AWS Smart Business Blog

Exploring Practical Use Cases for Generative AI in Small Businesses

The conversation around generative artificial intelligence has sparked both excitement and skepticism. The potential of AI is undeniable, with applications like chatbots improving customer service and machine learning algorithms detecting fraud or predicting equipment failures. But there’s often a gap between the hype and practical applications, leaving small or medium businesses (SMBs) wondering whether they can also join in on AI applications.

According to this US Statista survey, 44 percent of small business owners and marketing decision-makers stated that their biggest concern regarding using artificial intelligence and/or automation technology for marketing was their data security. Concerns about the price of implementation of the technology followed with 41 percent. This highlights the importance of efficient operations for SMBs, as they strive to balance productivity with budget constraints in order to remain competitive. With the right strategy, companies of your size can find affordable ways to use AI and make data-driven decisions that boost business.

How to get your SMB started in generative AI

You do not need an in-house data science team and high compute power to get started. Cost is often perceived as a barrier, however, the democratization of AI—along with the advent of many tools and services offering low-code to no-code solutions and pay-as-you-go models—has changed this landscape. In the cloud, you can benefit from AI capabilities without requiring deep technical skills.

That said, one prerequisite remains: having digitized data in the cloud. Before getting started, you should evaluate your existing data or abilities to gather such information. This data could include text files, spreadsheets, videos, images, and more. If not already in the cloud, it will need to be migrated, where it can be used for training and fine-tuning models.

Once you have completed an assessment of your data, the next step is to thoroughly evaluate potential use cases to meet business needs. With those defined, you can then explore available options. One option, if you have in-house IT staff, would be to make use of your data to train your own model or take an existing model and making small tweaks to it (what we call “fine tuning”). Another option would be to make use of an existing foundation model that can address the use case and leverage that in your applications.

If you’re like many SMBs without a dedicated IT staff member, we suggest working with skilled AWS Partner Network consultants who specialize in companies of your size. Many offer free consultations or assessments before you decide to commit.

Six use cases for SMBs

At Amazon Web Services, we understand the importance of getting ahead of these conversations to dispel the “hype cycle” mentality that AI is just another short-lived trend. Let’s explore some easy, entry-level ways you can use generative AI to solve real-world challenges for your SMB.

1. Content creation and optimization

Generative AI tools can assist small businesses in creating and optimizing content for websites, blogs, social media platforms, and education. From creating compelling product descriptions to crafting engaging courses, AI-driven content generation streamlines the process, enabling you to save time and effort.

AWS SMB customer,, transforms the way students from all over the world learn new content and review key concepts. The company has built a platform for students to upload their study material and receive a summarized version—as well as flash cards—in a matter of seconds. The company leverages several innovations brought by generative AI to achieve this ultra fast and reliable way of optimizing an approach to studies. Alec Conti, founder of, shared, “With Amazon Bedrock we have reduced information processing time by 40 percent compared to previous solutions. We have been able to generate more new content, while maintaining a high level of quality and reliability.”

You can also test our free, no-code generative AI tool, PartyRock (powered by Amazon Bedrock), to better understand how your business can improve its operations.

2. Customer engagement through personalized marketing campaigns

With AI-powered solutions, small businesses can deliver personalized marketing campaigns that resonate with their target audience. By analyzing customer data and behavior, generative AI can enable you to tailor email marketing content, social media ads, and website recommendations, which can enhance customer engagement and conversion rates. Check out a sample solution on how you can offer a personalized customer experience with machine learning.

3. Customer support chatbot integration

Enable your support staff to work on issues that truly require 1:1 involvement. Building custom chatbots using AWS services allows small businesses to provide efficient, 24/7 customer support. These AI-powered chatbots can handle routine inquiries, provide product recommendations, and even assist in completing purchases. This can improve customer satisfaction and reduce agent costs. Check out a sample solution on how to build a Q&A chatbot using AWS services.

4. Find answers and trends hidden in unstructured data

One exciting use case for generative AI is searching through unstructured data—such as videos, text files, email, and images—to produce accurate and relevant search results quickly. Unlike traditional keyword-based search, it can interpret the intent behind vague or abstract searches and return results that match the implied meaning. This allows users to search naturally using conversational language rather than having to come up with the exact keywords needed. By using the power of generative AI, search engines can deliver more accurate, complete, and human-friendly results when reviewing massive troves of data. For example, if you often need to process and review dozens of documents, check out this sample search solution with AWS.

Aerial view of Middle Eastern SMB teammates working at computers

5. Data analysis and predictive insights

AWS offers a range of AI and machine learning services that enable small businesses to extract valuable insights from their data. By using a tool such as Amazon SageMaker, businesses can analyze trends, forecast demand, and optimize operations, driving informed decision-making and competitive advantage. Check out this sample guide on predicting loan defaults for financial institutions.

6. Image and video processing

Generative AI capabilities extend to image and video processing, opening up opportunities for small businesses in industries like e-commerce, retail, and entertainment. With services like Amazon Rekognition, businesses can automate tasks such as image tagging, content moderation, and video analysis, enhancing productivity and user experience.


We know our AWS SMB customers have big dreams when it comes to expanding their businesses and the promise of AI excites them, but might not know where to get started. Once data is in the cloud, it can help SMBs improve content creation, optimize marketing efforts, or enhance customer support, to name a few. Generative AI offers practical solutions that were once out of reach for many small businesses but can become a reality. By using AWS’s suite of AI services and AWS Partner solutions, businesses can harness the power of AI to overcome challenges, drive growth, and stay ahead in today’s competitive landscape.

Learn more about the elements of AI in this past blog post written specifically for SMBs. As always, you can also contact us to transform your business and propel you toward success.

Mahesh Biradar

Mahesh Biradar

Mahesh Biradar is a Senior Solutions Architect at AWS with a history in the IT and services industry. He helps SMBs in the US meet their business goals with cloud technology. He holds a Bachelor of Engineering from Veermata Jijabai Technological Institute (VJTI) and is based in New York City (US).

Ahmed Megawer

Ahmed Megawer

Ahmed is a Territory Account Manager at AWS based in Dubai (UAE), supporting SMBs. Ahmed graduated with a Bachelor of Electronics Engineering from the American University in Cairo. He is responsible for helping customers define and implement a successful IT strategy by connecting them with solutions that deliver value. Prior to joining AWS, Ahmed worked as a Cloud Channel Sales Manager at IBM.

Mirabela Dan

Mirabela Dan

Mirabela is a Solutions Architect at AWS based in Dubai, where she is responsible for driving cloud adoption and growth for UAE SMB customers. She is also an elected advocate for the AWS Technical Field Community Core Team and an international speaker on all topics related to developer experience. In her previous role, Mirabela supported cloud enablement at one of the world’s largest online travel agencies, She holds a bachelor’s degree from The University of Manchester.