Most AI pilots die before they go into production.
As of July 2026 · updated monthly
The Nextise Top Ten
From 250+ projects, we've learned: access to AI is rarely the problem. Implementation in day-to-day operations is. That's why we compile our recommendations for AI adoption in the German Mittelstand from projects, client conversations, and our own practice — updated monthly by the Nextise team.
Current landscape · As of July 2026Why the
Why the
Nextise Top Ten exists
Nextise is the AI partner for the German Mittelstand from Baden-Württemberg. We help mid-sized and industrial companies deploy AI in day-to-day operations. Since our founding, we have delivered more than 250 projects. From this experience, we share practice-based recommendations, updated monthly by the Nextise team.
Our most important insight from the field: Companies rarely fail because of the model. They fail because AI has no place in their processes, data, and responsibilities. Successful AI adoption does not need another tool. It needs a system that actually works inside the company.
Many Mittelstand companies adopt AI without control over data and governance.
Productivity gains often stay capped in office work and do not scale into core business.
Models alone are no longer a competitive edge. There are now many capable alternatives.
Category 1
Top 10 Problems in AI Deployment
What most often slows Mittelstand companies down when introducing AI.
Most AI pilots never reach production. Processes, data, and responsibilities are missing.
A large share of Mittelstand companies adopt AI without control over data, governance, or costs.
Productivity gains stay capped in day-to-day office work and do not roll out across the organization.
Models are no longer a differentiator. There are many comparable alternatives on the market.
Many solutions are siloed. They do not connect with existing systems such as SAP, SharePoint, or CRM.
Missing internal expertise leads to dependency on external vendors without knowledge transfer.
Privacy and sovereignty questions are addressed too late instead of from the start.
There is no clear prioritization. Too many use cases are started at once; none are finished in production.
Existing, well-established processes are not sufficiently considered when AI is introduced.
Budgets are available. Without a clear business case and plan, the investment fizzles out.
Updated monthly by the Nextise expert team
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