The introduction of AI doesn’t require a traditional IT project – it requires continuous training.
- Jakob
- Aug 4
- 2 min read
For a long time, introducing new technology was primarily one thing: a project.
It was planned, commissioned, implemented – and once it went live, the job was mostly done. We talked about requirements, interfaces, and integrations.The goal was to deliver something technical that works.
💼 Artificial Experts don’t just change processes – they change how we think about work.
With Artificial Experts, we are witnessing a paradigm shift. Because AEs are far more than installed systems or controllable tools.They are virtual team members who take on entire fields of responsibility within an organization.Each Expert has a distinct identity, a stable long-term memory, and the ability to understand the context of their actions. They communicate across all common channels (such as phone, email, messenger, etc.) – and most importantly, they are built to continuously evolve and learn.
This potential demands a new approach:
Companies don’t just implement Artificial Experts – they train them.
What was once a software rollout is now the beginning of a true collaboration.Just like with a new employee, Artificial Experts require active onboarding, structured training, and continuous development. Where classic project thinking delivers automation, the trainer mindset unlocks the full potential of virtual experts.Those who see Artificial Experts as learning teammates open the door to real agency and operational support.They’re not “done” when launched – they’re just beginning to learn.
This shift changes the logic entirely. While traditional IT systems are expected to simply run stably after rollout, an Artificial Expert’s full potential only unfolds through daily interaction. Their knowledge and abilities are continuously refined through training, coaching, and support.
Artificial Experts operate right at the intersection of technology and teamwork. They are technically sophisticated, but their true impact emerges from their interaction with people, systems, and processes. That’s why their training is the key to success.
🧠 The Learning Organization: Humans and AI as a Training Team
This reframes the discussion from system functionality to strategic enablement. The core question is no longer: “What should the AI do?” But rather: “What does the AI need to learn to become a valuable team member?”
This shift – from static, deterministic customizing to dynamic skill development – is essential and brings new and exciting responsibilities.
Business departments now take on a vital new role: As trainers and mentors, they become responsible for the growth of their virtual colleagues.They guide onboarding, support continuous development, and provide ongoing feedback.
The vision is clear: We need people who take ownership as AE trainers and actively shape the development of their digital coworkers. And there's more: Human trainers are themselves supported by experienced virtual trainers during the onboarding of Artificial Experts.
The need for platform-specific tools or complex configurations is eliminated – replaced by a barrier-free dialogue between humans and their virtual counterparts.The result: a smart, scalable, and systematic training process.
🌱 The New Mindset: Partnership over Automation
The impact of Artificial Experts goes far beyond features or interfaces. It unfolds through targeted training.Their performance is a direct result of how they are developed.And just like human colleagues, they learn faster and more sustainably when they are actively trained, supported, and empowered.
Treating Artificial Experts like a project creates efficiency. Training them as colleagues creates engaged teammates who take initiative, assume responsibility, and grow with your team.
