What Are The Challenges To AI Adoption In Retail? 16 Experts Share Their Insights

  • 23 September 2019
  • Sam Mire

There's no shortage of promises that artificial intelligence will fundamentally change the way we shop. The technology could also be a boon for retailers, but AI implementation won't come with the snap of the fingers. The challenges to AI adoption in retail are many, and they're real. Here's what industry insiders say could most hinder AI adoption in retail:

1. Brian Walker, Chief Strategy Officer at Bloomreach

“One of the biggest challenges for any business to adopt AI is the structure and cleanliness of their data because if you put data into the AI that doesn't make sense, you will get data out that don't make sense either. And getting clean data from a run-time environment like commerce is not a one-time process.”

2. Amanda Nichols, Senior Manager for Retail, Hospitality, and Food Service Practice at Kronos 

“Fear and trust. AI done right has the potential to reduce or eliminate various roles across the retail environment. But will executives trust when the data steers them towards counter-intuitive decisions, such as identifying the best locations to open stores or which stores should be closed? Algorithms are only as good as the people who write them and the data that inform them. Teams looking at AI-generated recommendations should ensure they keep a balance between relying on technology and the inherent nuances of working with people.”

3. Shep Hyken, Customer Service & Experience Expert, NY Times Bestselling Author of Amaze Every Customer Every Time 

Shep HykenAI is linked to data. How is the data being used. Transparency and proper use of the data is paramount to creating confidence (and loyalty) with a customer. When the information is abused by the retailer, you may lose your customer.”


4. Kerry Liu, co-founder and CEO of Rubikloud

“Cleaning and preparing data to run models is the first challenge businesses face when beginning the personalization process. Modeling the freshly cleaned data properly is a task that if done poorly can be detrimental to the outcome of the entire project.”

5. Julian Fisher, CEO of jisp

“The biggest challenge to AI is cost and confidence. With some small steps there are a number of retailers both on and offline who have reported huge improvements in sales, but change is not something the retail sector is known for, even if a competitor is gaining ground.”

6. Brian Kilcourse, Managing Partner at RSR Research

Brian Kilcourse“The top challenge is dirty data (it's the elephant in the room).  Models are only as good as the data that creates them. One recent study estimated that over 80% of the effort of implementing AI relates to data cleansing.”

Michelle Bacharach, founder and CEO of FINDMINE

“Where to begin? AI can be used everywhere! Not to mention the resource constraints internally when all departments are trying to update their own technologies with AI! Just basic blocking and tackling take up all retailers time sometimes so where are the resources, the talent, and the time to execute on implementing AI?

Which is why we designed an ROI calculator for our clients, some of the most innovative global retailers to show how much additional top-line revenue their company should be making from having consistent outfits available for a majority of their product catalog and across channels. This helps create a compelling business case to get resources internally to invest in a multi-channel outfitting strategy. Some applications of AI, however, don't come with a built-in business case, and therefore will take longer to get adopted.”

7. Trey Courtney, Chief Product & Partnerships Officer at Mood Media

“The biggest challenge is the rapidly changing nature of the underlying technology. It’s all changing so quickly that it’s hard to place a bet without worrying that the next great application is right around the corner. I think we'll see more pilots and experiments over the next few years as the technology matures.”

8. Mike Callender, Executive Chairman at REPL Group

“The challenge as with most IT spends is budget and planning cycles. AI is developing faster than the typical retail IT budgeting process leaving projects in this area to come out of the CIO’s limited discretionary spend budget. Most retailers also are very risk-averse and are looking for others to be at the cutting edge. Couple this with the suppressed retail environment and it makes speculative ROI decisions difficult.”

9. Gil Larsen, Vice President of Americas at Blis

“Despite the rise of the omni-shopper, our research has shown a noticeable ingrained preference for making purchases in-store. While AI is great for creating tailored, seamless, omnichannel experiences, there are customers that will always prefer an element of human interaction. A challenge that retailers may face is investing too much in AI and creating an experience that feels inauthentic and too far-removed from the in-person experiences many (particularly older generations) are accustomed to and prefer. It will be important for retailers to leverage this technology to drive a positive shopping experience while also ensuring human-centric options are still available.”

10. Joe Skorupa, Editorial Director at RIS News

AI adoption is clearly on the retailer's radar today according to spend trend analysis. But the problem is most of it is scheduled for one and two years in the future. Frankly, this may be too late. Does anyone think the record-setting success at Amazon, Target and Walmart, as well as the surprising turnaround success at Best Buy, would be possible without their heavy in investment in AI engines several years ago? AI investments and deployments take time to reap measurable benefits. The sooner a retailer begins transforming core applications with AI engines the sooner they will reap benefits.”

11. Vidyuth Srinivasan, CEO of Entrupy

“I think a lot of companies, especially in sectors that have reputations for lagging behind in technology adoption – of which retail is one – are simply afraid. There have been too many dramatic “The robots will take your job” stories, and people working in an industry that’s already experiencing significant challenges probably feel their futures are already uncertain enough. But the reality is, AI is nowhere near the point where it can replace a human. It can just make humans do their jobs better and more efficiently.”

