According to analytics firm GlobalData, Walmart is focusing on augmented reality and AI-enhanced store management. Amazon, meanwhile, is leading advancements in customer personalisation and autonomous systems.

Kiran Raj, Practice Head of Disruptive Tech at GlobalData, notes: “Walmart and Amazon are no longer competing for market share alone. Their AI strategies are reshaping the entire retail ecosystem—from Walmart’s blend of digital and physical shopping experiences to Amazon’s operational automation.”

GlobalData’s Disruptor Intelligence Center, utilising its Technology Foresights tool, has identified the strategic focus of these retail titans based on their patent filings.

Walmart has submitted over 3,000 AI-related patents, with 20% of these in the last three years, indicating a swift evolution in its AI capabilities. In contrast, Amazon boasts more than 9,000 patents; half of which were filed during the same timeframe, underpinning its leadership in AI-driven retail innovations.

AI-powered retail transformation

Walmart is deploying AI-driven solutions like in-store product recognition while making notable strides in AR applications, including virtual try-ons. The company’s progress in smart warehouses and image-based transactions denotes a shift towards fully automated retail, enhancing both speed and precision in customer service.

Amazon stands out with its extensive deployment of AI in customer personalisation and autonomous systems. By harnessing technologies such as Autonomous Network Virtualisation and Automated VNF Deployment, the company is advancing its operational infrastructure and aiming to set new standards in network efficiency and data management.

Walmart’s development of intelligent voice assistants and automated store surveillance emphasises its aim to provide a seamless and secure shopping experience. Concurrently, Amazon’s progress in AI for coding and surveillance is pushing the boundaries of enterprise AI applications and enhancing security capabilities.

“Walmart and Amazon’s aggressive innovation strategies not only strengthen their market positions but also set a blueprint for the future of the retail sector,” Raj explains.

“As these two giants continue to push the boundaries of retail AI, the broader industry can expect ripple effects in supply chain innovation, customer loyalty programmes, and operational scalability—setting the stage for a new era of consumer engagement.”

(Photo by Marques Thomas)

See also: Whitepaper dispels fears of AI-induced job losses

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Walmart and Amazon drive retail transformation with AI appeared first on AI News.

AI News caught up with Vincent Chio, Data Science Lead at Shopify, to hear what the company is doing in the space and how AI is improving the end-to-end retail experience.

AI News: How has AI changed the shopping experience in recent years for both sellers and buyers?

Vincent Chio: From automated marketing, to smart fulfilment, and predictive analytics, AI has made it easier for retailers to manage and grow their business. But not every retailer has the resources to build and implement AI in their business.

That’s why at Shopify, we really focus on bringing the power of AI—which has historically been reserved for enterprise businesses—into the hands of our merchants, who are businesses of all sizes. To provide a few examples of what that looks like, we use machine learning in our fulfilment network to predict the closest fulfilment centres and optimal inventory quantities per location to ensure fast, low-cost delivery of our merchants’ products. Our business chat app, Shopify Inbox, is built on a natural language processing foundation that helps merchants convert conversations into sales. And, through state-of-the-art machine learning models that predict merchant business success, our product Shopify Capital automatically sends our merchants funding offers without them having to apply.

How this shows up for and benefits buyers is in the form of more accessible, seamless and personalized shopping experiences. From targeted product recommendations, to faster shipping and better ways to connect, buyers expect more from retailers, and AI is helping retailers meet those expectations. 

AN: What are some of the hurdles you’ve faced in bringing an AI model into production and how did you overcome them?

VC: When it comes to shipping anything, there are always hurdles you’re bound to face. At Shopify, we follow a few guiding principles for implementing and scaling AI that ensure easy adoption from the get-go. 

At Shopify, we take a merchant-first approach to identifying problem areas. So our first principle for implementing and scaling AI is to make sure that what we’re building is solving a merchant problem, and that we have enough data to create a solution. 

Second, we start simple. If a regression model will solve our merchant problem, that’s where we start. This doesn’t mean we avoid building complex models, it just means that we first prove that we can use AI/ML to solve the problem, and then we iterate by building complex models. 

