In a nutshell: AI systems amplify inefficient processes rather than solving them; process optimization must precede AI implementation.
Organizations that implement AI systems without fully understanding their existing business processes invest in costlier problems instead of genuine improvements. This reflects a fundamental misunderstanding of digital transformation.
The core problem lies in sequencing: many organizations fall into the misconception that AI technology itself acts as an optimizer. In reality, AI can only create value when built upon transparent, optimized processes. If the foundation is chaotic or inefficient, AI systematically amplifies these deficiencies at scale.
A concrete example: a company still using faxes lacks the digital foundation for automation. Implementing AI on such legacy structures means deploying expensive models to repair fundamental process deficits – instead of first cleaning up the processes themselves.
For CTOs, this implies a strategic reversal: process optimization and digitalization must be prerequisites, not consequences of AI adoption. Only with clear, documented, and efficient workflows can AI unlock its potential – and justify the investment economically.
Source: itwelt.at · Published 10 June 2026
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