All roles that make strategic decisions, are responsible for processes, or are affected by AI applications should be involved in developing an AI strategy. An AI strategy is not purely an IT task, but a company-wide initiative. Only when different perspectives come together does a viable and implementable vision emerge.
The involvement of executive management or top management is central. They set the strategic guardrails, prioritize investments, and ensure that AI initiatives are aligned with corporate objectives. Without this backing, the strategy often remains non-binding. In addition, business units should be involved, as they have the best knowledge of processes, data sources, and specific application needs. Their perspective is crucial for defining realistic use cases and building acceptance.
IT plays another key role. It evaluates technical feasibility, integration capability, and security requirements. At the same time, functions such as data protection, information security, compliance, or legal should be involved early on to address regulatory and ethical issues. This is particularly relevant for subsequent governance.
Last but not least, HR and organizational development play an important role. As part of change management support, they ensure that aspects such as competency development and role changes are appropriately considered and strategically managed throughout the process.
A structured strategy process ensures that these different stakeholders are purposefully involved—without unnecessarily complicating decision-making processes. This creates an AI strategy that is technically sound, broadly supported, and implementable in practice.
