Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for all applications of artificial intelligence. The development of competences and experts in the field of artificial intelligence must take place at least parallel to the process of every technological decision, but not at the end of the implementation of an AI strategy. Outsourcing must not be part of this strategy. 'Not to boil the ocean', in other words: small, agile, consecutive pilot projects alone are not enough to develop an AI strategy. Parallel to the pilot phase, a more far-reaching strategy should be developed together with the management to promote cross-departmental, process-independent and data-driven decision-making and activities.