Small and medium-sized businesses (SMBs) have faced a challenging battle against large corporations for decades. These giants have the advantage of scale. They can afford larger marketing budgets, more specialized staff, faster logistics, but also deeper research capabilities. SMBs have always been looking for ways to be competitive in the market, and to cope with all those huge resources that larger corporations have. Recently, artificial intelligence (AI) has emerged as one of the promising opportunities for small ones to stand shoulder to shoulder with the big ones.
The OECD 2024 Policy Brief on AI highlights the urgency for small businesses to adopt AI in order to be competitive. In 2023, only 8% of firms across OECD countries had adopted AI, compared to 28% in the ICT sector. Among the top 10% most productive firms, AI usage was nearly twice as high as in the bottom 10%, a gap that reinforces competitive disparities.
Large firms remain dominant in AI adoption, with usage rates almost double that of firms with fewer than 250 employees. Without action, this imbalance could deepen. The OECD warns that concentrated AI adoption among leading firms could limit inclusive economic growth and widen productivity gaps. For example, between 2003 and 2020, productivity in global frontier manufacturing firms grew by over 50%, while growth for non-frontier firms was under 10%. Similarly, the U.S. Small Business Administration (SBA) reports that while SMBs account for 99.9% of all U.S. businesses, they face structural disadvantages in adopting new technologies due to limited funding and talent access.
But the game is changing. AI is no longer reserved only for tech giants with dedicated research and development teams and multimillion-dollar budgets. Now, it is within reach for small players, too. The democratization of AI tools through platforms like ChatGPT, Google Cloud AutoML, and Microsoft Copilot means that even a 5-person startup can now automate tasks, analyze customer data, and personalize user experiences. In fact, Gartner predicts that by 2026, more than 80% of enterprises will use generative AI APIs or applications in production. This is a huge jump from less than 5% in 2023. Small businesses that start now can gain speed, save time, and improve what they offer. In a market changing this fast, waiting too long may mean falling behind.
The core idea is simple: AI helps SMBs compete not by becoming bigger, but by becoming smarter. Instead of hiring an expensive data science team, SMBs can use AI dashboards that surface trends and insights automatically. Instead of running costly marketing campaigns, they can target the right users with precision through AI ad platforms and personalization engines. Instead of adding more customer support agents, they can deploy AI chatbots that provide 24/7 service, improving satisfaction without increasing headcount.
AI and automation tools are now affordable and easy to use. In the United States, AI adoption among small businesses has surged. According to the U.S. Census Bureau, firms with 1-4 employees increased their AI use from 4.6% to 5.8% between early fall 2023 and early 2024. While this growth rate is moderate compared to larger firms, it indicates a steady adoption of AI among the smallest businesses.
The benefits of AI for small businesses are tangible. A study by the University of St Andrews, based on interviews with nearly 10,000 UK SMEs, found that AI adoption could lead to productivity gains ranging from 27% to 133%. In continuation of this section you can see examples of some of the opportunities that AI can provide in your work if you are an SME.
Automation is changing how small businesses operate. Tasks like invoicing, payroll, and inventory management can now be automated. According to DOKKA, 61% of small businesses have already implemented AI to automate daily tasks, freeing up time for growth and strategy. This allows small teams to focus on more important work. Even businesses with just a few employees can now compete with larger firms.
Marketing has become more efficient with AI. A study by Unbounce found that more than 30% of small and medium businesses use AI tools for marketing. These tools help create content, target ads, and analyze customer behavior. As a result, small businesses can reach the right audience without spending a lot. In fact, 95% of small businesses using AI tools report a reduced need to hire additional marketing staff. This means more savings and better results. For instance, Farfetch, a luxury fashion retailer, used Phrasee’s AI email marketing to increase open rates by 7% and click-through rates by 25%, showing how AI can improve engagement without significant expenditure.
Small businesses are seeing results with intelligent marketing, too. For example, a flower delivery start-up, the Bouqs Company, has reported improvements in marketing performance through AI and personalization. They achieved a 22% lift in conversion rates and a 34% increase in revenue per customer by targeting specific customer segments with personalized campaigns.
