Adapting the AI strategy to company size and goals

The development of an AI strategy varies depending on company size and specific requirements. While large companies should often pursue a comprehensive AI strategy integrated into all areas of the corporate strategy from the outset, it may initially be sufficient for smaller companies to start with individual projects. These projects allow for initial experiences and insights that provide a foundation for later, more extensive investments and strategic decisions. It's about first developing an understanding of how AI can improve specific business processes without immediately tying up significant resources. In any case, and regardless of the company's profile, an AI strategy represents an iterative learning process. The development into a data-driven company is never complete. The strategy should always be linked to the development of use cases and continuously adapted.

How to develop effective use cases?

The core of every AI strategy should be the identification and implementation of use cases that provide a direct, measurable added value for the company. Successful AI implementation requires a deep understanding of one's operations and potential influence areas and use cases for AI. Generally, embedding AI into corporate processes, services, or products is conceivable. Within the company's service spectrum, AI offers the opportunity to stand out through innovation. On one hand, existing products or services can be extended with AI, or entirely new business models can be created. On the other hand, integrating AI into business processes is suitable for reducing costs and improving quality.

Practical applications

Possible use cases for AI could be the following:

• Making better, more precise decisions with AI: AI optimizes decision-making processes through data-driven insights. It identifies patterns that, for example, show sales teams which customers are likely to be won, supports banks in granting credit, and helps in healthcare to plan treatments effectively.

• Efficiency gains through AI: AI reduces costs by increasing process efficiency and improving quality. Applications like ChatGPT can be used to automate tasks, from responding to customer inquiries to documentation. In production, AI enables automated quality controls, while in agriculture, machines can be used for autonomous harvesting, counteracting the shortage of skilled workers or leading to efficiency increases and cost savings.

• Personalization with AI: AI enables advanced personalization that can significantly improve customer interaction, medical treatments, and education. Customers receive tailored problem-solving offers, AI enables individualized therapy plans or drug development in healthcare, and it adjusts learning tasks to the level of each student in education. These personalized experiences increase customer satisfaction, improve treatment outcomes, and promote a more effective learning process.

• New business models and values with AI: AI drives the development of new business models by enriching products and services with innovative functionalities such as self-parking cars and making services more efficient, thereby reaching more customers. Additionally, AI can develop new products or materials that were previously too costly or technically unfeasible. By tapping into new markets and offering especially innovative products and services, AI creates new values and transforms industries.

AI enables companies to work more efficiently and sustainably secure their competitiveness. To successfully establish AI in companies and remain competitive, the strategic consideration needs to be complemented by the appropriate technological prerequisites and data, a corresponding management process (see compass topicsOrganization and Culture and Mindset) and beyond the corresponding competencies, see Compass topic Talents and Competencies. Applying for grants or acquiring a venture capitalist for your AI project can also represent a significant competitive advantage (see Compass topic Financing and Funding). Of course, legal and ethical frameworks must also be considered. The Compass topics Law and Regulation and Ethics go into these aspects in more detail.

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