How agentic AI Is redefining self-expression through commerce
This holiday season marked a turning point in retail. With AI increasingly embedded in shopping journeys, the question is no longer if AI will affect retail – but how deeply. Consumers are turning to AI not just for inspiration, but for actual decision-making and it is quickly reshaping the way consumers express identity through what they buy.
At the same time, a new foundation is taking shape: emerging AI agent protocols such as the Model Context Protocol (MCP) for tool access, and the Agent-to-Agent Protocol (A2A) for agent collaboration. These protocols are becoming drivers of change. They point toward a picture where seamless coordination between AI agents could redefine everything from product discovery to personalized service.
I call this shift Algorithmic Intimacy: the moment when AI agents learn not just what customers have bought before, but what they aspire to – delivering a level of personal relevance traditional digital commerce could never achieve.
American retailer Target recently announced it was bringing holiday shopping directly into ChatGPT, allowing customers to search, add to cart, and purchase through conversational AI. While this is fairly basic and it is still early days, it’s a move that signals a fundamental change in how people want to discover products today.
As Christmas shopping pushes product discovery, personalization and decision-making to their annual peak, Target’s move shows the first real signs that AI is beginning to shape not just what people buy, but how, where and why they buy it.
Shopping has always been about more than acquisition
If the holiday season proves anything, it’s that buying has never been just about acquiring things. It’s about identity-making, belonging, generosity, and self-expression. Historically, the fear around AI agents has been that they’ll replace these emotional experiences with cold optimization. But that fear is misplaced.
For example, instead of scrolling through 500 nearly identical jumpers, an AI agent can surface three that match a consumer’s aesthetic, fit their climate, suit their style (based on past purchases and aspirational content they are viewing) and align with values such as sustainability – all before they even articulate the criteria. These bots can even throw in a bold recommendation.
Agentic AI aims to remove the noise around shopping to improve decision-making whilst still maintaining the human touch. No more endless scrolling or sifting through thousands of irrelevant options or relying on the curation of merchandisers, instead focusing on recommendations that fit a person’s taste and intention.
This shift is already visible in the UK, where Boots uses AI-powered beauty diagnostics to recommend skincare and cosmetics uniquely suited to each customer’s profile – helping them feel seen, not sold to.
With smarter visual tools and a better sense of preferences, these AI agents can show how something will actually look and feel on someone in their everyday life. The deeper change though, comes from how they learn to read taste and intentions over time.
They infer aspirations from subtle behavioral cues, not just past purchases. They start to understand what consumers might be thinking. They remember the gift that was hesitated over last Christmas – and recognize when this year, the moment is finally right.
Adding the element of surprise
Traditional e-commerce was built for human eyes. Agentic-powered commerce however operates on a different level, as contextual rather than visual. It weighs price, ethics, sustainability, social proof, personal values, aesthetics, and lifecycle impact in milliseconds.
AI agents that thrive won’t just deliver what the data predicts, potentially creating a depersonalized experience, they’ll also bring moments of discovery like a personal stylist who spots potential items a person will like but hasn’t seen yet or is from a new challenger brand. The goal is AI that can forecast with precision and still leave room to surprise.
What retail leaders must understand going into 2026
The brands best positioned to lead the next phase of retail are going beyond simple digitization and rethinking what truly shapes consumer preference. They see that as AI handles more of the transaction, the real advantage will come from taste, curation, and a deeper understanding of what customers care about.
Human judgement is and still should be at the heart of great retail, and the emotional, social and status-led motivations behind shopping continue to matter. The shift now is that retailers can match this level of personal relevance at scale.
But here’s the insight retail leaders need most – retailers focused only on driving purchases will lose to those who focus on aligning with a customer’s identity.
The retailers who can embrace this new era of Algorithmic Intimacy will be the ones who stay relevant as customer preference becomes more personal, contextual, and identity driven.
Cathal McCarthy
Cathal McCarthy is Chief Strategy Officer at Kore.ai, a leader in enterprise AI with over a decade of experience in helping large enterprises realize business value through the safe and responsible use of AI. It provides comprehensive offerings for AI work, process automation and customer service use cases, built on an AI agent platform with no-code and pro-code tools for custom development and deployment at enterprise scale. Kore.ai takes an agnostic approach to models, data, cloud and applications used, giving customers freedom of choice.