The U.S. Small Business Administration notes that AI can help small businesses analyze their data to make better strategic decisions. This leads to smarter choices and improved performance. Even without a dedicated data team, small businesses can now make informed decisions that drive growth. For example, John Deere employs AI to process data from satellite imagery, weather forecasts, and soil sensors, providing farmers with real-time recommendations to optimize agricultural practices. This kind of AI support can be a game-changer for small-time farmers who don’t have the resources of large agricultural operations. With John Deere’s AI tools, farmers can get easy-to-understand advice on when to plant, how much water or fertilizer to use, and the best times to harvest, all based on real data from their own fields.
Instead of relying on investors’ resources or outdated methods, they can now make decisions that save money, increase crop yields, and reduce waste.
Personalization is no longer a luxury; it’s a customer expectation. A 2024 SAP Emarsys study found that 64% of U.S. shoppers reported improved retail experiences due to AI personalization, marking a 25% increase from the previous year. Furthermore, McKinsey reports that 71% of consumers expect companies to deliver personalized interactions. When these expectations aren’t met, 67% say they feel frustrated. Personalization has become a powerful engine for growth. The report shows that fast-growing companies generate 40% more revenue from personalization than their slower-moving peers.”
Small businesses are starting to deploy AI to meet these expectations, too. For instance, Benefit Cosmetics used AI to personalize email marketing campaigns, resulting in a 50% increase in click-through rates and a 40% boost in revenue. Another example is that the retail group TFG incorporated an AI chatbot into its online platform during the Black Friday period. This agent engaged with shoppers, leading to a 35.2% increase in online conversion rates, a 39.8% rise in revenue per visit, and a 28.1% reduction in exit rates. These cases show how AI can improve customer engagement and drive sales without significant human intervention.
In practice, small businesses can start with tools like Klaviyo, Intercom, or Drift. These help send customized messages or guide users based on behavior. They are easy to set up and work well with small teams.
AI accelerates product development by analyzing datasets to identify trends and customer needs. For example, StackBlitz, a startup focused on web-based development tools, used AI to create Bolt, an AI coding platform enabling non-technical users to build applications using simple prompts. Launched in October 2024, Bolt reached $20 million in annual recurring revenue within just two months and scaled to $40 million by March 2025. This rapid growth shows how AI can drive innovation and business success.
Another case is ThriveAI, a startup founded in 2024 by former tech leads from Google and Palantir. They developed AI agents that function as junior product managers, integrating with tools like Slack and Microsoft Teams to assist with tasks such as synthesizing feedback and monitoring competitor activity. This innovation helps reduce the administrative burden on human product managers, allowing them to focus on high-value tasks.
A small food business, Church Brothers Farms, used AI to improve its supply chain. By working with ThroughPut.ai, they optimized inventory and reduced waste. This led to a 40% improvement in short-term forecasting accuracy.
While AI offers benefits, small businesses must avoid common mistakes to ensure successful adoption.
AI is changing the way small businesses compete. Big budgets and large teams are no longer the only path to success. With the right tools and strategy, SMBs can act quickly, serve customers better, and make smarter decisions. They can automate daily tasks, improve marketing, create better products, but also personalize every customer interaction.
The key is not size, but it’s focus. Using AI does not mean doing everything. It means choosing the right tools for your goals. Start small, learn fast, and build on what works. AI can help you save time, reduce costs, and unlock new ideas without hiring large teams.
Remember, success today is not about having more. It’s about using what you already have in smarter ways. With AI, small businesses can lead with speed, creativity, and care. The future belongs to those who think differently but also act wisely.
Start small. Look at your daily work. Pick one repetitive task you do every week. Try using an AI tool to handle it. See what changes. You might save time or find new ideas. The best way to learn AI is to try it. One step at a time.
I hold a PhD in Computer Science and Electrical Engineering and currently serve as an associate professor at the Faculty of Electronic Engineering. My academic background and professional experience have provided me with expertise in Data Science and Intelligent Control, which I actively share with students through teaching and mentorship. As the Chief of the Laboratory for Intelligent Control, I lead research in modern industrial process automation and autonomous driving systems.
My primary research interests focus on the application of artificial intelligence in real-world environments, particularly the integration of AI with industrial processes and the use of reinforcement learning for autonomous systems. I also have practical experience working with large language models (LLMs), applying them in various research, educational, and content generation tasks. Additionally, I maintain a growing interest in AI security and governance, especially as these areas become increasingly critical for the safe and ethical deployment of intelligent systems.