Report on AI Adoption in the DACH Region: Insights from OMR Festival 2025 Survey

1. AI Maturity Segments

Our OMR survey identified five AI maturity levels among DACH businesses, reflecting their adoption stage:

• Curious but Cautious: Aware of AI but not yet implementing.
• Experimenting with Tools: Testing AI in pilot projects.
• Looking to Automate: Using AI to automate specific processes.
• Scaling & Optimizing: Integrating AI across operations.
• Advanced & Agent-Driven: Leveraging advanced AI, including autonomous agents.

Here’s a breakdown based on our survey, with comparisons to other studies:

Maturity Level	Typical Company Profile	Current Activities	Needs	Key Challenges
Curious but Cautious (35% of respondents)	SMEs in retail, services; CEO or dept. head	Researching AI, no active use	Education, use case scoping	Lack of expertise, cost fears
Experimenting with Tools (30%)	Mid-sized in marketing, tech; IT or innovation lead	Piloting tools like chatbots	Tool selection, integration	Data quality, legacy systems
Looking to Automate (20%)	Large firms in logistics, manufacturing; ops manager	Automating supply chain, maintenance	Workflow automation, data strategy	Data access, change resistance
Scaling & Optimizing (10%)	Large corporations in finance, automotive; CIO	Running multiple AI projects	Governance, advanced analytics	Coordination, compliance
Advanced & Agent-Driven (5%)	Tech startups; CTO	Using AI agents for innovation	Research, proprietary tech	Complexity, regulations

Comparison to Sources:

Our survey aligns with Bitkom (2024), which found 20% of German firms using AI and 37% planning deployment, reflecting a similar cautious majority (Bitkom, 2024).

However, our sample shows a higher proportion of early adopters (65% in Curious or Experimenting stages) than the Swiss AI Report (2022), which noted 80% at rudimentary levels (Mindfire & W.I.R.E., 2022).

The low percentage of Advanced firms (5%) matches McKinsey’s finding that only 1% of global firms are AI-mature (McKinsey, 2025).

2. Common Use Cases in DACH

Our survey revealed the top AI use cases among DACH businesses, particularly mid-sized firms. These applications also resonate with the identified demand profiles:

• Customer Service (40% of respondents): Chatbots for inquiries, e.g., a Hamburg retailer automating support; this can also help sales teams pre-qualify leads and manage initial contact volume.
• Marketing (35%): Personalized campaigns and content generation, like a Berlin e-commerce firm using AI for ads. This directly addresses the need for scaling quality content across various social media platforms and improving SEO.
• Operations (20%): Supply chain optimization, e.g., a Munich logistics company streamlining routes. While the survey primarily highlighted logistics, AI in operations can also be pivotal for developing internal knowledge bases and automating process documentation, addressing concerns about knowledge retention.
• HR (15%): Recruitment automation, such as a Stuttgart manufacturer screening candidates, which aligns with the HR Director's needs.
• Finance (10%): Fraud detection, like a Zurich bank using AI for risk analysis.

Comparison to Sources:

These use cases align with Visual Capitalist (2025), which ranks customer support and content creation as top AI applications (Visual Capitalist, 2025).

AIMultiple (2025) also lists predictive analytics and customer service as common, matching our findings (AIMultiple, 2025).

Our survey shows slightly higher marketing adoption (35%) than Bitkom’s broader German data, possibly due to OMR’s marketing-focused audience (Bitkom, 2024).

3. Barriers to Adoption

The OMR survey identified key barriers to AI adoption:

• Lack of Expertise (45%): Many lack in-house AI skills.
• Integration Challenges (30%): Legacy systems hinder AI implementation.
• Compliance/Privacy Concerns (25%): GDPR and data privacy are major issues.
• Fear of Disruption (20%): Resistance to changing workflows.

Comparison to Sources:

The expertise gap (45%) aligns with the Swiss AI Report’s 33.7% citing data issues (Mindfire & W.I.R.E., 2022) and Forbes’ note on skill shortages (Marr, 2024).

