While many sing the praises of applications like ChatGPT, a manifestation of textual AI, there are a plethora of innovative implementations of AI which may have a direct impact on people’s retail and consumer experience. 

Companies like Standard AI are leveraging AI to modernize retail operations through practices like self-checkout and autonomous shopping. 

Standard AI retrofits existing retail stores with AI-vision-powered ceiling cameras that can track shoppers and accordingly build a cart as customers pick up or put down items in the store. 

Once customers are done shopping, they tap out of the store with their credit card and the receipt is automatically sent to them via text or email. 

Director of Engineering at Standard AI Mohit Singh said the implementation of this technology targets issues faced by an increasing number of brick-and-mortar stores. 

“Shoppers interact with stores in so many ways — apps, cash, card, ordering ahead, asking for restricted items — that it is important to meet them where they are and accommodate their preferences,” Singh said. “As their expectations for convenience increase, so does the size of the tech stack.”

Singh said satisfying shoppers often requires building a tech stack around a myriad of vendor solutions. 

“We have heard for years that retailers want vendors who can do more; they find it frustrating when they have to piece together a tech stack with dozens of vendors and rely on dated legacy solutions with few alternatives,” Singh said. “Retailers now have the ability to understand shopper behavior, assist staff with operations, understand inventory levels in real-time and more effectively personalize the digital experience and they can do it with a single product.”

Singh said Standard AI has launched multiple operational stores and is working with international retailers. 

“Shoppers love it,” Singh said. “With an autonomous checkout, they do not have to wait in lines, making the experience significantly better.”

Along with the efficiency it provides, Singh said there are additional benefits for retailers. 

“As we have rolled out our system, we have seen a 20% increase in basket size of our customers,” Singh said. “We can provide retailers with insights and analytics to a level of detail they did not have access to before. We have been able to reduce 10% of out of stocks that occur in stores and we have been able to drive a 27% boost in impulse buys with the analytics we provide to the retailer.”

Additionally, Singh said this level of automation helps address the consistent shortage of labor in today’s retail environment.

“Hiring and retaining talent is an existential crisis for retail, one that threatens to limit growth and store performance,” Singh said. 

In the future, Singh said the overarching ambition of Standard AI is to deploy the use of this transformative technology in other types of consumer environments. 

“Our system is powered by a computer vision system which can be extended to verticals way beyond retail to gyms, warehouses, cafes, restaurants and many more,” Singh said.

Technology-driven consumer experiences are also becoming increasingly popular in restaurants. Companies like Toast, Ziosk and Oracle are building automated menus, order placement, payments and tipping. 

Eric Neilson, Vice President of Engineering at Ziosk, said the company delivers tabletop devices to franchise-based restaurants.

“Specifically around the tabletop devices, we collect data and analytics on how people interact with those devices, track things like how large a typical check is at a table and track the average tips,” Neilson said. 

Neilson said restaurants generally receive more positive feedback when customers interact with technology. 

“When you provide a very smooth, seamless technology integration with a restaurant, people tend to have a more positive experience, and we can see a higher guest satisfaction with our customer survey data,” Neilson said. “Our data shows that tips are better with tabletop paying devices and make for happier customers and happier servers too.”

Neilson said Ziosk has improved its devices to better address customer’s needs through years of iterative design. 

“We have learned over the evolution of the technology what is important to both the restaurant and the customer,” Neilson said. “Battery life, ruggedization and an intuitive user experience were the core design considerations.” 

Technologies like Ziosk have also transformed the dining experience. Junior Elsie Parigi said QR code and tabletop ordering brings convenience and efficiency to the checkout process.

“It is easier to use, especially in large groups, so everyone can pay for their own food separately, instead of having to split the bill at the end,” Parigi said. “And once you are done eating, you can leave instead of having to flag down a waiter.” 

Junior Katie Yen, who served as a hostess at downtown Palo Alto’s New Orleans-themed Cajun restaurant Nola, said tabletop ordering also provides advantages for the restaurant staff. 

“At Nola, there are hostesses who handle reservations, servers who help people order and answer food or drink related questions and food runners who bring the food from the food window to the customer’s table,” Yen said. “I find that this system works really well, especially when it is busy because waiters and servers are able to focus on other aspects of their job, like bussing tables and answering questions, rather than spending most of their time taking orders.”

Yen said the transition to tabletop ordering proved easier for those well acquainted with technology. 

“Because of the pandemic, many restaurants switched to similar ordering procedures, and I have found that younger age groups who are more comfortable with technology can easily use these systems,” Yen said. “However, as a hostess, I noticed that older age groups struggled and demonstrated frustration with this system.”

And Parigi said elements of the restaurant experience have been sacrificed in order to achieve the convenience. 

“A lot of times, it feels as though the experience is the same as if you just ordered from home,” Parigi said. “I feel like that defeats the purpose of dining out in the first place.”

As companies accumulate data about user preferences, Neilson said they can parley this information into training AI and Machine Learning models that will continue to enhance the consumer experience.  

“Imagine a diner booking a table at a restaurant, being greeted as they enter and having their table and their favorite appetizer waiting for them when they get to the table,” Neilson said. “Or maybe you’re vegan, and we know this because you either put this in your preferences or it’s noticed by your orders, so when you look at a menu on the Ziosk device, it only shows you vegan entrées. We can use machine learning models to try to predict what we think a customer might like based on their previous orders.”

While technology creates issues of data privacy and increasing automation raises concerns about the future of the workforce, Singh said when it comes to the implications of AI on the consumer experience, society is  just scratching the surface.

Singh said, “These technologies are advancing at an exponential rate. The possibilities are endless.”