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Is now the right time for retailers to actively pursue AI?
Many surveys and much of the available research shows about a 50/50 split between companies that understand how to apply artificial intelligence (AI) technology to their businesses versus those that do not. So, looking at those who understand how to use AI is a good place to start.
These companies — I will call them AI Actives — have long since addressed the “how-to” question and continue to advance. Market leaders, even those that experience dips and bounces in financial performance, already invested in data and analytics as difference makers. The other 50 percent — I will call AI Hopefuls — have data, software and people who support it all, but have yet to execute and scale use cases beyond trials, at most.
Some AI Actives have begun reporting a lack of success and disappointing results. What sometimes happens is that, despite human capital, advanced technology and lots of data, the use cases selected may not be right or were not scoped and executed correctly. Many times the company’s strategy for AI doesn’t align the right resources with the proper use cases.
AI can actually be simple and easy because it is a feature, a function or the purpose of almost anything technology-related today.
Hopefuls aware of these options might feel relief knowing there is a fast path to AI that differs from the slog endeavored by AI Actives.
The lesson here is that, regardless of whether you are an Active or a Hopeful, success depends on:
- Identifying the use cases most relevant to your business and prioritizing them.
- Aligning the right resources to the right use cases.
- Continually re-evaluating use case opportunities for relevance and prioritization.
What I think happens over time is that Actives and Hopefuls converge on the same point where people, products, technologies and processes rationalize around a use case strategy based on the goals of the business.
Amid the COVID-19 crisis, companies are being tested by their executives’ ability to prioritize. Look for case studies on the leaders who reshuffled their businesses well in these uncertain times. AI use cases will most certainly play feature roles in these stories.
Discussion Questions
DISCUSSION QUESTIONS: Is it a good time for retailers to explore the use of artificial intelligence technology, given the current state of massive change? Are there any use cases for AI you can envision that are important enough to prioritize immediately?
Poll
BrainTrust
Gene Detroyer
Professor, International Business, Guizhou University of Finance & Economics and University of Sanya, China.
Shep Hyken
Chief Amazement Officer, Shepard Presentations, LLC
This is like asking when the best time to plant a tree is. The old proverb says, “The best time was 20 years ago. The second best time is now.”
Retailers must embrace new technology. Take the appropriate steps to determine if the tech is right for you. Look for tech that is applicable in good times or bad. Realize that if you don’t keep up with the technology and the times, your competitor probably is. Don’t get caught having to play catch up.
It could not have been said better: “This is like asking when the best time to plant a tree is. The old proverb says, ‘The best time was 20 years ago. The second best time is now.’”
To paraphrase a proverb, the best time to actively pursue AI was five years ago. The next best time is now. There are myriad use cases for AI in this environment that will likely carry over post-pandemic. Start with those that make the customer’s journey easier and more appealing.
I don’t know about this – I think retailers’ focus needs to be on taking care of business, the health of their staff, and the health of customers. AI needs a detailed focus and infrastructure changes that might not be prudent right now in our current state. While I believe that AI and technology enable businesses to run more efficiently and productively, I just don’t think this is a priority at this time.
As beneficial as AI may be, in the middle of this crisis retailers are focused on survival. Many retail head office jobs (including data analysts) have been disrupted by massive layoffs and furloughs. If retailers already have an AI capability, they should use it; if the retailer doesn’t already have an AI capability, trying to explore and deploy it now would likely be an unhelpful distraction.
AI provides many benefits to the businesses that have invested in it. And as the article says, it’s essential to use it correctly to obtain the information it can provide and from that information help make the right decisions. That said, I doubt companies that have not invested in AI or have not learned to use it to its fullest potential will be thinking much about it now. We are in survival mode and anything that can be cut will be cut. Once businesses reopen, there will be more cutting. That includes inventory, personnel, advertising, and, unfortunately, technology. I am afraid that when this pandemic is over, and we attempt to get our nation back on track, it is going to be a prolonged process with months of many Americans out of work, businesses forced to file for bankruptcy and whole industries seeing their one-time lucrative opportunities drying up. I hope this will be temporary but, as of now, no one knows how long the pandemic will be with us, if it will return, and how long the country will remain shut down.
I have said for a very long time that the use of AI in retailing is table stakes for the future success of retail. The majority of retailers have so much data available they are swimming in it. The only way to successfully activate against this data is with the thoughtful use of AI. Retailers must move towards using AI to better understand their business and use the analytics to effectively market to their customers. Retailing, both online and brick-and-mortar, are being required to change because of the current business environment. It is more critical than ever for retailers to find new, creative ways to engage the consumer. AI can help.
AI is not a panacea and won’t be even in a crisis. If retailers haven’t been disciplined in their use of AI prior to now (and more importantly, disciplined in data management), scrambling to implement AI during this crisis won’t solve any problems. As the author very well knows, (Gib is an expert in this area), the key is the discipline around data management before the application of AI. AI only works when it has all the trusted data necessary, which can be used by the machine to come up with decisions which people can then leverage. It isn’t a matter of “flipping the switch to turn on AI and you get automatic results.”
