Why most AI projects fail
AI automation requires method, not magic
Does this sound familiar? Your company introduces an AI tool. But your experts bypass it because it causes more work than it saves. The problem isn’t the technology. The problem is the distribution of roles:
The old world: experts as bottlenecks
In traditional approaches, the expert remains at the centre. The AI tool runs in parallel as an aid that the expert must actively use. The result: in the stress of everyday life, the AI is ignored. The expert remains the bottleneck. There is no real automation.
The new world: AI as process leader
Our approach reverses the roles: AI leads the process. It collects information, analyses documents and prepares decisions. The expert only intervenes when the AI agent reaches an impasse, significantly reducing their workload.