These two steps are key for getting stakeholder buy-in which, if you don’t get, can stop your project before it even gets off the ground. We’ve got more principles and tips that you can check out here. 

AN: An increasing number of third-party integrations are available for Shopify that harness AI—what are some of the most unique and/or interesting ones in your view?

VC: We’ve got a ton of third-party developers creating innovative apps that help extend the capabilities of our merchants’ stores. Some of the most interesting ones, in my opinion, are the ones using AI to translate those authentic, in-person retail experiences to online stores. Like I mentioned earlier, AI is changing the shopping experience by using data to bring more personalization to retail.

Our third-party apps that use algorithms to help merchants optimize the full buyer journey, from marketing and conversational automation, to recommendations and cart abandonment, not only have the power to help merchants convert, but they’re creating better shopping experiences for buyers.

AN: Shopify introduced LinNét earlier this year, its new product categorisation model. How does the new model differ from its predecessor and why was it deemed necessary?

VC: Shopify has seen amazing merchant growth in the past 2 years, hitting over 1.7 million merchants across the world. New merchants means new products, so we decided to reevaluate our existing product categorization model. We wanted to evaluate our old model’s performance because it’s important that we understand what our merchants are selling, so we can build the best products that help power their business growth.

After evaluating key metrics like how often our predictions were correct and how often do we provide a prediction, while also taking a look at our product road map and how our model might support new products, we decided to build a new model to improve our performance. 

Compared to our old model, LinNét not only uses text features for prediction but also images. On top of this, LinNét has the ability to understand products in multiple languages. LinNét was also part of a larger effort to modernize our machine learning systems and we can now do things like real-time prediction, which we couldn’t do with the previous model.

With these new features, LinNét has increased our leaf precision by 8% while doubling our coverage. If you’re interested in learning more, read our blog!

AN: What’s next for AI at Shopify?

VC: We’re excited to further leverage the scale of our data to not only empower Shopify but to create new experiences for our merchants that are impossible without data.

Some of the ways we’re doing that is by exploring how to better support merchant workflows through product understanding and creating experiences for merchants that suggest best actions for their workflows, while foregrounding merchant autonomy.

How that will show up is through eliciting merchant feedback through accepting or rejecting our recommendations, and through education around our machine learning approaches to workflow optimization.

AN: Shopify is sponsoring, speaking, and exhibiting at this year’s AI & Big Data Expo Europe. What can attendees expect from your presence at the event?

VC: Attendees can expect the chance to really get to know the Shopify Data Science & Engineering team, and the kind of work we do. 

On day one of the expo, you’ll get to hear more from me! Diving into Shopify Inbox and the natural language processing foundation behind the product, I’ll illustrate how we accelerate product development with AI at Shopify, providing takeaways that can be used at any organization. I’ll also cover how to build a data foundation to establish trust and identify opportunities only AI can solve at scale.

Then, in the afternoon, you’ll have the chance to hear from Shopify’s Yizhar Toren, Senior Data Scientist. Yizhar will join a panel conversation on ramping up AI projects, discussing key tips like how to move your project from experimentation to production, and turning AI into ROI.

Attendees will also get the chance to meet our speakers and recruiters at our booth on the exhibition floor. Come say hi at booth #301!

(Photo by Mike Petrucci on Unsplash)

Shopify will be sharing its invaluable insights during this year’s AI & Big Data Expo Europe which runs from 23-24 November 2021. Shopify’s booth number is 301. Find out more about the event here.

The post Vincent Chio, Shopify: On using AI to revolutionise the retail industry appeared first on AI News.

Moreover, despite the developments that have been contrived, some retailers have not yet acknowledged the true possibilities of AI and what this entails. It is these retailers that need to question themselves: what do we want to accomplish with AI? What can AI really deliver – and what will this mean for our customers?

The Power of AI 

The opportunities to leverage AI and ML to improve retail operations are exponential for either online, in store or in the warehouse. However, before AI can be truly powerful in the sector, the hurdles of data quality and quantity must be addressed.

