AI in retail is everywhere. Walmart uses it to analyze what customers are buying and adjust inventories and supply chains automatically. Amazon’s legendary machine learning algorithms drive revenue by recommending products based on customers’ behavior. And the fashion brand Gucci, with the recently launched “Gucci Assistant,” chats up users as they move through the customer journey.
While AI was initially associated with big tech and multinational brands, the technology is becoming increasingly available for everyone. Startups and small and medium-sized retail businesses can reap the benefits of using AI even when they do not have big companies’ resources. To do this, they need to understand the benefits and the risks and have a game plan aligned with their business goals.
How Small and Medium Retailers can get into the AI Game
There are a few things that small and medium-sized businesses can do to get started with AI and GPT-style models. They can partner with a larger company with the resources to deploy these models. They can also turn to cloud-based AI services that do not require any upfront investment and they can start small by using AI for simple tasks, such as customer service or marketing.
As AI and GPT models become more affordable and accessible, we expect to see more small and medium-sized businesses using them. Starting slow and laser-focused is essential for retail companies looking to benefit from AI. As the saying goes, “Think big but take small wins.”
Why should a company start slow? AI and GPT models can be complex and expensive to implement. It’s also essential to make sure that AI and GPT models are used in a way that is ethical and responsible. And getting feedback from customers and employees is critical before scaling up the use of AI and GPT models.
More importantly, by starting slow, small and medium-sized businesses can avoid some of the most significant risks of AI and GPT models. Companies should closely monitor AI bias, inaccuracy, cybersecurity, job displacement and data privacy.
AI can help retailers improve their performance, efficiency and customer satisfaction if developed appropriately. It can tailor products, services and marketing to target individual customers based on their preferences, behavior and feedback.
The technology can also enable retailers to optimize their end-to-end operations, manage pricing and organize logistics. It reduces costs, waste and errors and increases profits and customer satisfaction.
AI on a Budget
Economic uncertainty is pushing every industry into a highly conservative mode — freezing new hires, pausing expansion plans and slashing budgets. However, retailers can still deploy AI applications in this tight economy.
Companies can start working on numerous cost-efficient, easy-to-use and easy-to-deploy AI retail applications today.
For example, chatbots offered by top cloud vendors like Google, Microsoft or Amazon can provide customer support or talk with clients. They can be used to automate customer service tasks. These chatbots can be rapidly embedded into a business’ website or mobile app and are usually built into cloud plan packages.
AI product recommendation is another popular and powerful AI feature that can be accessed rapidly due to its abundant availability. This technology is offered by top cloud vendors and companies that provide product recommendation-as-a-service. More importantly, the tech is a perfect fit for small companies.
Similarly, AI fraud detection features, fully developed and used daily by financial companies worldwide, are also available as cloud-based apps. This technology seamlessly integrates into touch points and platforms.
To move an AI agenda forward, companies can follow three steps:
- They must select AI applications aligned with their business goals and targets and not randomly buy into AI services without a clear plan;
- Once the apps are deployed, they must get feedback from management, employees and customers; and
- Knowing if an AI is working as it should requires constant supervision and maintenance.
Understanding the Challenges and Risks
The talent gap is the first roadblock small and medium-sized companies face when deploying AI. AI technology models are complex and require a lot of data and computing power to train. As a result, small and medium-sized businesses often do not have the resources to deploy these models. AI systems also need to be intensely trained, tested and maintained. To resolve these challenges, AI providers are designing no-code AI applications that are easy to use, affordable and accessible.
Like any public technology, AI apps must avoid common pitfalls, legally comply with data and consumer laws and be secure and accurate. Most of these pitfalls are linked to data quality. Some AI applications are built to ensure privacy first, and these are the ones companies should be considering.
Data is the basis of AI. If the data that feeds your AI is incomplete, inaccurate, outdated or biased, the system will be unreliable and negatively impact your bottom line, customers and employees.
Another problem for small and medium businesses is data privacy. Trends show that users have become extremely sensitive to how companies manage their data. Laws such as the California Consumer Privacy Act and GDPR have directly responded to peoples’ data privacy concerns. New laws like the European Artificial Intelligence Act are expected to play a significant role in the near future. Small and medium-sized retailers must understand governance and compliance to avoid heavy fines and reputation damage and to build trust among its workers and consumers.
Solving Real-World Retail Business Problems
There is a fundamental difference between the AI-media hype and the reality of how the technology is used in the real world. We all remember when the metaverse was top news, rapidly becoming an overhyped tech that has yet to live up to its promise.
The lessons we learn with innovation is that it must always be put into play to solve real world problems. AI has already proved to have tremendous potential in that area.
From personalization to automation, analytics and opening new channels, AI will profoundly impact the retail industry. And there is no reason why startups or small and medium-sized retailers should not benefit from AI.
Sajid Mohamedy is a seasoned professional with a wealth of experience in business planning and market analysis. Having worked with major brands such as Gap, Walmart, Intel and Falabella, he specializes in delivering scalable, cloud-based solutions. With expertise in ecommerce, digital strategy, business agility and blockchain, Mohamedy has a proven track record of delivering exceptional results in a highly competitive market. As EVP of Growth and Delivery at Nisum, he leads the development and delivery of innovative solutions that drive business and people growth and success.