The AI Assault on Retail

At GrowCommerce, we spend a lot of time thinking about marketing trends that will transform retail and require news ways of engaging the customer. When we look out into the horizon, one trend driving disruption is the use of AI technology to automate customer interactions. Because of the importance of this technology, we asked Jon Nordmark, co-founder and CEO of, to share his thoughts in this blog post and on stage at GrowCommerce on July 20th. indexes 160,000 emerging technologies to help Iterate’s partners (17 retail brands and 10+ media brands) innovate faster and with more precision. Here are his thoughts on the state of AI, and the opportunities for retailers to gain a competitive edge. And if you’re interested in learning more, apply to attend GrowCommerce in NYC on July 20th.

The AI Assault on Retail
and how deep learning is fueling the new retail battleground

Lately, Google, Amazon, Facebook, Apple, Salesforce and Microsoft have been buying up AI and deep learning startups like hotcakes. Despite the $48 billion they collectively invest in internal R&D each year, these technology leaders leverage startups focused on AI technologies to build their products. Amazon, in particular, is leading the AI assault throughout the retail industry. With no signs of slowing down, it is quickly integrating deep learning throughout its web, mobile, supply chain and IoT experiences.

So, how does deep learning play into the AI ecosystem, how can AI help retailers, and what can retailers do to keep up? Many answers to these questions usually start and end with startups.

Step Aside AI—Deep Learning Is Taking the Driver’s Seat 

Deep Learning (DL) is not simply a sexy new label used to “sell” AI. It’s not a fad; it’s not just a sub-discipline of AI. Synonymous with “neural networks”, deep learning is the fastest growing field in artificial intelligence and can be applied in a variety of ways, continually pushing AI in new innovative directions.

It allows humans, and human jobs, to be replaced by machines, a well-known goal of Amazon’s. It enables practical, reliable applications of AI and machine learning—breaking down typical human tasks in ways that make possible all kinds of machine-assisted work, while delivering faster, more reliable, and safer outcomes. Self-driving cars don’t drink before driving, thanks to deep learning. Netflix recommends obscure movies that match your personality, thanks to deep learning. Amazon’s 45,000 deep Kiva Robots work in Amazon warehouses 24-7, and they don’t shoplift—thanks to deep learning. Robotic Radiologists don’t become sleepy after reading x-rays, with a high degree of accuracy, for 32 straight hours—thanks to deep learning.

In retail and elsewhere, companies training these deep learning systems now get a head start on those sitting on the sidelines. Companies claiming first mover advantage are poised to deliver better consumer experiences, faster, than those waiting to move. The more data a deep learning system consumes, the better it becomes, enabling AI to become entirely autonomous and self-teaching. Over time, systems train themselves on new data received and they learn from their mistakes—just like humans. Having a head start inarguably helps early movers gain competitive advantage.

Wake Up Retailers—The Time for AI Is Now

Technology companies like Google, Amazon, Facebook, LinkedIn, Pinterest, and Netflix, are positioned for leading a new AI-based world order with their massive datasets that are fed by constant consumer engagement. Their ecosystems create tight feedback-loops that continually improve their deep learning algorithms. Efforts like Amazon’s open-sourced deep learning program mean that in the nearer-than-we-think future, deep learning algorithms will programmatically affect pricing, marketing, merchandising, assortment planning, product recommendations, warehouse robotics, advanced home delivery systems, in-home shopping, and more. The AI-powered evolution of the customer journey is now undeniable.

Where does that leave retailers who are still uncertain about AI?

As sophisticated customer care apps emerged, AI became a focal point for retailers a year ago. AI-based customer care apps are emerging across a number of disciplines, from helping with real-time customer problem resolution to speak recognition.


(Credit: Brian Sathianathan,


But now, AI is all-encompassing.

Screen Shot 2017-04-17 at 11.44.57 AM


(Credit: Brian Sathianathan,


To keep up, retailers need to move technologies off old systems and onto AI-based systems—and it needed to happen yesterday. AI comes in a few different flavors and can affect numerous systems within any organization, including: inventory planning, voice recognition and computer vision used in areas like fraud protection, scheduling systems, programmatic writing, automated marketing tools, financial planning, and advanced analytics. AI will touch almost everything, and flatfooted retailers will be left in the dust.

Retailers can engage with AI-based startups and gain similar network effects, and similar advantages.

Yes, some technologies and some executions are far better than others. Watson, owned by IBM, is a horizontal AI platform, which serves many industries and purposes. But hundreds of startups are building vertical platforms that may require less training and command less cost, delivering even better results than the horizontals. Evaluating potential outcomes on a case by case basis is important, as is knowing what technologies are available.

How Retailers Can Actually Start Accelerating Innovative Initiatives

To prepare for what’s coming, retailers can start by updating internal jargon, like “I.T.”, and work hard to modernize internal cultures.

Out with the old and in with “I.T.”

Traditionally, the retail world has classified “the business” and “I.T.” as two separate entities. That increasingly ineffective world is one where retailers silo the technical, positioning themselves poorly to keep up with new trends. By demonstrating that you value “I.T.”, your company positions itself to hire the strongest technology teams. It aligns you with more 21st century work cultures.

Modern tech-driven work cultures—born as recently as 1994 (Amazon), 1997 (Netflix), and 2011 (Chewy and Dollar Shave Club)—are very different from those cooked up by traditional retail brands. Modern tech-driven cultures prize developers, and their new tech platforms are often modular. Older, traditional retail brands tend to be burdened by a myriad of cumbersome cultural descendants, including complex hierarchies, leaders who don’t understand technology and make slow decisions, pensions, and legacy technology stacks that are often large and monolithic (run by third-parties). This makes it difficult for established retailers to embrace the newest, most advanced technologies. As an older enterprise learns to work seamlessly with AI-based (and other) startups, it bridges cultural and technical gaps. New opportunities emerging around microservice technologies are also evolving to make older legacy systems behave in a more modular way.

Enter ExO and crowdsourcing

Any company can tap into AI and deep learning technologies by becoming an Exponential Organization (ExO). ExO is a form of crowdsourcing and leveraging third party resources. Today, this rare retailer competency needs to become a core competency. Amazon pioneers this ExO space, as well. In addition to the 1,000 engineers Amazon has working on voice AI technologies, Amazon has crowdsourcing and crowdfunding activities in place. To speed up the development of the products like the Echo, Amazon is investing $100 million (via its Alexa Fund) into startups that build voice-control apps to give it thousands of new skills. Amazon Studios’ original TV shows are also built upon a crowdsourcing platform that Amazon introduced in 2010 for aspiring scriptwriters—and now Amazon is winning Emmy’s.

To truly connect with the “Connected Shopper”, retailers need to find new AI- and deep learning-powered ways to enable and expand on existing connections. Iterate believes all retailers should immediately leverage strategic partnerships within the emerging startup ecosystem, which is funded to the tune of $80 billion per year. This will effectively and efficiently power each retailer’s own AI and deep learning practice, and will help the retailer stay competitive in this new age.