Artificial intelligence has become one of the most discussed topics in retail, but not always for the right reasons. While headlines tout bold promises and sweeping transformations, much of the current discourse has come to feel performative: flashy demos, exaggerated claims, and little operational substance. The disconnect between hype and practical application has gotten so bad that “executives demanding AI features that no one asked for” has effectively become its own genre of meme on TikTok.
But beneath that spectacle, a more consequential shift is underway. AI is transforming what’s possible for retailers, not just at the surface level but deep within their core operations. It’s becoming embedded into the foundational architecture, influencing how customers are targeted, data is governed, teams are connected, and decisions are made.
In recognition of AI Appreciation Day, I want to explore how retailers are moving beyond hype and integrating AI with purpose, applying it in more practical ways to drive measurable business value.
Personalization: From Universal to Singular
Retail’s traditional approach to promotions was rooted in mass marketing — sending the same weekly offers to broad customer segments. Email and mobile improved segmentation slightly, but the “spray-and-pray” model has always prioritized scale over relevance, and more importantly, precision.
AI has fundamentally changed that model. Today, the technology can facilitate real-time, one-to-one personalization that reflects individual behaviors, preferences, and context. For example, a customer who consistently shops for family meals on Sunday evenings might receive recipe suggestions and offers delivered via mobile when interest is highest, right as they’re writing their grocery list over coffee. And since they’re also a coffee connoisseur, they’ll likely appreciate a timely promotion for your new premium roast. Add it to the list.
The key isn’t just the algorithm; it’s the ability to connect the dots between behaviors, moments, and motivations. When done right, personalization doesn’t just feel relevant, it feels prescient and intuitive, not intrusive.
Data Use and Privacy: The Shift from Extraction to Partnership
Historically, retailers collected enormous volumes of customer data, often without a clear strategy or customer consent, then used it to deliver weirdly knowing promotions that could put recipients on edge. That approach has fallen out of step with both consumer expectations and regulatory demands.
Modern customers expect transparency, control, and genuine value in exchange for their information, and global policies, from the GDPR in Europe to the CCPA in California, are backing them up. Leading retailers are flipping the data relationship from seemingly unsettling retailer-controlled surveillance to consumer-empowered engagement, where transparency and accountability are prerequisites for personalization.
They are now adopting a “data partnership” mindset. That means being crystal clear about what data is collected, how it’s used, and what customers get in return. It means limiting data collection to what’s necessary and designing opt-in experiences where the exchange is clear and equitable: more relevant offers, faster service, or enhanced loyalty benefits. In today’s world, trust has to lead the data exchange.
Security plays a big role here, too. As AI expands into every corner of the retail experience, from supply chain to checkout, protecting the collected data isn’t optional — it’s foundational.
Ethics and Accountability: Building Explainable, Responsible AI
In the early days, AI operated like a black box. Inputs went in, outputs came out, and very few people understood how or why. That’s not good enough anymore. Today, responsible retailers are adopting explainable AI (XAI) frameworks, which allow teams to trace and justify algorithmic decisions. That means being able to identify and address bias, audit performance, and improve systems iteratively, not just reactively.
Retailers should think about AI governance in the same way they think about financial oversight: with clear accountability, cross-functional ethics committees, and regular audits. This isn’t about red tape. It’s about long-term resilience.
Retailers also need to ask: Who’s accountable when AI gets it wrong? The answer can’t be “the technology.” It has to be people, backed with the right processes in place to detect and correct mistakes before they damage customer relationships or brand reputation.
Business Operations: From Pilot Projects to Core Infrastructure
Too many retailers still treat AI as a pilot project, IT initiative, or a feature unceremoniously tacked on to the product in niche use cases. But the most successful implementations I’ve seen are fully integrated into the fabric of the business.
AI now plays a critical role across nearly every department. Retailers are using machine learning to forecast demand, flag inefficiencies, and drive faster, more data-informed decisions throughout the organization. It has become a core component of business strategy, influencing marketing, loyalty, customer experience, inventory management, and pricing decisions. They’re also increasingly leaning into machine learning algorithms to help optimize supply chains, predict demand fluctuations, and identify operational inefficiencies that human analysts might overlook.
At the individual level, team members are using generative AI tools like ChatGPT to accelerate routine tasks, draft content, and conduct research. At the company level, AI is connecting systems and workflows that once operated in silos. The result is shared visibility and a more cohesive organization.
We’re also witnessing the emergence of agentic AI systems that can coordinate activities across teams in real time. They’re already beginning to help retailers sync marketing, inventory, and customer service functions around a shared set of goals.
Final Thought: AI That Respects the Human Touch
There’s no question that AI is reshaping retail, but the most impactful implementations are not those that chase novelty, the flashiest bot or the AI features that no one asked for. Instead, they’re grounded in clear objectives: creating better customer experiences, improving efficiency, and protecting and building long-term trust.
Retailers that take a thoughtful, cross-functional approach, one that centers ethical principles, transparency, and customer value, will be best positioned to succeed in the years ahead.
As we mark AI Appreciation Day, it’s worth asking not what AI can do, but what it should do. Let’s commit to what’s practical, responsible, and valuable — for retailers and their customers alike.
