AI in Retail: Time to Stop Experimenting and Start Delivering Value at Scale
We’ve been reading headlines about the revolutionary potential of artificial intelligence in retail for several years now. In fact, we’ve probably already reached the top of the hype curve for this much-touted technology. Accenture’s research shows, for example, that the vast majority of retailers (almost 90 percent) are now testing out the possibilities of AI, expecting it to transform their industry, drive growth and set new benchmarks for financial and operational success.
But while this “experimental” phase is all well and good, the true value of AI in retail comes from getting beyond proofs of concept and translating the technology into solutions that can deliver real returns for the whole business at scale.
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Right now, that’s not where most retailers are. Many initiatives are being pursued as one-off experiments conducted within the boundaries of existing business siloes. “Shiny object syndrome” means teams are buying in their own AI solutions without fully considering the dependencies and impacts across the whole business.
No surprise, then, that the true value of AI in retail is yet to be realized. Lacking an organization-wide cross-function strategy (or the necessary processes, skills and governance structures to go with it) the returns on AI initiatives are often smaller than anticipated. That contributes to a sense of inertia, with retailers struggling to turn their ambitions of becoming truly data-driven organizations into reality.
Turning experimentation into innovation
With every competitor searching for an edge with AI, the time for tinkering is over. The imperative is now to deliver the value, not just prove it. So, retailers should be looking to transform their great ideas and proofs of concept into real-world innovations that deliver next-level personalization, precision and profitability.
The value of personalization is well understood by the industry. But are fashion retailers targeting their personalization strategies on the right segments? Typically, just 5 percent of customers generate 33 percent of the profit. Retailers can use AI to first identify these highest-value customers and then home in on the personalized messaging that works best for them.
Look at how Stitch Fix uses a mix of AI and human stylist expertise to deliver personalization at scale. Blending insights into each subscriber’s preferences, lifestyle and budget, the rapidly growing start-up curates a regular subscription clothing service for its more than 3 million customers.
AI also allows a retailer to optimize operations with precision across the supply chain. By applying tools like machine-learning to their vast pools of omnichannel customer data, retailers can make more accurate predictions to help anticipate what will be bought, by whom, as well as when, where and how. These are crucial insights in radically optimizing inventory and reducing time to market.
Intermarché, for instance, is using machine learning and computer vision in conjunction with data visualizations to help staff offer assortments customized to the specific requirements of each locality. By creating a “data factory,” the leading French supermarket is fast-tracking AI concepts into viable solutions at scale, looking to quickly boost productivity and growth.
Ultimately, the value of a new technology comes down to its effect on profit. And here AI can impact both the top and bottom line. Indeed, Accenture’s research shows companies embracing analytics and AI have significantly more growth than those who lag in adoption.
A route map for scaling AI — fast
With the right AI strategy in place, fashion retailers can begin to really unlock value at scale. In doing so, there are four key areas of focus.
First, remember that people are the true drivers of business value. So executive teams should be leading from the top with a human-centered approach to AI, ensuring employees and intelligent technologies work collaboratively together. That includes assembling the right talent mix and supporting innovation across corporate siloes. For instance, creating multidisciplinary hubs of internal and external data experts can help retailers maximize the returns from AI.
Second, recognize that AI tools and solutions are only as good as the data used to train them. So it’s critical to have a data strategy encompassing all the multichannel data sources now available (including video, social and geolocation, as well as POS and inventory). This issue is too often overlooked at the c-suite level. In fact, Accenture research shows half of retailers with sales of more than $1 billion have no specific function to evaluate new analytics capabilities.
Third, get the right platform in place to support AI initiatives. Cloud platforms enable scaling at speed to support a culture of continuous AI innovation. The mega-platforms provided by global tech giants are masters of using data insights to streamline processes and incorporate innovative new capabilities. These platforms also allow retailers to tap into the best of the partner ecosystem, especially in areas like demand sensing and predictive analytics.
Finally, think about governance from the get-go. It’s not the most exciting item on the AI agenda, but it’s vital to successfully translating experimentation into scaled innovation. A good governance model will help identify value, prioritize action and optimize returns. It will also be essential in managing the necessary cultural change, and the responsible use of AI, as the organization transforms toward AI-powered decision-making.
The fast track to AI value
These four focus areas can help fashion retailers leave endless experimentation behind and accelerate and scale the value of AI. With the competitive landscape evolving quickly, this is fast becoming an essential capability for any retailer that hopes to forge new paths to growth. Furthermore, in this era of responsible retail, companies need to operate ethically and fairly in terms of their customers, their workforce, their partners and investors and our planet.
Through this lens of responsibility, retailers can deliver value to customers through data security, privacy and transparency — and AI is no exception. Responsible retailers are adopting AI, using information and tools in a way that maintains users’ data privacy, security and enables transparency while also unleashing the benefits of data. It’s time to get smart about AI and start seeing the true value at scale.
Jill Standish is senior managing director and global head of retail at Accenture. Vish Ganapathy is managing director and global retail technology lead at Accenture.
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