Artificial Intelligence is becoming a core element of corporate strategy across industries. Beyond technical capabilities, public AI strategies and dominant regional approaches to AI development increasingly shape how organizations design, adopt, and govern AI systems.

In the United States and China, AI strategies are closely linked to platform leadership, ecosystem control, and strategic positioning of AI providers and users. These approaches influence organizational decisions such as open vs. closed AI architectures, platform participation, partnership strategies, and “AI-first” orientations.

In contrast, the European Union has primarily approached AI through regulatory and governance-oriented frameworks. European organizations therefore often develop and deploy AI systems within strategic and technological ecosystems shaped by U.S. and Chinese AI providers, raising important questions about strategic autonomy, sovereignty, positioning, and long-term competitiveness.

From a Business Information Systems perspective, understanding how public AI strategies translate into organizational AI strategies is essential for both research and practice.

Research Objective
The thesis examines how different regional AI strategies in the EU (e.g., DACH), United States, and China influence corporate AI strategies, focusing on both AI providers and AI-adopting organizations.

Exemplary Research Questions

• How do public AI strategies differ across the EU, U.S., and China?
• How do these strategies shape organizational AI decisions, such as:
  • AI-first strategies
  • Open vs. closed AI architectures
  • Platform and ecosystem participation
• How do AI providers and AI adopters align their business models and communication strategies with regional AI strategies?
• What strategic challenges and opportunities arise for European organizations operating within globally shaped AI ecosystems?

The thesis follows a comparative qualitative research design, potentially complemented by quantitative elements.

Data Sources

• Public AI strategies, policy papers, and regulatory frameworks (EU, U.S., China)
• Corporate strategy documents, technical blogs, and public communications of selected AI providers and adopters
• Industry reports and selected media sources on AI strategy and ecosystems

Methodological Approach

• Comparative analysis of regional AI strategies
• Case-based analysis of selected organizations linking public AI strategies to corporate AI decisions
• Optional: Exploratory time-series or event-based analyses examining how major AI-related announcements or policies relate to market reactions (e.g., stock prices or sector indices)

Knowledge of Chinese is an advantage but not required.

• Close supervision and regular academic exchange
• Integration into a motivated research team working on AI strategy and governance
• A highly relevant topic at the intersection of AI, strategy, and information systems
• Flexible start date and an expected completion time of approximately six months

Please send a short email to teresa.grauer@unisg.ch. A virtual meeting will be arranged to discuss details and potential focus areas.