AI has the potential to fundamentally change work methods and roles by automating recurring tasks, supporting decisions, and redistributing responsibilities. Employees are relieved of burdens, while at the same time requirements for skills, collaboration, and leadership are shifting.
In many areas, AI takes over operational tasks that were previously performed manually, such as analyses, reviews, or the preparation of information. This shifts the focus of work: away from routine, toward control, evaluation, and decision-making. Roles evolve without disappearing entirely. Employees work more with AI rather than being replaced by it. This change becomes immediately visible in daily operations, particularly when using customized AI agents.
At the same time, new requirements for skills and responsibility emerge. Employees must be able to contextualize, question, and take responsibility for AI results. Leaders are challenged to enable new forms of collaboration and provide guidance. Decisions become more data-driven, but remain under human responsibility. This shift requires clear role definitions and decision-making frameworks.
Collaboration between business units and IT is also changing. AI projects require closer exchange, iterative coordination, and shared learning. Without clear structures and supporting measures, uncertainties or resistance quickly arise. This is precisely where change management comes in, ensuring that new work methods are understood and accepted.
For these changes to have lasting impact, they must be actively shaped. In combination with training & development and clear integration into AI strategy development, AI becomes an enabler of new, more efficient work methods rather than a trigger for overwhelm or rejection.
