Promptathon: Developing AI Skills in Teams | Alphabees

The introduction of artificial intelligence in organizations rarely fails because of the technology itself. It fails because of adoption by employees. Traditional training formats often don't achieve the desired impact: what's learned fades away, tools remain unused, and the hoped-for productivity gains never materialize. That's why a format pursuing a different approach is gaining importance: the promptathon.

From Training to Community: A Paradigm Shift

Marina Kraft, an active member of the Corporate Learning Community, conducted her third promptathon with 127 colleagues in February 2026. Her observation summarizes what many learning leaders now recognize: AI skills don't develop in the classroom but in shared practice.

The crucial difference lies in the approach. While traditional training delivers knowledge and hopes for later application, the promptathon combines learning and doing in a shared experience. Participants work on real tasks, exchange experiences, and immediately see which approaches work.

For decision-makers in education, this means a fundamental shift in perspective:

From individual training to community of practice:

Sustainable learning emerges through regular exchange and mutual support, not through one-time knowledge transfer.

From mandatory attendance to visible success:

When learning achievements are shared and celebrated, motivation for further development increases.

From perfection to experimentation:

AI competence develops through trying and iterating, not by following rigid rules.

Why Traditional Training Formats Often Fail with AI

The challenge of AI upskilling differs fundamentally from other professional development topics. AI tools evolve rapidly, best practices aren't yet established, and individual value depends heavily on the specific application context.

Traditional e-learning modules or classroom training reach their limits here. They teach fundamentals that may be outdated within weeks. They show examples that don't transfer to one's own work situation. And they end before the real learning curve begins: in daily application at work.

The consequence for many organizations: high investments in training but low actual use of AI tools. Employees return to their workplace, routine takes over, and new skills atrophy due to lack of practice and support.

Elements of Successful AI Upskilling

From experiences with formats like the promptathon, success factors can be derived that are relevant for any organization looking to build AI competencies:

• Regularity over one-time events: Recurring learning formats anchor new behaviors better than individual intensive training sessions.
• Peer learning over pure instruction: Exchange among colleagues creates relevance and promotes transfer to one's own practice.
• Visibility of achievements: When effective prompts, solved problems, and productive applications are shared, a positive cycle emerges.
• Low barriers to entry: The threshold for participation must be low so that even hesitant employees can join.
• Continuous support: Between organized learning formats, learners need points of contact for questions and problems.

The last point particularly deserves attention. The energy of a promptathon dissipates if participants are left on their own afterward. This is where structures that extend beyond the event prove their value.

The Role of Continuous Learning Support

Community events like promptathons provide important impulses. But actual competency development happens between these highlights: when an employee wants to formulate a complex prompt, when a team leader searches for the right AI application for a process, when uncertainties arise in daily interaction with the tools.

This is precisely where AI tutors demonstrate their value. They're available when the question arises, not just at the next organized learning format. They can address the specific situation rather than giving generic answers. And they enable a practice environment where mistakes have no consequences.

For learning leaders, this results in an interplay of various elements:

• Community events like promptathons for shared experiences and motivation
• Structured learning paths for systematic competency development
• AI-powered learning support for individual assistance at the moment of need
• Platforms for sharing best practices and successful applications

Integrating an AI tutor into existing learning management systems like Moodle bridges the gap between organized learning formats and individual learning needs. Learners receive support exactly when they need it, without having to wait for the next promptathon or office hours.

Measurable Adoption Instead of Training Attendance

A rethinking is also required for success metrics. The number of training sessions conducted or attendance rates say little about an organization's actual AI competency. More relevant are questions like: How many employees regularly use AI tools in their work? Which processes have been improved through AI support? How does the quality of interactions with AI systems develop over time?

Organizations that achieve measurable AI adoption combine various approaches. They create opportunities for learning together, as the promptathon exemplifies. They establish structures for continuous support. And they make learning achievements visible, creating positive momentum.

Experience shows: AI competence cannot be mandated, but it can be cultivated. Formats like the promptathon demonstrate that the human factor remains decisive. Shared experimentation, mutual support, and visible successes create the foundation for an organization where AI actually becomes part of daily work.

For decision-makers in education, the task lies in connecting these various elements into a coherent overall concept. The promptathon represents one important building block. The question for every organization is: What additional structures are needed to transform the initial impulse into sustainable competency development?

Frequently Asked Questions