Even with the magnitude of data currently captured by many retailers, they repeatedly struggle with capturing and retaining enough of the ‘better stuff’ – historical data that is factual, complete and textual – to take full advantage of the benefits AI can put forward. This data is fundamental to make AI and ML models the best they can be. In the rush to grasp innovation, it is easy to overlook the challenges presented and move focus away from the essential objectives, which should be: where is the ROI, and what is the implication for the customer experience?

Take, for example, a great AI solution in store that gathers information about a customer – such as hair colour, size, and style – to recommend new products, from hair-styling to make-up, fashion to accessories. This could be extremely enticing for customers, especially due to the pandemic, as it allows for minimal contact and social distancing.

Future Goals

With the future of various high street stores remaining questionable, getting the customer experience right at every opportunity – which means encouraging repeated visits – is critical. In today’s highly competitive retail landscape, ridden by challenges from Covid-19, consumers continue to face seismic hurdles with both offline and digital worlds. Therefore, it’s crucial to understand the key benefits that new technology will bring, including the customer experience implications. 

Today, customers will seek different retailers within the overloaded omni-channel marketplace if products can be delivered efficiently as well as being at a lower price elsewhere. Strong customer experience and satisfaction are not achieved through technology gimmicks, but through ensuring technology can help customers quickly get their hands on the products they are searching for before it’s too late. 

In practice, this means ensuring maximum stock availability where it is needed, at the correct time, and at the right location. It means achieving a slick warehouse and distribution centre operation that can deliver both to the store and to the consumer’s front door whilst adhering to social distancing requirements. AI solutions will add positive value when this structure is in place.

Change is good

Retailers that have utilised AI in the warehouse are already driving tangible developments in efficiency and accuracy. By combining high-quality order history data with AI and ML to greater grasp the aspects of purchasing trends, including direct to consumer ecommerce orders, retailers can reconsider operations. Schedules can be re-organised and resources rearranged, while orders can be seamlessly prioritised and new delivery choices enabled. 

In addition, AI enables retailers to better manage changing sales peaks such as the back to school rush or a sudden April heatwave. The huge rise in ecommerce orders experienced when stores closed their doors last year, indicates how retailers need to be well prepared if a new peak suddenly emerges. 

With the help of AI, retailers can take advantage of accurate and granular predictions that can be utilised to smooth out the entire logistics process and efficiently respond to challenges in real-time. With innovation at the core of AI, retailers of all types and sizes can use the myriad of AI and ML opportunities to level the playing field with giant retailers.

AI is taking retail by storm, however, putting the gimmicks aside, the real and attainable value of AI currently is to be gained by applying proven algorithms to drive fundamental supply chain developments.

Find out more about Digital Transformation Week North America, taking place on November 9-10 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

The post Utilising AI for retail in a post-pandemic world appeared first on AI News.

Shopic’s goal is to transform in-store shopping through its AI-powered clip-on device for shopping carts. The device recognises when shoppers add or remove items to their cart and allows them to pay without the need for a cashier or self-checkout machine.

Seemingly the next step in the nullification of supermarket employees, Shopic’s frictionless solution has enticed a number of investment companies, with Claridge Israel leading the round alongside existing investors Entrée Capital, IBI Tech Fund, and Tal Capital.

The device is already being deployed globally in selected stores of major grocery chains and this additional funding will be directed into accelerating said process and expanding the Shopic team.

“We’re excited to announce this additional funding that will help us progress more rapidly as we expand our solution into new stores and retail partners,” said Raz Golan, CEO and co-founder of Shopic.

“This investment, from a long-term growth investor such as Claridge Israel, is a vote of confidence in our approach to build and deliver frictionless retail solutions that are practical, immediately deployable, and cost-effective, without having to make major changes to the way stores are run,” he added.

Once attached to a shopping cart, the device automatically recognises items placed in or taken out of the cart in real-time, automatically registering them by price and displaying the shopper’s active receipt on the device’s screen.

