A consumer shift toward agentic AI in shopping is imminent
We’re standing at the edge of another fundamental shift in consumer behavior. AI is moving from the background to the frontlines of digital commerce. It’s not just about automation anymore, shoppers now expect AI to handle part of the buying process for them. That’s backed by real numbers. According to Kearney’s 2024 report, 73% of consumers already know how to use AI tools, and 60% expect to actively use agentic AI to shop in the next 12 months.
Agentic AI acts. These systems can scan across platforms, analyze deals, match specifications to consumer preferences, and make recommendations, or even real-time purchases, without constant human oversight. They represent a leap beyond scripted chatbots or smart recommendations. For C-suite leaders, the signal is clear: consumer expectations have moved faster than many retail digital strategies. It’s time to catch up or get left behind.
If you’re still betting on loyalty built through traditional marketing alone, this shift threatens that model. Consumers are looking for faster, smarter decisions, and they’re trusting AI to deliver. The relationship with the customer is evolving, and your ability to influence buying behavior now depends on how well you integrate with these decision-making systems.
This also means your product isn’t just being evaluated by your target customer anymore, it’s getting filtered through machine logic, driven by trained algorithms that don’t respond to brand messages or discounts in the same way people do. Your pricing models, fulfillment, product metadata, and customer experience workflows need to be optimized for both humans and agents.
And here’s the strategic point: while this seems like a disruption, it’s actually an advantage for those who move fast. C-suite executives who act early on agentic AI can define new customer interfaces, drive transaction efficiency, and operate closer to where decisions are really being made.
The future of shopping isn’t just digital. It’s autonomous.
Retailers face risk of losing control over customer relationships due to the rise of cross-platform AI “super-agents”
Retailers are losing direct access to their customers. Not gradually, suddenly. Cross-platform AI agents are starting to shape how people find, choose, and buy products. These agents operate outside of any one brand’s ecosystem. They don’t care about who built the app or how polished the front-end storefront looks. All they care about is what gives their users the best value.
That’s a problem for companies used to controlling the buying experience. In the agentic commerce model outlined by Kearney, these “super-agents” aren’t tied to a single retail platform. They pull data from across the internet, price, specs, reviews, availability, and then recommend whatever gives the strongest match. These bots remove friction, but they also remove the brand’s ability to frame the decision.
If controlling the customer journey has been your competitive advantage, you’ll need to rethink it. These bots don’t care about atmosphere or storytelling. They will take customers anywhere if the product is a better fit. Loyalty, in their world, is entirely performance-based. That means your features, pricing accuracy, and data visibility need to outperform, not just your competition’s offering, but their ability to show up on the bot’s radar.
From a business strategy standpoint, power has shifted to whoever feeds better data to the algorithms. If your systems can’t communicate product specs, availability, shipping time, and user satisfaction signals instantly and with accuracy, you’re already losing relevance. The agent won’t “suggest” your product, it will simply ignore it and move on.
The way forward is clear. You either wait for these super-agents to commoditize your offering, or you build alignment with them, through platform partnerships, proprietary agent strategies, and back-end infrastructure built to rank high in their decision-making process. Control doesn’t need to be lost, but it has to be re-earned by competing on the terms these AI systems respect: machine-readable quality, performance transparency, and total data clarity.
Agentic commerce is challenging traditional brand loyalty by shifting decision-making authority from consumers to AI bots
Brand loyalty doesn’t mean what it used to. In a world shaped by agentic AI, purchase decisions are increasingly being made by bots, not by the humans your marketing team spent years trying to build a connection with. These bots don’t “prefer” brands. They run logic. They optimize. They cut through emotion and evaluate based on specs, price, user satisfaction, reviews, warranty, delivery options, whichever parameter has the most weight in the model.
According to Kearney’s report, this is not about an incremental change. This is a structural reset in how value is assessed and how choices are made. If your core business value relied on familiarity, storytelling, or positioning, those have limited weight when the decision engine is code, not instinct.
It’s not that brand is dead, it’s that its influence is indirect now. Agents don’t show preference unless there’s measurable benefit. That shifts your strategy. Your product pages, logistics capabilities, transparency of inventory, and accuracy of customer satisfaction signals now outperform traditional brand-building in terms of conversion. You need structured clarity across all consumer touchpoints that matters to automated systems as much as people.
For C-suite executives, this demands a dual-track mindset: build for humans, but optimize for machines. Your pricing strategy needs to be consistently competitive, not just during campaign peaks. Your fulfillment KPIs need to be accessible to APIs, not just dashboards. The cleaner your product data, the more likely your offer will surface. The days of relying on brand loyalty alone to drive repeat purchases are shrinking.
This shift also requires re-engineering loyalty mechanisms. Bots won’t respond to emotional affinity, but they will recognize recurring value. Loyalty now becomes a data-driven construct. It’s less about what people remember and more about how your backend performance improves outcomes for every purchase. That’s the loyalty AI agents reward, efficiency, accuracy, and sustained alignment with logic-based priorities across multiple evaluations.
Traditional brand equity still retains value, but its role in the purchase path has been downgraded. If your organization hasn’t updated how it earns influence in a world where bots make choices, it’s not just behind, it’s invisible.
Key executive takeaways
- AI-driven shopping demand is accelerating: 60% of consumers expect to use AI agents for purchases within 12 months. Leaders should prioritize integrating agentic AI capabilities to meet rising demand and avoid falling behind customer expectations.
- Cross-platform AI agents reduce retailer control: As “super-agents” pull data from multiple platforms, brand influence weakens. Executives must invest in backend infrastructure, real-time data accuracy, and platform interoperability to remain visible in AI-driven purchase flows.
- Brand loyalty is losing ground to logic-based AI decisions: Bots are replacing emotional brand connections with algorithmic choices based on performance, price, and availability. Retail strategies must shift toward data transparency and optimized product feeds to stay competitive in AI-filtered decisions.
