Artificial intelligence is moving from promise to practice in record time, and business leaders are racing to take advantage of it. According to a report by McKinsey, 92% of companies plan to increase their investment in AI over the next three years. At the same time, early adopters are already seeing meaningful improvements. According to Goldman Sachs, 80% of small and medium-sized businesses currently using AI report increased efficiency, and nearly half say AI improves data-driven decision-making.
However, AI is not a silver bullet. Delivering value requires careful scoping and thoughtful implementation. AI cannot replace the creativity, judgment, and intuition that small businesses rely on. Instead, we’re expanding what small teams can accomplish. According to a 2025 Shopify study, 69% of business owners using AI tools use them to generate content. Other common use cases include assisting with data analysis and insights (32%), improving customer service quality (29%), and assisting with product development (23%).
More companies are realizing that the value of AI is truly realized when it augments human creativity and capabilities, rather than completely replacing them. These are the ways smart companies are leveraging AI with the most success.
Democratizing data science for smarter campaigns
What once required focus groups, surveys, and weeks of analysis can now be done in minutes with AI. Small and medium-sized businesses are increasingly using AI for market research tasks such as analyzing customer reviews, social conversations, and search behavior to uncover emerging needs before competitors can respond.
Jones Road Beauty uses tools like OpenAI’s Deep Research to analyze thousands of product reviews, Reddit threads, and YouTube comments. From that analysis, the clean beauty brand’s team identified five real-world personas, including busy parents and frequent travelers. These insights informed Just Enough’s tinted moisturizer campaign, helping the team refine the message, choose the right models, and shape the overall creative direction.
AI-powered analytics not only speeds up data analysis, but also makes data analysis available to everyone in your company. Wallet and accessories brand Ridge uses AI to eliminate internal bottlenecks that slow data-driven decision-making. “We have a data warehouse and all Shopify reports,” says Ridge CEO Sean Frank. “Instead of doing something manually, you can take a screenshot and drop it into ChatGPT, and the analysis will run. Your whole team can work like data scientists.” Everyone on the team can get their insights instantly, instead of waiting hours or days for specialists to crunch numbers.
These examples illustrate broader changes. AI is giving small teams the analytical power of large organizations. By lowering the barrier to data analysis, brands can move faster, experiment more often, and build campaigns that are rooted in what customers are actually thinking and behaving.
Building personalized products
For small businesses with limited engineering resources, launching new products can be costly and time-consuming. AI is changing that calculus. AI accelerates research, content generation, and user testing cycles, enabling teams to bring new digital products to market at unprecedented speed. In many cases, it not only accelerates development, but also enables entirely new categories of personalized and adaptable products.
Loftie, a wellness company that designs sleep products, uses AI to develop and release the Loftie Rest app, a digital companion to its signature alarm clock. The app has expanded Loftie’s reach, opened up new revenue streams, and built a subscription business from the ground up, which currently has about 15,000 members. “We couldn’t have released this product without AI,” says Founder and CEO Matthew Hassett. “This was the first seed of what would become our subscription app.”
Personalized content is the backbone of Rest apps, including Storymaker, which uses a simple survey and adjustable audio profiles powered by OpenAI and Eleven Labs to generate customized bedtime stories. Further extending personalization, Loftie’s Night School feature analyzes correlations between users’ Apple Health data, screen time habits, alarm settings, and self-reported sleep quality. When a pattern emerges, such as late-night scrolling leading to sleep deprivation, the tool recommends changing habits or prompts users to block distracting apps. “We use AI to look for patterns and make proactive suggestions to help you put your phone down at night,” Matthew says.
Lofty combines AI insights with human-generated content every step of the way, from educational modules to meditation flows. AI determines what users need, and humans help create what is provided. The result is a digital product that continually adapts while maintaining a distinctly human tone. This would have been prohibitively complex to build without AI.
Scaling ad creation and testing
Amplifying your creative output is becoming an important part of a strong paid advertising strategy. Brands will need more and more advertising variations to be successful. This is often more than a creative team can realistically produce on their own.
Ridge is leveraging AI to bridge that gap. The company created a custom GPT trained on its best-performing ads and connected it to automation tools to generate hundreds of new static assets every day. “We built a static advertising factory,” Sean says. “You can see 500 ads a day without even touching a keyboard.”
These assets are sent to a shared drive for review, but most are not rotated. that’s ok. The key is volume. “Out of 500, 450 are terrible,” Sean says. “But the top 10% are between 5 out of 10 and 7 out of 10. They’re going to fund them.” The brand next plans to extend this process to video as well, generating more hooks and variations for testing.
AI won’t replace Ridge’s creative team. The company’s best-performing ads still come from its Human Design team, which consistently produces 10 out of 10 winners. AI allows for more concepts, more iterations, and more opportunities for platforms like Facebook to match the right ads to the right people at the right time.
“The future of advertising is all about shots on goal,” explains Sean. “What you see and like is going to be completely different than what I see and like.” Combining human-created assets with massive amounts of AI-generated variation allows Ridge to scale experimentation far beyond what would be possible manually, turning paid strategies into continuous data-driven testing and improvement loops.
Improving customer service
Early AI tools, such as chatbots and interactive voice responses (IVR), were a natural fit for repetitive use cases, such as “Where’s my order?” and “What are your business hours?” This makes customer service one of the most mature applications of AI in small and medium-sized businesses. However, the risks of balancing human and machine intervention remain high. A 2024 study from Acquire Intelligence found that just one bad experience with AI-assisted support could cause 70% of consumers to consider moving to another business.
At Loftie, AI agents now answer over half of the support emails we receive. “It’s difficult to standardize responses across human agents. AI is much more reliable,” Matthew says. “The same question has been answered 1,000 times by now.” The team also uses AI to uncover trends from what Matthew calls the “data graveyard” and turn thousands of customer interactions into insights that help improve products and experiences. “I was honestly surprised by the reluctance of brands to implement AI in customer service,” he says.
Ridge had similar benefits. “Customer service is a very simple use case,” Sean explains. “About 60% of tickets are answered by AI.” The company has also seen a 10% to 20% improvement in customer satisfaction scores compared to human-only workflows. “Customers love talking to AI,” he added. “Faster, faster, more accurate.”
These improvements are driven by a shift from rules-based chatbots to agent AI. Agent AI is a tool that can understand intent, see past interactions, access customer data, and perform simple actions like processing refunds or exchanging products. Once limited to large enterprises, agent AI is now available through tools like Zendesk and HubSpot.
Implementing AI thoughtfully and understanding when to escalate emotional or complex issues to a human agent will give your team more scope without sacrificing quality. Routine questions are resolved quickly and consistently, freeing up human agents to spend more time on the conversations that matter most.
As AI continues to evolve, opportunities for small businesses will come from this kind of selective adoption, using AI to enhance human capabilities and keep people at the center of the work that defines their brand.