12. Yigit Kocak, Inbound Marketing Manager at Prisync

“Having an accurate, clean, and organized data. More than half of the retailers are unable to access data, which creates an obstacle to AI adoption. Only then, AI can work properly. In reality, retailers expect everything to be implemented by using expensive software or by believing marketing copy.”

Kevin Sterneckert, CMO, Symphony RetailAI

The primary challenge to AI adoption in retail today lies with decision makers. Many of them are worried that AI will take their job or reduce their value to the business. This isn’t completely unfounded; Amazon, for example, changes prices on its products 3 million times per day by leveraging AI. 

But I don’t see AI as a threat to job security. In fact, AI should be considered a personal decision coach. It helps users to sort through billions of records in real time to identify opportunities. Ultimately, AI helps decision makers identify the relevant story within their data so they can make more informed decisions that drive more value, more quickly. We’re highly confident that once this is proven out over time with both pilot programs and large-scale deployments, investments in AI across the industry will increase dramatically.”

13. Sanjeev Sularia, CEO of Intelligence Node

Many small and medium, as well as conventional retail organizations, still lack the foundational practices to create value from AI at scale. They often get deterred by the costs of building the infrastructure and data processing capabilities needed for AI adoption. However, flexible businesses have successfully integrated AI across all business functions and upskilled their people to efficiently reorient to a data-driven mindset without trying to build everything from scratch.”

14. Akhilesh Tripathi, Global Head of Digitate

“As more retail organizations move to a multichannel sales approach (brick-and-mortar, mobile, online), there’s an increased expectation that the same standard of superior customer experience is delivered across all of these. But this move to multichannel has also created a massive variety, volume, and velocity of data that needs to be grappled with and which is too much for humans alone to handle. On top of this, the retail industry has traditionally been slow to adopt new technologies in general.”

Carol Spieckerman, President of Spieckerman Retail

“Discomfort and uncertainty on the part of consumers. Back-end usage (data processing) is largely invisible, however, front-end solutions that tie into AI like robots in stores and facial recognition can spook shoppers.

Retailers must frame consumer-facing innovations in terms of clear benefits. Self-serving solutions that depart wildly from the past will be met with skepticism or even push back. I would place talent at the top as well. As much as the conversation around AI centers on automation, without properly trained people and articulate ambassadors, the potential will be cut short.”

Oz Etzioni, CEO of Clinch

“Management and workflows. I believe these are decisions that need to come from the top C-level. These decisions need to be supported by personnel, budgets, attention, and goals as part of the transitional roadmap of the retailer. AI adoption, which is not a stand-alone process. ties into many other processes and executions and many other workflows that need to change, in order to accommodate the integration of AI into workflows and execution process. Personnel overseeing the workflows might need to change the size of teams, the QA process, budget and allocation, goals and more. These are changes that require forward-thinking planning and affect many departments of an organization. Therefore, the decisions need to come from the top and be supported within the organization’s roadmap- with enough allocated resources and experienced personnel.”

15. Alexandra Sheehan, B2B Retail Copywriter for Shopify, Vend POS, and Stitch Labs

“As mentioned above, with more technology comes more touchpoints. Retailers have to navigate where AI will truly enhance the shopping experience instead of detracting it. It can be tempting to add all the bells and whistles to your store, but if it gets in the way to the path to purchase, you’re ultimately not doing your job.”

Chris McCullough, CEO and co-founder at Rotageek

The real challenge now lies not in the adoption of AI per se, but in revamping current processes using more intelligent approaches to solve problems. The challenge here is taking the huge amounts of data and interpreting what it actually means, and then taking this information and rethinking how we currently approach tasks and problems.”

16. Sean Byrnes, CEO of Outlier

“Surprisingly, the biggest challenge to AI adoption continues to be human resistance. Despite evidence that shows that AI can improve human behavior and results, making them more valuable to their organizations, many analytics teams still fear being replaced by automated systems. In this case, some choose to do nothing and continue attempting to sift through mountains of data, ultimately missing important trends. This resistance to adoption is real and leaders need to identify and overcome it to drive the efficiencies they need to survive in the market.”

Jeff Hunt, founder of Snap36

“There are always barriers to every kind of new technology, but retail in particular has traditionally been a very rigid industry. It’s highly structured and there’s not a ton of collaboration going on between departments. That’s the disadvantage it has compared to digitally-native eCommerce companies. For example, what Sears once had going for it was that it was mostly a real-estate company, and it just had to concern itself with shipping out products to all its different stores. But they focused on that instead of growing their IT capability, and by the time they tried to create one, it was already too late. Luckily, retailers are quickly seeing they need to adapt.”


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About Sam Mire

Sam is a Market Research Analyst at Disruptor Daily. He's a trained journalist with experience in the field of disruptive technology. He’s versed in the impact that blockchain technology is having on industries of today, from healthcare to cannabis. He’s written extensively on the individuals and companies shaping the future of tech, working directly with many of them to advance their vision. Sam is known for writing work that brings value to industry professionals and the generally curious – as well as an occasional smile to the face.