How to get started with industrial AI: a 7-step framework
- Digitalization
- AI
- 12.8.2026
- Reading Time: {{readingTime}} min
Contents
Turning years of AI experience into a proven framework
We recognized the growing importance of artificial intelligence in industry early on and established our AI Competence Center several years ago. Since then, we have been purposefully developing AI applications and continuously expanding our expertise. Through this center, we have trained colleagues across the organization, enabling AI solutions to be developed and implemented in multiple departments.
Our developments include an AI assistant that supports software developers in KeStudio, as well as the KEBA AI Module for industrial control systems, which provides a hardware platform for deploying AI applications in industrial environments.
Building on the experience gained from these and many other AI projects, our experts have developed a structured approach that helps machine manufacturers successfully adopt AI and remain competitive in an increasingly AI-driven industry.
Step 1: Develop the big picture
The first step is to define the initial situation. How is the market changing? What are the technology trends that will dominate the activities of machine manufacturers and automation specialists over the next two to five years?
Ask your customers about their plans and strategies for the coming five to ten years in order to gain a good overview:
- Are there changes to the business model?
- How will production change from their point of view?
- What (new) requirements does this entail for their machines and plants?
- What are their actual pain points, and which of these can (only) be addressed through AI?
- Which trends do they consider important?
Where in the big picture will the effects of artificial intelligence become relevant?
Step 2: Identify the influence of AI
The next step is to figure out where in the big picture the effects of artificial intelligence will become relevant. What role does AI play in these trends? What areas are relevant for AI?
For example:
- Machine operation: simplification through assistant systems
- Intelligent enhancements of machine control and functionality
- Cloud solutions for data analysis
Anyone still without in-house AI resources should use this step to acquire basic knowledge of AI, for example by attending industry events on the subject, by studying best-practice examples, or by obtaining support from more experienced partners.
Step 3: Define your own position
The next step is to consolidate this knowledge and apply it to your own situation. Use the big picture and the identified AI trends as a basis for finding answers to questions:
- How will the market changes affect your own business?
- What role can you (or do you want to) fill in the future?
- What are your own capabilities with regard to data availability?
- What data is already available, what data can be generated for applications, and what data is definitely out of reach?
Since AI is data-driven by definition, the availability of data determines your position. Data provides answers to questions such as how you can support customers through changing technologies and strategies, or how you can use more digitization and more AI to adapt your products and services better to your customers’ requirements.
Completing this step successfully requires uncompromising focus.
Step 4: Identify AI mis-steps and potentials
The next question is inevitable:
- Which AI aspects are relevant to you?
- In what areas can you (or do you want to) become active?
The answers depend, at least partially, on what in-house competencies are available. You should take into account that AI solutions need both hardware and software. Completing this step successfully requires uncompromising focus. AI technology in its totality offers an enormous wealth of options. But individual applications will be successful only if they solve specific problems.
Step 5: Develop your business case
Step 6: Create the right conditions
Step 7: Find a cooperation partner
Continue your AI journey with the full whitepaper, where you'll find a detailed explanation of steps 5-7, practical examples, and actionable recommendations for machine manufacturers.
Have questions? Connect with the author.