I think this is the perfect time for an AI strategy. One that looks at the core values of a retailer and aligns those values with the new customer journey. The BOPIS journey is a use case that must be prioritized now. There is massive discordance with BOPIS when what is needed and constantly touted is a “frictionless” experience. We need to consider a new model. A dark or semi-dark model where we rethink what a store really is. It is a distribution point and as such, given the current circumstances, we need to rethink the journey. We need to leverage AI to match the customer expectation with the new normal.
Well if you haven’t invested in transformative technologies by now, then there is no time like the present! These emerging and now maturing AI technologies have been on the market for years, and have become a fundamental driver of the personalized customer experience. A data and analytics strategic approach are fundamental to enabling companies’ digital transformation initiatives.
From my experiences, even today, most people have a CliffsNotes (remember those?) understanding of AI and ML. As Gib points out, “the use cases selected may not be right or were not scoped and executed correctly.” And still high on the list is leadership buy-in. Many today speak of AI as a buzzword. This statement pretty much sums it up. It would have been a good time to explore AI at a minimum at least five years ago. Those days are gone. Given the knowledge and interest gap around AI for retailers, I think it is best for retailers to focus on how to reinvent retail in and of itself in our new world of health and economic disaster survival.
The problem with the way people talk about AI is that they make it sound like a solution – it is not, and retailers should think about what they are trying to achieve not about “AI initiatives.” They will then identify where AI may and almost certainly will be able to help them. But as long as we keep referring to AI as if it is a solution, the greater the chance that people will dismiss it because they do not understand or see it.
History has shown us, whether in business or battle (or personal life) that the best time to make progress is in times of stress.
That is when we come up with challenges and opportunities that we did not expect. AI will be the perfect example. What are the challenges now or the solutions in AI that we never thought of? By happenstance does it give us some answers we never previously considered?
Those retailers that have pursued AI will make leaps forward. Those who have not will fall further behind.
Retailers should focus on solving business-critical problems that will help them survive, and they need solutions that can be leveraged in appropriate time frames. So a three-year ROI isn’t a priority no matter how compelling. With those priorities crystal clear, I have little doubt that AI should be part of the many solutions where its potential will fit. (Which will be in quite a few places, but as others have pointed out — you have to match the use case properly.) However now is not the time to pick a solution and then find the problem.
This is a great time to explore your business challenges first, then develop a potential use case, and then finally determine if AI has the potential to solve the business challenge. Don’t try to stuff AI into a part of your business just because you think you should be using AI. However, yes, today companies are offering totally free AI solutions to address immediate problems with COVID-19, so I definitely recommend exploring vendors right now.
The most powerful AI applications in retail right now are in the marketing stack. ML-taught models can be implemented very quickly (with about one day of tech work, and three weeks for the models to learn) and can be transformative to the real-time decisions that retailers make in marketing. As brands begin to toe-dip back into digital performance marketing, spending ad dollars in judicious, high-impact ways will be critical. AI can be used to predict the future value of every online shopper in real-time. Those predictions can then be activated in Google, Facebook, Instagram, etc. so ad dollars are only spent on users most likely to actually buy.
So while now is NOT the time to invest in 3-yr AI strategy, it IS the time to deploy smart, simple, transformative AI applications. They are available to use out-of-the-box, and can have massive positive impacts on near-term P&Ls.
Leveraging AI should be about problem solving and thinking about AI as a tool, not an end state. Companies investing in AI now will have advantages and be ahead of the curve against their competition who didn’t – but the same would hold true even outside of a crisis. Finding the right options here and maybe even applying AI to current problems can be valuable. AI application to logistics, routing, deliveries, even store format or planogram adjustment to ensure customers in the store stay apart can be potentially useful – but these are only as pressing as the retailer feels AI’s importance will be going forward. The concept of AI is broad and its potential applications are also just as broad. This is about belief in AI to solve specific problems, not whether it makes sense to pursue or not.
Great thoughts Ananda. “Companies investing in AI now will have advantages and be ahead of the curve against their competition who didn’t – but the same would hold true even outside of a crisis.”
Key point here is “outside of a crisis.” The crisis doesn’t change anything regarding leveraging this progressive capability of AI, in my opinion.
Intuitively, since a lot of implementations work best from a “ground up” perspective, this might seem like an ideal time. A lot of companies, sadly, are essentially starting from zero.
Realistically though, with most retailers now either incredibly busy (grocers, online sellers) or facing bankruptcy (most everyone else) it’s probably the worst possible time. That so few people chose the first answer, I think, is hope over experience.
Crisis situations are the best time to reinvent and revolutionalize. The concepts of AI and ML have been around for a long time but only in recent years have we started to understand and unlock their full potential.
In our current environment, the massive shift to digital (voluntary and involuntary) allows companies to collect even more data from shoppers. Dynamic AI/ML driven models provide retailers with abilities for predictive pricing and promotions.
In an unprecedented time, when retailers will struggle to keep up which categories and products are driving demand, AI provides assortment optimization. Amidst a major refocus on online merchandising, AI provides insights that can help build brand loyalty. For example, through Amazon’s website, Whole Foods shoppers can see their transaction history. This added-value of convenience makes the entire shopping experience more effortless which in turn increases share of wallet.