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.
