Three models for sustainable AI strategies in business practice

The development of artificial intelligence (AI) has reached a new stage of maturity. After years of fragmented pilot projects, AI is now at the heart of corporate value creation. Companies that continue to rely on selective applications risk not only inefficient use of resources, but also strategic setbacks. AI should therefore now be strategically anchored in the company.

Our white paper identifies three key patterns that recur in successful AI initiatives worldwide:

Value comes from the integration of AI, data and cloud in a common technological ecosystem.

1. The value is created through the integration of AI, data and cloud in a shared technological ecosystem.
2. The type of AI deployment depends largely on whether it is function- or industry-specific (vertical) or cross-functional (horizontal) - with direct consequences for the sourcing strategy.
3. Companies should differentiate between whether AI provides generally available knowledge or generates specific insights based on proprietary data - and derive their make-or-buy decisions from this.

Our analysis clearly shows that the real benefit does not come from individual tools or short-term efficiency gains, but from a coherent and coordinated architecture. Companies that rely on a networked data landscape and reusable, quality-assured data products create the basis for scalable and differentiating AI applications - both in day-to-day operations and for strategic decision-making processes.

When choosing between in-house development and purchasing, differentiation is the key: standardized, vertical AI solutions offer robust industry practice and enable rapid deployment. At the same time, real differentiation is achieved above all where companies combine their own data with horizontal AI and develop tailor-made applications on this basis - for example for risk assessment, customer segmentation or offer optimization.

The three patterns form the foundation for modern AI governance. They help companies to deploy their resources in a targeted manner, avoid dependencies and see AI not as a technology project, but as a strategic design field. The complete white paper offers detailed recommendations for action, a practical decision-making grid and concrete examples of successful implementations - a compass for anyone who wants to anchor AI in their company in the long term.