06.10.2025
AI agents are becoming a strategic success factor
IBM study proves: German companies are investing heavily in autonomous AI systems
The transformation is clear: 64% of German companies are investing their AI budgets directly in their core business – and no longer just in experimental pilot projects. A recent IBM study shows that AI agents are evolving from technical gimmicks to business-critical infrastructure.
The figures speak for themselves
An eightfold increase in AI workflows by 2025 – this forecast from the IBM study marks a turning point in the German corporate landscape. While 2024 was still a year of experimentation, companies are planning to put autonomous AI systems to productive use in business-critical areas in 2025.
The strategic shift is remarkable: instead of isolated IT projects, companies are integrating AI agents directly into their value chains. Investments are being channeled specifically into areas that generate direct business impact.
Specific use cases are revolutionizing day-to-day business
Customer service and support:
AI agents handle complex customer inquiries and only forward critical cases to human experts.
Financial processes:
Automated invoice processing, liquidity planning, and risk assessment using intelligent systems.
Supply chain management:
Proactive supply chain optimization and predictive maintenance using self-learning algorithms.
HR and human resources:
From candidate selection to employee development, AI agents support strategic HR decisions.
SAP as a pioneer of the AI agent revolution
SAP users have some cool opportunities: SAP Build Process Automation and SAP AI Core let you smoothly integrate AI agents into your existing business processes. The SAP Business Technology Platform (BTP) acts as the main hub for company-wide AI workflows.
SAP Joule, the generative AI assistant, is already demonstrating how AI agents can simplify and accelerate complex ERP processes. From automated order processing to intelligent financial analysis, the possibilities are endless.
Mastering strategic challenges
Change Management:
73% of companies see employee acceptance as the biggest hurdle. Successful implementations begin with transparent communication and targeted training programs.
Data quality:
AI agents are only as good as their data foundation. Companies must invest in data governance and data integration.
Governance and Compliance:
Autonomous systems require clear rules and control mechanisms, especially in regulated industries.
Your roadmap to AI agent transformation
- Phase 1 (Q4 2025): Identification of suitable use cases and pilot implementation
- Phase 2 (Q1-Q2 2026): Scaling of successful pilots to other business areas
- Phase 3 (Q3-Q4 2026): Company-wide integration and optimization of the AI agent infrastructure
The message of the IBM study is clear: companies that invest in AI agents now will gain sustainable competitive advantages. The question is no longer whether, but how quickly the transformation will succeed.
