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Until recently, Artificial Intelligence (AI) was seen as something reserved for science fiction films or tech giants. Today, however, the scenario has changed radically: what once seemed distant is now within reach of Small and Medium-sized Enterprises (SMEs), becoming one of the most democratic and accessible tools for innovation.
Recent studies focused specifically on the SME ecosystem reinforce this idea. They show that AI should not be seen as an end in itself, but as a powerful tool capable of enhancing human creativity, accelerating internal processes, and revealing opportunities hidden in the data that the company itself already possesses. Innovation, therefore, lies not only in the technology itself, but in how each organization orchestrates its use.
Two recent articles, listed at the end of this text, illustrate these points. The 2024 text shows how the adoption of AI and other emerging technologies is directly linked to the entrepreneurial orientation of companies, highlighting that SMEs with cultures more open to experimentation and risk-taking achieve significantly better results. The second article (from 2021) presents a robust framework for building AI capabilities within organizations, demonstrating that the most valuable impact occurs when technology is applied to generate concrete results such as creativity, efficiency, and performance.
Based on these findings, this article focuses on presenting five practical recommendations so that your company can transform AI into a lever for innovation, regardless of its size or the sector in which it operates.
- Redefine what it means to innovate: from big leaps to continuous improvements
For many SMEs, the word innovation still conjures up images of grandiose projects, high investments, and risks that are difficult to absorb. AI allows us to debunk this myth. The most transformative innovation, especially in smaller companies, can be incremental, continuous, and applied to everyday life, as recommended by the Japanese philosophy of kaizen.
As a practical recommendation, instead of looking for a revolutionary “silver bullet,” start by identifying specific operational pain points. For example, ask: “Where do we waste the most time?”, “What repetitive processes wear down the team?”, “What flaws irritate the customer the most?”
Two simple examples. A small e-commerce business can implement an AI chatbot to answer 80% of the most frequently asked questions about delivery times or exchanges. This improvement frees up customer service staff time to deal with more complex issues or to focus on sales prospecting. Or, a neighborhood restaurant can use AI to automatically adjust its digital menu according to the best-selling items at certain times, avoiding waste and increasing profit margins.
The big lesson here is: innovation does not have to be disruptive to be impactful.
2. Discover innovation in the data you already have
There is a belief that only large corporations with vast amounts of data can benefit from AI. This is a misconception. Small data, when well organized and analyzed, hides valuable insights.
To do this, first check and analyze your internal data. Map the information that your company already generates naturally—sales history, WhatsApp interactions, production times, registered complaints, feedback on social media. This set of data is an underutilized gold mine. With that, focus on simple and useful applications, such as accessible predictive analytics tools, many of which are available on subscription platforms and already enable applications such as:
- Predict seasonal demand spikes and avoid stock shortages.
- Identify customers with a higher risk of default.
- Recommend products based on past purchases, even for small customer bases.
Imagine, for example, a small clothing store that discovers from its data that certain customers always buy new items during seasonal sales. This pattern can be used to create hyper-focused campaigns, maximizing conversion at low cost.
3. Become an innovation facilitator, not an AI expert
A common mistake is to think that only highly technical professionals can lead the adoption of AI. In reality, the role of the SME manager is not to master all the algorithms, but rather to act as a facilitator: creating conditions for the entire team to explore the potential of these tools.
Today, there are several tools available to everyone. So, make generative AI solutions (such as ChatGPT, Midjourney/DALL-E, predictive analytics tools, among others) available to marketing, operations, and customer service teams. And promote regular meetings where teams collectively use AI to brainstorm campaigns, optimize product descriptions, or solve logistical bottlenecks.
Here, the gain is not only technological, but cultural: by democratizing access, you create a more creative, collaborative, and engaged organization.
4. Use AI to personalize the customer experience
One of the most powerful opportunities for SMEs may lie in the customer experience. AI allows you to offer a level of personalization and proximity that was previously restricted to large corporations with abundant resources.
With AI, you can achieve smarter market segmentation, going beyond traditional segmentation (age, income, location). You can use AI to identify behavior patterns, hidden preferences, and consumption habits.
Another powerful use of AI is to achieve proactive and personalized communication. This can help implement systems that remind customers to restock a product they usually buy, or offer a personalized discount on their birthday. A healthcare clinic, for example, can use AI to send personalized automatic reminders for periodic checkups, accompanied by educational content tailored to each patient’s history. The result is more engagement, more loyalty, and less attrition.
5. Adopt a mindset of testing and rapid learning
The biggest advantage of modern AI tools is the low cost of experimentation. Unlike other innovation investments, it is possible to test hypotheses quickly and cheaply. This way, you can treat each project as a short-term pilot.
To do this, you must define a simple goal (e.g., reduce customer response time by 30%), set a short deadline (e.g., 3 months), and track a clear metric of success. If it works, scale it up. If it doesn’t work, discard it or pivot, remembering that even “failure” generates useful learning. This fail fast, learn faster mindset should become part of your company’s culture.
Conclusion: the human factor as a differentiator
The most important point is to understand that AI does not replace innovative managers or their teams. On the contrary, technology amplifies human potential, freeing up time and energy for people to focus on what they do best: creating, imagining, connecting with customers, and building visions for the future.
The role of leadership is to allow AI to take on repetitive, analytical, and operational tasks, while humans focus on what no machine can replicate: intuition, empathy, strategic vision, and creativity.
Therefore, dear managers, the final recommendation is simple. Start small and start now: the window of opportunity is open, and the barrier to entry has never been lower. Use AI as a tool, not as an end: it is how you apply it that will determine whether it will be just a passing fad or a true driver of innovation for the future of your company.
Prof. Dr. Marco Antonio Silveira
Universidade de Marília – Master’s Degree in Administration
marcoarlp2016@gmail.com
Further reading:
Kumar, V., Ramachandran, D., & Kumar, B. (2024). The interplay of emerging technologies and entrepreneurial orientation in driving innovation and performance in SMEs. Technovation, 133, 103008.
Mikaief, P., et al. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434.
