For a long time, introducing new technology meant one thing above all else: a project. It was planned, commissioned, implemented — and once it went live, the job was largely done. People talked about requirements, interfaces, and integrations. The goal was to deliver something technical that works.
Artificial Experts Do Not Just Change Processes — They Change How We Think About Work
With Artificial Experts, a fundamental paradigm shift takes place. Artificial Experts are far more than installed systems or usable tools. They are virtual employees who take over entire areas 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, messaging services, and more) — and this is the crucial point — they are designed to continuously evolve and learn.
This potential requires a new approach: companies do not simply deploy Artificial Experts — they train them.
What used to be a software rollout is now the beginning of a real collaboration. Just like a new team member, Artificial Experts require active onboarding, solid training, and continuous development.
While the classic project approach delivers automation, the full potential of virtual experts only emerges when companies adopt the mindset of a trainer. Those who see Artificial Experts as learning colleagues unlock true agency and operational support.
Artificial Experts are not finished when they go live — that is when they begin to learn.
This development fundamentally changes the logic of technology adoption. While traditional IT systems are expected to run stably after implementation, the true value of an Artificial Expert only unfolds through daily work within the organization.
Their skills and knowledge are continuously expanded and refined through training, coaching, and ongoing care.
Artificial Experts operate precisely at the intersection of technology and teamwork. They are technologically advanced, yet their real impact emerges through interaction with people, systems, and processes. That is why their training is the key to success.
The Learning Organization: Humans and AI as a Training Team
This shifts the discussion from pure system functionality to a new strategic level. The key question is no longer, “What should the AI do?” but rather, “What must it learn to become a valuable member of our team?”
This shift — from static, deterministic customization to dynamic competence development — is essential and brings with it new and exciting responsibilities.
This new perspective places business departments in a central role. As trainers and mentors, they are responsible for developing their virtual colleagues. They design onboarding, accompany ongoing training, and provide continuous feedback.
The vision is clear: organizations need people who take responsibility as AE trainers for the development of their digital colleagues.
At the same time, one crucial aspect elevates the training process to a new level: humans who train Artificial Experts are themselves supported by experienced virtual expert trainers.
Operating proprietary agent platforms is fully replaced by barrier-free communication between human and virtual colleagues. This creates an intelligent, scalable, and systematic training process.
A New Mindset: Partnership Instead of Automation
The impact of Artificial Experts goes far beyond features and interfaces. It unfolds through deliberate training. Their performance is a direct result of their education.
And they learn faster and more sustainably the more actively they are trained, guided, and supported — just like their human colleagues.
Those who treat Artificial Experts like a project gain efficiency. Those who train them as employees gain colleagues who take initiative, assume responsibility, and grow together with the team.