Aside from just being a smart cart solution, Shopic also offers contextualised in-store promotions to users based on previous buying habits, store location, and item availability in real-time.

“Shopic has been developing retail-specific AI for several years, and we’ve gained intimate knowledge of the space and our customers’ unique needs,” said Eran Kravitz, Shopic’s co-founder and CTO. “Our computer vision technology solves many of the challenges of the noisy, visual-heavy environment of big supermarkets, while still delivering fast performance at very high accuracy levels.”

Initial deployments of Shopic devices in Europe, the US, and Israel indicate that more than 90% of shoppers are enthusiastic about the smart cart and feel that it improved their overall shopping experience. Initial data also indicated that shoppers using the device increased their basket size by more than 10%.

Find out more about Digital Transformation Week North America, taking place on November 9-10 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

The post Shopic AI smart carts secure further £7.2m in funding appeared first on AI News.

Drive-thru usage has rocketed over the past year with many indoor restaurants closed due to pandemic-induced restrictions. In fact, research suggests that drive-thru orders in the US alone increased by 22 percent in 2020.

Long queues at drive-thrus have therefore become part of the “new normal” and fast food is no longer the convenient alternative to cooking after a long day of Zoom calls.

Israel-based Hi Auto has created a conversational AI system that greets drive-thru guests, answers their questions, suggests menu items, and enters their orders into the point-of-sale system. If an unrelated question is asked – or the customer orders something that is not on the standard menu – the AI system automatically switches over to a human employee.

The first restaurant to trial the system is Lee’s Famous Recipe Chicken in Ohio.

Chuck Doran, Owner and Operator at Lee’s Famous Recipe Chicken, said:

“The automated AI drive-thru has impacted my business in a simple way. We don’t have customers waiting anymore. We greet them as soon as they get to the board and the order is taken correctly.

It’s amazing to see the level of accuracy with the voice recognition technology, which helps speed up service. It can even suggest additional items based on the order, which helps us increase our sales.

If a person is running the drive-thru, they may suggest a sale in one out of 20 orders. With Hi Auto, it happens in every transaction where it’s feasible. So, we see improvements in our average check, service time, and improvements in consistency and customer service.

And, because the cashier is now less stressed, she can focus on customer service as well. A less-burdened employee will be a happier employee and we want happy employees interacting with our customers.”

By reducing the number of staff needed for customer service, more employees can be put to work on fulfilling orders to serve as many people as possible. A recent survey of small businesses found that 42 percent have job openings that can’t be filled so ensuring that every worker is optimally utilised is critical.

Roy Baharav, CEO and Co-Founder at Hi Auto, commented:

“At Lee’s, we met a team that puts its heart and soul into serving its customers.

We operationalised our AI system based on what we learned from the owners, general managers, and employees. They have embraced the solution and within a short time began reaping the benefits.

We are now applying the process and lessons learned at Lee’s at additional customer sites.”

Hi Auto’s solution runs on Intel Xeon processors in the cloud and Intel NUC.

Joe Jensen, VP in the Internet of Things Group and GM of Retail, Banking, Hospitality and Education at Intel, said:

“We’re increasingly seeing restaurants interested in leveraging AI to deliver actionable data and personalise customer experiences.

With Hi Auto’s solution powered by Intel technology, quick-service restaurants can help their employees be more productive while increasing customer satisfaction and, ultimately, their bottom line.”

Lee’s Famous Recipe Chicken restaurants plan to rollout Hi Auto’s solution at more of its branches. A video of the conversational AI system in action can be viewed here:

Going forward, Hi Auto plans to add Spanish language support and continue optimising its conversational AI solution. The company says pilots are already underway with some of the largest quick-service restaurants.

(Image Credit: Lee’s Famous Recipe Chicken)

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

The post Hi Auto brings conversational AI to drive-thrus using Intel technology appeared first on AI News.

