Today, artificial intelligence (AI) has become an irreplaceable part of how we shop and do business on the web. It's a key component of the underlying infrastructure that brands and retailers rely on to engage customers, track trends, make better business decisions, and provide the most optimal, personalized customer experiences possible. Here are the top nine trends in eCommerce AI that you can expect to see in 2022 and 2023. AI voice assistants like Amazon's Alexa, Apple's Siri, and Google Assistant have become household names used by millions of people worldwide. In fact, 27% of shoppers took advantage of voice assistants to make online purchases in 2020, accounting for $40 billion of revenue in the U.S. and the UK alone.

Ankorstore is an ecosystem that enables independent brands and retailers to thrive. We're on a mission to rewild retail and restore it to its natural order by empowering brands and retailers to grow freely, embrace their creativity, and stay competitive. Our platform harnesses the power of technology to create a mutually beneficial community that reinvents the way brands and retailers work together. With decades of experience in retail and building marketplaces, in 2019 the Ankorstore founding team knew it was time to create a global wholesale solution to swing the balance in favor of independents and return them to their rightful place – at the centre of their communities. Just two short years later, we've grown to a team of over 650 employees operating across seven offices worldwide, and we'll grow even more in 2022.

One of the biggest challenges that marketers are facing today and struggling with is the massive amount of data that we see in our line of work, day in and day out. Some would like to call it "data overload," which is only getting compounded due to the speed at which we're getting data in ever-increasing ways. I like to say, and I am sure other marketers will agree, whenever we are putting together any strategic plan, we start with the data. We say, "What does the data tell us?" Data dictates everything that we do, from what people say on social media and review sites about our brands and products to our customers' suggestions on things that we should consider implementing, like a new soda flavor or a new travel route. Further, there are times when the data that comes to marketers also gives us a kernel of insight into potential consumer trends that may impact our brands and products.

We're officially a month into 2020 and the new decade is well underway. So much so, it is worth reflecting back as it jolted our eyes open and set the stage for what's to come. To sum it up in a word, data. Data, data everywhere – how to get it, how to use it, how to see it. Everywhere you looked there were analytics dashboards.

Consumer expectations are higher than ever as a new generation of shoppers look to shop for experiences rather than commodities. They expect instant and highly-tailored (pun intended?) To be forward-looking, brands and retailers are turning to startups in image recognition and machine learning to know, at a very deep level, what each consumer's current context and personal preferences are and how they evolve. But while brands and retailers are sitting on enormous amounts of data, only a handful are actually leveraging it to its full potential. To provide hyper-personalization in real time, a brand needs a deep understanding of its products and customer data.

Some amazing--as well as some downright freaky--innovations in artificial intelligence and machine learning were detailed at the recent Decoded Future NYC Summit, presented by Stylus. Take, for example, technology that will watch consumer faces as they shop online, recording smiles, frowns, or other gestures to measure interest in a product. In the near future, consumers could also be interacting "face-to-face" with virtual assistant machines that have lifelike personalities, emotional responses and character. While those advances may be a few years away, AI and machine learning have already become customary among brands and retailers who are looking to track the right trends in style, color, and pricing. The major players have been taking advantage of this technology for years.

Bottom Line: Manufacturers' most valuable data is generated on shop floors daily, bringing with it the challenge of analysing it to find prescriptive insights fast – and an ideal problem for machine learning to solve. Manufacturing is the most data-prolific industry there is, generating on average 1.9 petabytes of data every year according to the McKinsey Global Insititute. Supply chains, sourcing, factory operations, and the phases of compliance and quality management generate the majority of data. The most valuable data of all comes from product inspections that can immediately find exceptionally strong or weak suppliers, quality management and compliance practices in a factory. Manufacturing's massive problem is in getting quality inspection results out fast enough across brands & retailers, other factories, suppliers and vendors to make a difference in future product quality.

Inventory tracking -- that is, figuring out which products are in stock, which stock is likely to run low in the next week, and so on -- is a never-ending battle, as shoppers spend an estimated 40 billion hours picking things off store shelves. However, serial entrepreneur Richard Schwartz believes he has the answer, and it involves airborne drones with brace cages that resemble giant wiffle balls. Schwartz is the CEO and founder of Pensa Systems, an Austin startup developing a retail inventory system that taps computer vision algorithms to "understand" what's on store shelves. Pensa has already trialed its platform with Anheuser-Busch InBev -- a strategic investor -- along with several other brands and retailers in multiple countries. And at the New York Retail Federation's annual conference in New York, the company today announced that it has secured fresh capital it will put toward client acquisition.

Here's a look at five of the key vendors behind the technology that is allowing brands and retailers to streamline their distribution processes in order to operate more nimbly and deliver upon shoppers' increasing desire for speed and convenience. In our Future of Retail 2019 report, PSFK identified Bossa Nova Robotics, Kindred AI, Ocado, Takeoff Technologies and Persado as some of the leading robotics companies helping retailers build the DTC future through warehouse automation. Persado uses AI-generated language and emotion to interact with consumers and collects data from consumer spending patterns for brands to produce customized messages. Bossa Nova Robotics is an information services company that has created service robots for the global retail industry using enhanced technology of robotics, computer vision, artificial intelligence and big data to solve the challenges of implementing fully autonomous service robots in busy environments. Kindred AI is an artificial intelligence company that develops and programs autonomous robots by using innovative computer software to explore and engineer systems that enable robots to interact with and complete tasks in place of humans.

This piece accompanies a dedicated series from Ben around intelligence, A.I, and data-driven design and development in retail – all of which you can find in our 7th Edition. Similarly, you will find references to other'features', which denote to the other editorial pieces in our 7th Edition Report.] Just as WhichPLM did for both of our previous special editorial examinations (covering 3D in 2015, and the Internet of Things in 2016) the last exclusive feature in our 7th Edition acts as the final piece of the puzzle, collecting guidance, food for thought, and practical recommendations for retailers and brands who may be looking to lay the long-term groundwork for their own A.I. initiatives, or to embark on a particular, more pressing project. The clearest question for prospective customers of A.I. solutions: are these viable products, with clear return on investment potential? Broadly speaking, the answer is yes. While general intelligence – a single machine to run everything, with mental capacities far in excess of our own, across essentially all of human endeavour – remains a pipe dream, more focused applications of narrow, specialised A.I. are limited only by customers' ability to find the right technology partner and to gain access to their own information and broader market data in sufficient volume to deliver results. But even if A.I. was more limited – its capabilities confined to being a better analytics platform or Business Intelligence tool, for instance – I believe it would still rank as an essential investment for many retailers and brands.