German Companies Struggle to Scale Agentic AI Amid Integration and Change Management Challenges
Lünendonk study reveals German companies face major challenges scaling Agentic AI due to integration, data quality, and organizational barriers despite growing experimentation.
- • Only 30% of companies scale more than 25% of AI prototypes into production.
- • Agentic AI enables autonomous decision-making and is being tested or used by about 38% of companies combined.
- • Key challenges include system integration, data quality, and organizational adaptation.
- • By 2028, 73% of decision-makers expect autonomous AI agents to become significantly more relevant.
Key details
A recent study by Lünendonk highlights the significant hurdles German companies face in advancing the use of AI technologies, particularly Agentic AI, within their business operations. Despite widespread experimentation, only 30% of surveyed firms manage to scale more than 25% of their AI prototypes into productive use, underscoring a gap between ambition and implementation.
The study, surveying 150 IT and business leaders from medium-sized and large companies across multiple sectors, found challenges stem more from change management, data quality, and organizational adaptation than from technological limitations. Successful AI integration depends heavily on cross-departmental collaboration and clear assignment of responsibilities, with 60% of companies emphasizing the need for realistic expectations about AI capabilities.
Agentic AI, characterized by autonomous decision-making agents that can plan and execute complex tasks independently, is emerging as the next wave of AI adoption. Currently, 20% of companies are testing Agentic AI in pilot scenarios, and 18% have already implemented it in specific contexts such as back-office processes, cybersecurity, and customer service. However, large uncertainties remain regarding system integration, data quality, governance, and traceability of automated decisions.
Looking ahead, 73% of decision-makers anticipate autonomous AI agents will play a significantly larger role by 2028, marking Agentic AI as a critical area for future business transformation. Advanced organizations increasingly focus on establishing solid organizational frameworks and involving both IT and business units early in AI projects to improve scaling success.
This content aligns with broader trends in AI adoption, as German businesses increasingly recognize the strategic importance of AI for efficiency and innovation. However, successful scaling requires overcoming noted barriers through collaborative efforts and structured change management, supporting the notion that technology readiness alone is insufficient.
As Agentic AI matures, companies must address integration complexities and enhance data reliability to fully realize the technology's potential benefits within their operational models.