TFF #4: How SMEs can achieve real ROI with AI - and avoid the biggest pitfall

AI can be a real game changer for SMEs - but only if the right priorities are set. The biggest danger is usually not the price, but that you invest time and money in AI projects that don't bring any real benefit.

Many SME bosses are currently asking me the same question: "We hear so much about AI - but what does it really do for us?"

The uncertainty is great. Some rely on AI tools in the hope of quick success. But it often ends differently:

  • Projects are not progressing.
  • Costs rise unexpectedly.
  • The new systems are hardly used in everyday life.

The result? Frustration. Waste of time. No return on investment (ROI).

We experienced it recently:

  • A service provider introduced automated quotation generation - but employees continued to work as before because they didn't understand the opportunities.
  • A production company relied on AI-supported maintenance - but the quality of the machine data was insufficient. The result was a standstill.
  • A retailer hoped to reduce customer inquiries with chatbots - but customers weren't satisfied because the bot didn't know the important questions.

The technology wasn't the problem - the wrong priorities were. These companies have followed the hype instead of focusing on the real benefits.

This ensures that your AI investments pay off:

Step 1: Impact instead of hype

Rate each AI project according to two clear criteria:

  1. Business Impact: Does it increase sales, reduce costs or increase efficiency?
  2. Implementation effort: How much time does the project take? What are the costs? What skills do we need?

Organize all ideas into an AI ROI matrix:

▶ High potential, low effort → IMMEDIATELY implement (Quick Wins)

▶ High potential, high effort → PLANNING (Strategic projects)

▶ Low potential, low effort → TEST (Small optimizations)

▶ Low potential, high effort → STRIKE (time and money waster)

Step 2: Calculate ROI

The return on investment (ROI) of AI is not only calculated by Cost reduction. You can also measure success in other ways:

Time saving → Efficiency ROI: (hours saved × labor costs per hour) ÷ investment

More sales → growth ROI: (sales profit - investment) ÷ investment

Risk minimization → avoidance ROI: (Avoidable error costs or downtime) ÷ Investment

Example: An SME automates invoicing with AI:

▶ Saves 10 hours per week at CHF 50 per hour = CHF 500 per week

▶ Annual savings: CHF 26,000

▶ Costs of the AI solution: CHF 5,000 per year

ROI: (26,000 - 5,000) ÷ 5,000 = 420 %

Step 3: Where AI brings the greatest benefits for SMEs

These fields of application have proven their worth with SMEs:

Productivity: AI assistants automate routine tasks (30-50 % efficiency gain).

Distribution: AI-supported analyses increase the closing rate (20-40 % sales increase).

Customer service: Chatbots drastically reduce response times (up to 70 % cost savings).

Marketing: AI personalizes campaigns, campaign success increases (up to 3x higher engagement rate).

Maintenance: Predictive maintenance prevents breakdowns (up to 40 % less downtime).

Use these figures as a guide for estimating your AI potential.

Step 4: Start small - but don't wait

▶ List all AI ideas for your company.

Prioritize the quick wins with the AI ROI matrix.

▶ Start your first project with low effort and high benefit.

▶ Measure the ROI after 3 months - adjust and scale further.

The goal is not perfection - it is momentum.

SMEs that start now are building the AI fitness that will set them apart in the future.

👉 Download the KI-ROI matrix (available in English).

Are you ready?

We are glad you asked! Schedule an appointment with us directly to begin this important first step of the innovation process - the needs analysis. We look forward to working with you to overcome the challenges and drive digital innovation in your business.

Our blog

Latest post

TFF #40: AI strategy: How to overcome inertia in SMEs

In many SMEs, we are currently observing a phenomenon that I call the "AI paradox". Our latest "Culture Compass" study sums it up: 78 % of companies rate AI expertise as crucial for their future, but only 23 % feel prepared for it. This gap is huge. And it is not caused by a lack of technology [...]

TFF #39: Why AI fails without the cloud (and what most people overlook)

This week at the AI Café, a statement was made that has stuck with many. Manuel Pfiffner from sl.one showed a statistic: 70% of employees use AI today. "A customer told me: nobody uses it at my company," Manuel said. His response to the customer was direct: "Don't believe that. Please don't believe that." And then [...]

TFF #38: The four-gap trap: Why 62% of AI projects remain piecemeal

Some typical scenes from everyday AI life: Scene 1: The hopeful start A financial services provider tests a custom GPT for customer communication. Works great. The team is enthusiastic. 3 months later: Only 2 people are using it. Scene 2: The resistance A production company wants to introduce AI for process optimization. The management pushes. The team puts the brakes on. Not out of unwillingness. Out of fear [...]