AWS for Industries

Next Big Things for Retail – Generative AI leads the pack but isn’t alone

Over the years, retail has seen seismic shifts due to the emergence of new technologies. Examples include the barcode, ecommerce, and mobile phones, all of which had a profound impact on the way shoppers buy from retailers, resetting consumer expectations. (The same could be said for non-technical inventions like the supermarket format and malls, but we’ll be sticking to just technologies.) Retailers that stay on top of emerging trends are more likely to adjust and embrace those advancements to the benefit of their businesses.

Following is a summary of the four technologies most likely to have big impacts on retail. Additional details, including retail-specific use cases and solutions, are available in the Seismic shifts in Retail ebook.

Generative AI and Machine Learning

Generative AI (artificial intelligence) and machine learning technologies have emerged as powerful tools with transformative potential for the retail industry. They have revolutionized the way retailers analyze data, understand customer behavior, and make informed decisions. By leveraging these technologies, retailers can unlock valuable insights, deliver personalized experiences, and optimize various aspects of their operations.

Machine learning involves the use of algorithms that enable systems to learn from data and improve their performance over time without being explicitly programmed. It allows systems to automatically analyze and make predictions, or decisions, based on patterns and insights derived from data. Retailers have been using machine learning, in varied capacities, to optimize things like forecasting and personalization.

Generative AI, a specific type of machine learning, refers to the use of algorithms and models to generate new content, such as images, videos, text, or even entire virtual environments. These models learn from existing data patterns and can create novel outputs that resemble the original data.

Web3 and Spatial Computing

Web3, characterized by decentralized technologies like blockchain and cryptocurrency, along with the metaverse, a virtual shared space, are reshaping the digital landscape. As these technologies continue to evolve, the retail industry stands at the precipice of a major transformation. Retailers can leverage immersive technologies to create virtual storefronts, allowing customers to explore products, try them virtually, and engage with brands in novel ways.

Computer Vision and Sensors

Computer vision and sensor technologies have made significant advancements in recent years, helping to truly digitize physical stores. Computer vision involves the use of algorithms and artificial intelligence to enable machines to interpret and understand visual data. It encompasses various capabilities, such as object detection, facial recognition, image classification, and tracking. Sensors are devices that detect and measure physical inputs, such as light, temperature, motion, proximity, and more. In the retail context, sensors can be deployed in various locations, including shelves, shopping carts, store entrances, and dressing rooms, to collect data and enable real-time monitoring.

Not only can retailers collect data about customer traffic patterns, but they can remove much of the friction from checkout with Just Walk Out technology by Amazon.

Composable Commerce

The digital revolution has transformed the retail industry, enabling new business models and consumer expectations. To stay competitive and meet evolving customer demands, retailers must embrace innovative approaches. Composable commerce has emerged as a promising strategy that empowers retailers to adapt swiftly and efficiently. Composable commerce is a methodology that enables businesses to build and modify digital commerce experiences by assembling prebuilt, independent components known as microservices. These microservices encompass various functionalities, such as product catalog management, checkout processes, payment gateways, personalization engines, and more. By decoupling these functionalities, retailers can create a flexible and scalable commerce architecture using services such as microservices and containers, Amazon API Gateway, and AWS AppSync.

How can AWS help?

AWS works backwards with retailers, collaborating to imagine the end solution to a problem, then backing up to determine the tasks to achieve the goal. We are constantly exploring these technologies in the context of retail, and welcome engaging with retailers that are interested in transformations.


Of the four technologies examined, machine learning has the biggest potential for retail, including areas like deep learning, generative AI, and eventually artificial general intelligence, an autonomous system that surpasses human capabilities. By its very nature, machine learning technology continues to “learn” and improve. But the other technologies will also have impressive impacts, so retailers should monitor all four closely, looking at which use cases provide the most value for them.

To learn more about these technologies, download the Seismic shifts in Retail ebook where you’ll see use cases, benefits, and solutions for retailers.

Contact an AWS Representative to learn how we can help accelerate your business.

Further Reading

David Dorf

David Dorf

David Dorf leads Worldwide Retail Solutions at AWS, where he develops retail-specific solutions and assists retailers with innovation. Before joining AWS, David developed retail technology solutions at Infor Retail, Oracle Retail, 360Commerce, Circuit City, AMF Bowling, and Schlumberger’s retail and banking division. David spent several years working with NRF-ARTS on technology standards, is on the advisory board for the MACH Alliance, and supports the Retail Orphan Initiative charity. He holds degrees from Virginia Tech and Penn State.