Table of Contents
1. The Starting Point
In many companies, AI initiatives are currently a hotly debated topic. While enthusiasm for new technologies is high, the question often remains of how the success of such projects should be measured. Especially in the B2B space, there's a risk that projects drift into uncertainty without clearly defined success parameters.
Does AI Really Fit Your Processes?
Avoid costly missteps and uncover hidden potential. Use our non-binding initial consultation for a clear expert assessment.
2. The Strategic Approach
To ensure the long-term success and profitability-oriented use of AI, it's crucial to define concrete goals from the start. The value of an AI project must be clearly linked to business objectives so you can measure relevant impact.
3. Critical KPIs for AI Projects
1. Average Handling Time (AHT) / Time Savings
Average handling time is a classic indicator in automation projects. It shows how efficiently processes are accelerated by AI technologies. For example, you can measure how much the processing time of support requests has been reduced.
2. Conversion Rate and Revenue Growth
Another valuable metric is the conversion rate. Here you measure the success rate of sales conversations or interactions before and after introducing AI. This provides a direct connection to revenue development.
3. Employee Satisfaction
Employee satisfaction can be a decisive KPI, since AI takes over many repetitive tasks and can shift focus to more demanding work. This is measurable through regular surveys and employee feedback, for instance.
4. Real-World Example: Mechanical Engineering
A mid-sized mechanical engineering company with 200 employees reduced its average maintenance effort by 30% through the use of AI-supported maintenance software. The conversion rate in customer projects rose by 15% because the AI used real-time data for project optimization. Additionally, 85% of employees reported increased satisfaction because automation relieved them of routine tasks.
5. The First 3 Steps to Project Success
- Goal setting: Define clear, business-oriented goals and link them to specific KPIs.
- Process analysis: Identify the processes that will benefit most from AI.
- Pilot testing: Test the AI in a small, controlled environment and adapt the broader rollout based on the results.
Does AI Really Fit Your Processes?
Avoid costly missteps and uncover hidden potential. Use our non-binding initial consultation for a clear expert assessment.
