The widespread availability of new tools and applications of artificial intelligence (AI) creates numerous opportunities for small and medium-sized enterprises. AI, in the form of chatbots, automatic image recognition, and process automation, has long been a part of everyday business. At the same time, many companies shy away from the seemingly high initial investment. However, with the right approach, a pragmatic, step-by-step introduction is possible – even with a manageable budget.

Step 1: Clear up the most common misunderstandings

New technologies are often associated with stereotypes that make open engagement difficult – and AI is no different. The assumption persists that AI only works with vast amounts of data. However, there are long-standing, proven applications with smaller, structured data sets, such as text recognition or product data classification. For example, a regional furniture manufacturer can use AI to automatically evaluate complaint reports to identify patterns and improve quality.

Another misconception: AI will replace many jobs. While routine tasks can be automated, value-added tasks usually remain with humans—or are created through the interplay of technology and human expertise. Openly address reservations and dispel them early on. This will build acceptance within the team.

Step 2: Clarify requirements

The use of AI is challenging – and not just technically. In addition to IT issues like data access or cloud infrastructure, the key question is what goals you want to achieve with AI. Ask yourself: Where do you want to reduce costs, improve quality, or save time? A good AI strategy doesn't start with tools, but with a business potential analysis. Simple checklists help you understand the current status and plan the next step.

Step 3: Create the conditions

Few SMEs can put an AI application into operation overnight. The marketing promises of many providers often sound ambitious – but the decisive factor is whether the benefits are a good fit for your company. Identify specific processes where AI is worthwhile. Examples include recurring customer service inquiries, supply chain bottlenecks, or time-consuming manual data entry.

Once the benefits are established, focus on closing gaps: Build knowledge about data management and data infrastructure – internally or with partners. This will lay the foundation for successful implementation.

Step 4: Build a pilot

From the possible use cases, select the one that promises the greatest benefit at a reasonable cost. The goal is a pilot application with which you can test the economic added value. Use software-as-a-service solutions for this purpose – this way, the financial risk remains manageable. The pilot should cover a clearly defined sub-process, for example, a section of your supply chain or a recurring customer service process.

Step 5: Expand AI usage

If initial tests deliver positive results, further develop the solution. Check: Has the application achieved what you expected? In addition to key performance indicators, feedback from day-to-day use is also important. Are efficiency, quality, and costs consistent?

If the outcome is positive, gradually expand the solution to other departments or processes. Coordinate each step closely with the relevant departments. Embed the acquired knowledge permanently within the company: Train "observers" who want to understand what is possible with AI, "users" who actively use AI, and "developers" who adapt solutions or implement new ideas. This creates a learning organization in which AI is a natural part.

Conclusion: Getting started with AI is feasible – even for SMEs

SMEs don't need expensive, high-end solutions to benefit from AI. What's crucial is a clear, practical approach that addresses their own challenges—not hype. Those who start where time is lost or processes are stalled can achieve real improvements with manageable effort. Support offers from chambers of commerce, funding programs like the AI Transfer Hub in Germany, and collaborations with universities and startups can help with this. Don't wait for the perfect moment—start your AI journey step by step.

You can find more basic information, exciting facts, and helpful methods on the topics of digital transformation and data in “ Data Business – The $851 Billion Business .”