Myth #1: Artificial Intelligence Is Too Expensive to Be Accessible for SMEs

This week, we’re addressing one of the most persistent myths: the idea that AI is too expensive and inaccessible for small and medium-sized enterprises (SMEs).

I understand why this perception is widespread. A quick search on AI use cases in manufacturing often highlights large-scale corporate projects, massive investments, and teams of data scientists.

If I were an SME executive, I would probably conclude that these technologies are out of reach. And that’s a reaction I hear often.

But the reality is quite different: today, AI is more accessible than ever. Many tools allow SMEs to:

• Automate tasks
• Optimize processes
• Improve productivity at a lower cost

Far from the highly publicized and ambitious projects, it is often modest but well-targeted initiatives that deliver the best return on investment.

Even better, some projects do not require advanced technical skills and can be led by your own teams.

Understanding AI: The Fundamentals

AI can be defined as a set of theories and techniques aimed at creating machines capable of simulating human intelligence.

There are several types of AI:

Robotic Process Automation (RPA): These “software robots” automate repetitive tasks such as data entry, invoice processing, or updating customer databases.

Machine Learning: These systems analyze data to detect patterns and predict outcomes (e.g., sales forecasting, inventory optimization).

Generative AI: Capable of creating content (text, images, audio), it offers opportunities in document production, communications, and marketing content creation.

Process Optimization: An Excellent Starting Point

While chatbots and virtual assistants capture attention, the most immediate gains for SMEs are often found in automating and optimizing internal processes.

These initiatives increase efficiency, reduce errors, and free up time for higher-value tasks.

How to Identify the Best Automation Opportunities in Your Business

There are several ways to identify automation opportunities: mapping processes or conducting an analysis based on your performance indicators.

One of the simplest and most effective approaches is conducting a time study:

• Ask employees to track the time spent on their daily tasks over two weeks.
• Analyze the results to identify time-consuming and repetitive activities.
• Distinguish essential tasks from those that could be automated or eliminated.

Why is it important to take the time to conduct this study?

Because there is often a gap between our perception of how long a task takes and reality.

These insights may even allow you to eliminate certain tasks altogether (automating with AI is great, but automating an unnecessary task does not add real value—the classic “garbage in, garbage out”).

When we conducted this exercise at Amazon, we were surprised by how much time supervisors spent filling out manual reports (yes, that exists at Amazon too). After validating the importance of these reports with their recipients, we realized they were not even being reviewed.

The best solution was not to automate the report, but to eliminate it entirely. By taking the time to analyze the time study results, we were able to make the best decision for the business.

What Are the Next Steps?

Once the opportunity is identified, here is how to structure your project:

Define expected benefits: Time savings, cost reduction, quality improvement, etc. This step will help you gather the information needed to build a solid business case.

Evaluate existing tools: Does your company already use solutions that integrate AI? Can your current system create automations? Avoid the temptation to add new software for every opportunity; first maximize the tools you already have in place.

Choose the right technology: There are no-code automation tools (Make, Zapier), automation platforms (UiPath, Power Automate, Automation Anywhere), as well as custom solutions. The right choice depends on the complexity of your use case.

Launch a pilot project: Start small, measure results, and adjust before scaling. Many automation platforms offer trial periods—take advantage of them.

Ensure adoption: Train your teams, communicate the benefits, and support the change. The best tool in the world is useless if it is not properly used.

Conclusion

Automation may not have the “wow” effect of a chatbot speaking to your customers, but what truly matters is improving profitability and efficiency. Even when it comes to AI, the focus should remain on return on investment.

Have you already tested automation solutions in your business? What were your results? Share your experience in the comments.

P.S. The newsletter format does not allow for optimal sharing of certain tools or graphics. Feel free to send me a private message if you would like more information on the topic.

Note: This article was conceived and written by a human, then reviewed by AI.