Compliance concerns (25%) are slightly lower than the Swiss AI Report’s 43.8% worrying about incorrect AI results (Mindfire & W.I.R.E., 2022), possibly due to our sample’s tech-savvy nature.

Integration challenges (30%) match Bruegel’s finding that 71% of European firms face adoption barriers (Bruegel, 2021).

4. Where External Experts Can Help

AI agencies like keinsaas can address these challenges:

• Curious but Cautious: Provide workshops and use case scoping to build confidence.
• Experimenting with Tools: Support tool selection and pilot integration.
• Looking to Automate: Develop automation solutions and data strategies.
• Scaling & Optimizing: Offer governance frameworks and analytics expertise.
• Advanced & Agent-Driven: Collaborate on innovative AI solutions.

Comparison to Sources:

This aligns with McKinsey’s emphasis on external expertise for immature firms (McKinsey, 2025) and Forbes’ solutions for overcoming adoption barriers (Marr, 2024).

5. Ideal Demand Profiles

Based on our survey insights and common business needs, these demand profiles are ideal for external AI support:

• Sales Lead: You don't have enough resources to manage the necessary volume of lead research and outreach, while maintaining personalization and quality in your SDR team. AI can help automate research, qualify leads, and personalize initial outreach at scale.
• Marketing Lead: You struggle with producing a high volume of quality content consistently across various social media platforms and optimizing it for SEO. AI tools can help you scale content creation, maintain brand voice, and improve SEO performance efficiently.
• Head of Operations: You want to solve the "brain drain" when employees leave and ensure valuable knowledge stays within the company by building an effective internal knowledge base. AI-powered knowledge management systems can help capture, organize, and make company expertise easily accessible.
• HR Director (Corporation): You face high recruitment costs and want to leverage AI for talent acquisition, including more efficient screening, candidate matching, and a better candidate experience.

Comparison to Sources:

These profiles reflect Bitkom’s focus on manufacturing and services (Bitkom, 2024) and the Swiss AI Report’s emphasis on SMEs and large firms (Mindfire & W.I.R.E., 2022), adapted to specific departmental needs we frequently encounter.

Conclusion

The OMR 2025 survey of 104 DACH professionals highlights a region with growing AI interest but varied maturity.

Most businesses are cautious or experimenting, with use cases in customer service and marketing.

Barriers like expertise gaps and compliance concerns persist, offering opportunities for agencies like keinsaas to provide tailored support.

Compared to broader studies, our findings show higher early adoption, likely due to OMR’s tech-forward audience, but align on barriers and use cases.

Sources

AIMultiple. (2025). 100 AI Use Cases with Real Life Examples in 2025. https://research.aimultiple.com/ai-usecases/ ↗

Bitkom e. V. (2024). Künstliche Intelligenz in Deutschland: Perspektiven aus Bevölkerung & Unternehmen. https://www.bitkom.org/Bitkom/Publikationen/KI-in-Deutschland-Perspektiven ↗

Bruegel. (2021). What is holding back artificial intelligence adoption in Europe? https://www.bruegel.org/policy-brief/what-holding-back-artificial-intelligence-adoption-europe ↗

Marr, B. (2024). 11 Barriers To Effective AI Adoption And How To Overcome Them. Forbes. https://www.forbes.com/sites/bernardmarr/2024/05/10/11-barriers-to-effective-ai-adoption-and-how-to-overcome-them/ ↗

McKinsey. (2025). The state of AI: How organizations are rewiring to capture value. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai ↗

Mindfire & W.I.R.E. (2022). Swiss AI Report 2022. https://cdn.prod.website-files.com/5e71f505e224b656715c1753/629f91e3ac23483a71029685_Swiss_AI_Report_19052022.pdf ↗

Visual Capitalist. (2025). Ranked: All the Things People Use AI for in 2025. https://www.visualcapitalist.com/ranked-all-the-things-people-use-ai-for-in-2025/ ↗