For some time now, the sector has also been at the forefront of another top technology trend. As they evolve to become the interaction hub of the digital enterprise, contact centres have been deploying AI-technologies at pace. Leveraging image recognition, natural language processing (NLP) and data analytics contact centres are now able to predict call volumes, enable new automated customer self-service channels, and boost the performance of contact centre agents.

Unsurprisingly, when the pandemic hit, contact centres were able to pivot at speed to cope with the ‘new-normal’. So much so, that other industry sectors have been inspired to deploy many of the AI technologies pioneered by contact centres to respond more effectively to the operational realities of today’s post-COVID world.

Transforming omnichannel retail

In the face of repeated national lockdowns, retailers have had to evolve their omnichannel service offerings fast to accommodate rapidly shifting consumer shopping habits. To optimise on-demand home deliveries and click-and-collect pickups from stores that are now operating as virtual warehouses, they had to utilise AI to integrate stock data from across their store and distribution networks. They are also using AI to auto-detect and proactively avoid inventory scarcity issues and aggregate and analyse consumer demand to accurately forecast the optimal product assortments and manage supply chain issues.

To further enhance the online shopping experience and make it more personalised, many retailers are investing in AI tools that enable customers to create a virtual model of themselves using their mobile or laptop camera. This offers customers the ability to ‘try on’ items like make-up, hair colour and clothing from the comfort of their home or create interactive 3D ‘photos’ of rooms to better visualise how furniture and accessories might look in their own spaces.

Revolutionising healthcare service delivery

The outbreak of coronavirus has helped to fast track a number of NHS initiatives designed to transform patient care and make it more predictive, preventative, and personalised. Intelligent automation (IA) – a technology similar to AI that combines robotic, intelligent and autonomous systems – is providing a foundation for this accelerated digital transformation. From supporting faster and more accurate disease diagnosis, to the more effective management of beds and staff resources and ensuring the NHS is better prepared and more responsive to future pandemics, IA is being leveraged to bring life-saving innovation across the health service.

But it’s not just clinical and disease management pathways that are benefiting. The NHS has also taken a pioneering approach to applying this technology to bolster the performance of its NHS 111 online and telephone service. Utilising automatic call routing technology has enabled the service to respond faster and more effectively to patients, prioritising at risk patients with complex or long term health conditions to the right person first time together with all their patient records and details.

These technologies also played a key role in enabling all healthcare providers to collaborate in critical decision making, in conjunction with government bodies, around the best way to deploy resources in emerging coronavirus hotspots. Similarly, digital agents are being used to streamline the management of patient prescriptions, online video bookings with GPs and clinicians and more.

Financial services deploy AI to support new ways of working

COVID-19 accelerated a rapid uptick in the adoption of call centre and channels by customers. Indeed, some banks reported a 400% increase in inbound calls in March 2020 alone. In response, banks and other financial institutions had to innovate at speed, turning to intelligent automation solutions to upscale their operations and streamline previously human intensive and error-prone processes like onboarding, know-your-customer, and anti-money laundering checks. 

To deliver improved customer support, they’ve also utilised AI-powered virtual assistants to automate responses to general queries – such as resetting passwords – and generate a deeper understanding of each customer’s context, behaviour needs and preferences so they can provide personalised recommendations and more streamlined customer journeys.

With thousands of employees across call centres, trading departments and other teams forced to work from home, financial services organisations have turned to AI to mitigate risks and ensure services continue to be delivered in a compliant way. 

Operational agility – it’s the future

Organisations in every industry sector are now taking advantage of AI and IA to optimise performance, streamline processes, deliver enhanced and more personalised services to customers, and uncover insights that can inform strategic decisions.

Providing the resilience that is needed to stay one step ahead of evolving market and consumer demands and disruptive events, AI technologies are now going mainstream and transforming the world of work as we know it.

(Photo by Matt Artz on Unsplash)

Looking to revamp your intelligent automation strategy? Learn more about the Intelligent Automation Event & Conference, to discover the latest insights surrounding unbiased algorithyms, future trends, RPA, Cognitive Automation and more!

The post Opinion: Adjusting and transforming with AI technologies appeared first on AI News.