AI Implementation

The model works in the lab. In production, it falls apart. AI implementation bridges that gap: data preparation, training, system integration, testing, scaling. Everything has to work together for a model to deliver results in day-to-day business.

The numbers are sobering

Over 80% of AI projects fail (RAND Corporation), twice the rate of traditional IT projects. 42% of companies abandoned their AI initiatives in 2025, up from 17% the year before. Why?

• Knowledge gaps in the team (72%)
• Technical integration challenges (70%)
• Poor data quality (43%)

The most common mistake: starting with the model instead of the data. Allocating 50-70% of budget and timeline to data readiness doubles your success rate.

Timelines and costs

Chatbot deployment: 2-4 weeks, starting at EUR 10,000. Workflow automation: 6-12 weeks, EUR 20,000-150,000. Custom AI model with SAP or ERP integration: 3-6 months, EUR 100,000-500,000.

What makes the difference

Companies that buy from specialized vendors achieve a 67% success rate, compared to 22% for in-house development. Redesigning workflows before choosing a model doubles the probability of significant returns.

Start small. Execute one use case properly. Then scale. AI strategy and implementation belong together, but the implementation must deliver tangible results quickly.