is feasible with current technological capabilities. Managing business processes with AI is distinct from project management techniques and applications that have previously entered our workflows.

The first and most significant difference lies in AI's ability to abstract and integrate other technologies. This dynamic nature means that the potential to use AI at a level far beyond its current iteration is always present and continuously evolving.

Consequently, if individuals only acquire know-how or memorize how to work with AI, it will not generate the right impact on the technological transformation side. Competencies such as understanding the fundamentals of AI technology, perceiving its limitations, and envisioning how these boundaries can evolve—frequently highlighted in European Union incentive programs—are essential for the completion of the technological transformation process.

Given this, it is most effective for an ideal AI program to target four main pillars and structure its content accordingly:

 
1. Understanding the fundamentals of AI technologies

 
2. Being Tool Free (Using AI without being tied to any specific platform)

 
3. Being Domain Free (Producing computer-based solutions based on AI capabilities)

 
4. Using AI within the boundaries of data security and ethical limits

Training programs covering these pillars will not only teach the best practices of the moment but also enable individuals to adapt to future developments in this field.

Of course, while it is not always possible to enrich these processes with real-life examples from the current business practices of existing firms, doing so will optimize the training experience when possible.

As the NobleProg team, drawing on the experience gained from our international business expertise, we begin all our training processes with pre-training expectation surveys. In this survey, participants briefly describe who they are, the essence of their work, and their expectations from the training.

In this way, when preparing our training content, we avoid non-scientific inventory tests and eliminate time costs. At the same time, we build processes that are as close as possible to the ideal approach discussed in this article.