AI could be a Game Changer for SMEs: Generative AI, AI Tool Adoption

Despite the hoopla surrounding Generative AI, AI tool adoption is relatively modest. According to a recent Morgan Stanley poll, only 19% of respondents had used the ChatGPT AI chatbot. For most people, AI is still a buzzword rather than a practical reality, with a need to understand how these tools may benefit them. This is especially true for those who own small and medium-sized businesses.

AI has been a game changer.

While AI has been a game changer in online marketing, web searches, and shopping recommendations, its impact has been primarily limited to the tech sector. With millions of consumers, big tech companies like Google and Microsoft can afford to invest extensively in advanced AI technology since it improves their bottom line in the short term. However, supporting their limited AI resources only appears worthwhile for smaller organizations if they are certain it would considerably increase their income.

This is beginning to change as AI tools become more accessible and affordable.

However, this is beginning to change as AI tools become more accessible and affordable. Until recently, implementing an AI model was a challenging task. It entailed employing many engineers, collecting a large amount of labeled data, training the AI model with that data, and then using it. This procedure might take months and cost a fortune. However, thanks to generative AI technologies, it can now be completed in a matter of days without requiring an army of engineers. There is also a widespread misperception that massive amounts of data are needed to construct a helpful AI model. While this is true for large systems, even modest datasets can yield stable and functional AI models. As a result, small enterprises can gain a competitive advantage by using smaller customized AI models to expand and scale in unforeseen ways.

A coffee shop, for example, may utilise tailored AI to boost sales forecasting. Integrating customer and order information into an AI model makes it possible to identify patterns that humans may miss. It may be learned that a particular coffee sells better on Sundays or that buyers frequently match a coffee blend with a banana cake. AI can also aid in quality control by analysing photographs of freshly brewed coffee and comparing them to the ideal standard.

AI can improve inventory management and product positioning in the business.

Furthermore, AI can improve inventory management and product positioning in the business. Shoe manufacturing is another use for AI models. Based on past data, AI can assist with demand forecasting, supply chain management, and shoe quality control. An AI model can be trained to seek broken and defective shoes instead of someone.

Customised AI models can also be employed in garment manufacturing, pharmaceuticals, and restaurants. Because advanced AI technologies are now available, small businesses may leverage the power of AI at a reasonable cost and with minimal or no coding expertise required.

Because each organisation has a unique set of use cases and client base, AI solutions for small businesses cannot be one-size-fits-all. One shoe firm's needs may differ considerably from those of another. As a result, firms should concentrate on acquiring as much information as possible about their products, facilities, and other pertinent features. This data can then be used to train artificial intelligence models to recognise relevant trends and address specific problems.

Incorporating AI into enterprises is analogous to adopting the Internet in the 1990s and 2000s. Initially, it was employed mainly by computer companies, but soon, most businesses hopped on the internet bandwagon. Some firms currently run entirely over the Internet. However, learning from previous experiences with technology such as blockchain is critical. Because of the initial excitement surrounding blockchain, many began to apply it to problems with better solutions. AI and blockchain are excellent tools but should not be used arbitrarily. As a result, organisations must adhere to sound design thinking concepts.

Written by Preeti Anand