AI for Small & Medium Businesses: Potentials and Feasibility

Artificial Intelligence (AI) offers significant opportunities for small and medium-sized enterprises (SMEs). However, many SMEs face challenges, including limited resources, that slow AI adoption. This includes not only the plastics industry, but is a bottle neck across all fields.

Expert insights

Johannes Kreft, Head of Political Communication at the German state-owned bank KfW, emphasizes that public funding can ease these financial barriers. He advises SMEs to explore government-supported programs for digitalization and innovation projects. Programs like KfW’s Credit No. 380 and the German government’s Central Innovation Program for SMEs (ZIM) can support AI investments.

You can also read: AI for enhanced Materials Development and Manufacturing

In the “Markt und Mittelstand” portal, David Evans, VP of Product Management at GoTo, suggests SMEs align AI projects with existing IT systems. He recommends beginning with low-cost options, such as low-code chatbots, especially if internal teams lack AI expertise. These tools are easy to implement and provide immediate value.

Key Challenges in AI Implementation for SMEs

Germantech identifies multiple challenges SMEs face when adopting AI, including:

• Data Suitability and Security: High-quality, secure data is essential for AI.
• Lack of Technical Knowledge: Many SMEs lack internal expertise in AI.
• Incompatibility of Processes and Structures: AI may not easily fit existing workflows.
• Low Digitalization: Limited digital infrastructure hinders data availability for AI.

Kreft also notes that complex and tech-intensive sectors benefit most from AI. For example, manufacturing, predictive maintenance, and robotics often see the largest gains. Other sectors, like traditional trades, have been slower to adopt AI but can benefit from automation over time.

You can also read: AI and Injection Molding: Bridging the Gap through Research

Cost Factors and Checklist for AI Adoption

Understanding AI-related costs is essential for SMEs. Key cost factors include:

• Initial Investments in Hardware and Software: Specialized equipment can be costly.
• Ongoing Maintenance: Regular upkeep can bring recurring expenses.
• Licensing Fees: Many AI tools require licenses, which vary widely in price.
• Cloud-Based Services: Usage costs depend on storage, bandwidth, or service levels.
• Free Tools and Updates: SMEs should explore free or low-cost tools when possible.
• Standard Tools vs. Custom Solutions: Tailored solutions may be needed for certain applications.
• Internal vs. External Expertise: SMEs should assess if tasks need external AI experts.
• Use Cases and Benefits Across Industries

AI offers diverse applications across sectors. For example, generative AI enhances office tasks in service industries, while smart energy management benefits manufacturing. In one case, the Kübler GmbH in Ludwigshafen uses AI for heating system optimization in large factories. Through a digital twin model, AI helps Kübler increase energy efficiency and extend equipment lifespan.

Johannes Kreft highlights that engineering and technical fields gain the most from AI through cost reduction and automation. However, he adds that some businesses choose not to adopt AI if employees resist change or if costs outweigh benefits.

Is AI Worth the Investment?

For SMEs, the answer is increasingly yes. AI offers strong potential in engineering and technical fields, where automation reduces costs and increases efficiency. Although SMEs face adoption challenges, public funding and structured planning make AI more accessible. By strategically leveraging AI, SMEs can drive growth and remain competitive.

To read more: Leveraging AI for small and medium-sized enterprises (SMEs): Exploring real-world