AI trends 2030 — the new Industrial AI trend report

  • AI and Industry 4.0 — Developments & Impacts
  • The most relevant AI use cases & real use cases
  • AI agents in industrial environments
  • AI integration using Model Context Protocol (MCP)
  • Strategic fields of action for the mechanical engineering, energy, logistics & armament industries
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What challenges will industry have to overcome by 2030 with the help of AI?

AI will determine competitiveness by 2030. Our AI trend report “AI Trends 2030” shows how Agentic AI, Model Context Protocol (MCP) and sovereign data strategies are changing entire industries — from industry and logistics to energy and software. With clear recommendations for action, practical examples and a realistic view of opportunities and risks.
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Content in detail

AI between hype and reality

AI is no longer a topic of the future, but an economic reality. This chapter summarizes the current AI revolution and shows why today's decisions will determine 2030.

AI agents & integration via MCP

AI only becomes proactive and controllable through context-enabled agent architectures. MCP provides the basis for deeply integrating AI into existing software, production and OT/IT landscapes.

AI application scenarios up to 2030

From production to logistics to energy: Specific scenarios show how AI automates processes, supports decisions and unlocks new efficiency potential in key industries.

Strategic fields of action

Data sovereignty, sovereignty, choice of models and governance are becoming management tasks. This chapter provides clear guidelines for a controlled, sustainable AI strategy up to 2030.

    Case studies & partnerships

    Real use cases show how AI works beyond pilot projects. Successful implementation requires partners who bring together technology, integration, and industry reality.

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    A graphic that describes how an MCP server is integrated into legacy software

    AI trend in focus: Agentic AI and MCP

    Agentic AI marks the next evolutionary step in artificial intelligence. While today's AI systems usually respond reactively to inquiries, agent-based architectures enable proactive, context-aware decisions across system boundaries for the first time. The Model Context Protocol (MCP) creates the necessary regulatory framework: It combines data, goals, roles and governance to form a controllable overall system. The trend report shows why Agentic AI and MCP will be the decisive success factor for integrated, sovereign AI solutions by 2030.

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