Agentic Commerce: the Next Evolution of AI-driven Shopping

A new curve is emerging in the artificial intelligence era – one defined by the rising integration of Agentic AI: autonomous systems capable of acting on behalf of shoppers. As these agents begin to embed themselves across the customer journey, they are reshaping how demand is discovered, decisions are made, and purchases are executed.

This isn’t just an evolution of e-commerce. It is a redefinition of shopping itself – where the boundaries between platforms, services, and experiences give way to an integrated, intent-driven flow.  In this new model, highly personalized journeys replace fragmented interactions, delivering faster, more intuitive, and increasingly frictionless outcomes. Leaders who adapt early could gain a significant competitive advantage. Those who do not risk losing visibility and relevance in this next major retail transformation.

Let’s delve deeper into this shift and explore what leaders need to understand and act on to thrive in the era of agentic commerce.

From chaos to coordination: A new shopping paradigm

Traditionally, the online shopping journey was limited by the amount of time shoppers were willing to spend researching their options and keeping track of details.

Agentic commerce changes this dynamic entirely. It does not have such constraints.

AI agents can scan, evaluate, and recommend products across the literal worldwide web in real time. They can: surface relevant options, introduce new brands alongside familiar ones, and help customers make better choices based on their preferences. What was once a reactive, effort-driven process becomes a proactive, orchestrated, and continuous one.

This shift transforms the shopping journey from a series of discrete actions into a coordinated system. One in which intelligent agents anticipate needs, reduce decision fatigue, and deliver outcomes with minimal friction.

Early signals of an agent-driven future

This is not just an incremental change – it’s a structural shift in how commerce operates. As interactions move beyond the human-readable web, AI agents are poised to become the primary interface between consumers and businesses, fundamentally redefining how products and services are discovered and purchased.

The momentum is already visible. According to a McKinsey survey, 44 percent of surveyed users who have tried AI-powered search say agentic AI has become their ‘primary and preferred’ source for internet searching, compared with 31 percent who prefer traditional search.

“Companies have spent decades refining consumer journeys, fine-tuning every click, scroll, and tap. But in the era of agentic commerce, the consumer no longer travels alone. Their digital proxies now navigate the commerce ecosystem, making millions of micro-decisions daily. To thrive, leaders must rethink the full stack of engagement – not for the people they’ve worked to understand but for the agents now acting on their behalf”.

 – says, Becca Coggins, McKinsey senior partner and global leader of the Retail and Consumer Packaged Goods Practices

In many ways, this shift is similar to the rise of e-commerce; however, it’s happening much faster.

Example of agentic commerce 

We’re already seeing the early signs of this shift in platforms like Perplexity’s Shop like a Pro, which delivers personalized product recommendations via backend product APIs. While its ‘Buy with Pro’ feature enables one-click checkout directly in the interface.

Likewise, OpenAI recently announced an Agentic Commerce Protocol, codeveloped with Stripe, which allows users to complete purchases within ChatGPT without leaving the chat. 

Similarly, Shopify is developing an agentic shopping infrastructure that allows agents to tap into its catalog and build carts across merchants. 

Collectively, these moves are turning agentic commerce from a concept to an imminent reality.  

How agentic commerce works: Key interaction models

Agentic commerce is taking shape through three key interaction models:

1. Agent to site: 

Agents interact directly with merchant platforms. For example, a clothing agent scans multiple clothing websites, highlighting those that fit your preferences and confirming your interest before booking the attire.

2. Agent to agent: 

Agents transact autonomously with other agents. For example, a personal-shopping agent communicates with the retailer’s in-house AI commerce agent to secure better pricing, bundle products across categories, or optimize delivery terms – without human intervention.

3. Brokered agent to site: 

Intermediary systems facilitate multi-agent and multi-platform interactions. For example, a travel planning agent could route your trip request through a booking platform, which then coordinates with airline and hotel systems to find the best options, apply available discounts, and finalize your itinerary based on your preferences – all in one seamless flow.

Together, these models signal a shift from isolated transactions to interconnected, intelligent ecosystems.

The implications: Disintermediation and new competitive pressures

For businesses, this transformation introduces both opportunity and risk.

One of the most immediate threats is disintermediation.

As AI agents become the default entry point for commerce, consumers may bypass retailer websites entirely. The rise of zero-click interactions and agent-mediated decisions reduces direct traffic, and with it, visibility into customer behavior.

At the same time, AI agents evaluate options differently than humans. They prioritize objective factors such as price, ratings, delivery speed, and availability, often placing less weight on brand familiarity or emotional loyalty.

This has far-reaching consequences:

• Increased dependence on third-party AI ecosystems for visibility and conversion
• Loss of first-party data that fuels personalization and monetization
• Erosion of traditional consumer loyalty
• Reduced cross-selling opportunities
• Intensified competition on price and fulfillment

In all, the basis of competition is shifting, from brand-driven persuasion to algorithmic relevance.

Agentic commerce era: How can business and tech leaders in retail prevail in this new normal?

To get ahead of the curve, leaders should:

1. Make product data machine-readable

Use structured formats (e.g., JSON-LD), enrich product information/supply chain data, and add natural-language attributes that reflect real shopper intent.

2. Enable real-time syndication and APIs

Product catalogs need to stay updated and accessible wherever agents shop – whether on Perplexity, Google, GPTs, or beyond.

3. Join emerging agentic platforms 

Apply to programs like Shop with Pro to ensure products are represented in agent-led interfaces.

4. Create content for agents as much as people 

Product descriptions, bundles, and reviews should be optimized for algorithmic parsing –  not just human browsing.

5. Rethink attribution and analytics

Track how AI agents influence the buyer journey, even if the shopper never visits the business site directly.

Critical enablers for long-term success

Beyond technology, success in the agentic era will depend on broader organizational shifts:

Hence, leaders should make a note of the following:

Avoid the ‘uncanny valley.’

Agentic AI represents a fundamental shift in how humans interact with technology, redefining user experience and engagement. While these systems have the potential to deliver highly intelligent and autonomous capabilities, their success hinges on user trust.

If AI fails to communicate naturally or oversteps personal boundaries, consumers may be hesitant to engage. To drive meaningful and trusted adoption, leaders must focus on designing or scaling agentic AI that is not only functional but also intuitive, approachable, and respectful.

Prepare the workforce for ‘symbiotic intelligence.’

Leaders will need to reevaluate their talent strategy to upskill and reskill workers as multidisciplinary professionals – who can triangulate across domains.

As companies continue to adopt advanced technology solutions, employees must also recognize that embracing symbiotic intelligence doesn’t just benefit the company – it’s also an investment in their own career growth and long-term relevance.

Forge strong connections with Silicon Valley and other innovation hubs

Leaders should establish a close-knit network with developers, start-ups, and incubator programs in the epicenter of AI innovation. Consider basing teams there to stay at the cutting edge of AI advancements and to maintain a competitive edge in the evolving digital landscape.

Lead with purpose

To lead with purpose means prioritizing people, customers, and community – while driving organizational goals, fostering higher engagement, resilience, and performance. It requires articulating a clear ‘why’ beyond profitability, aligning daily actions with core values, and inspiring others to contribute to a meaningful, long-term vision.

The inflection point: Lead the shift or lose relevance

AI agents aren’t just another wave of digital innovation; they are fundamentally reshaping the retail landscape. While almost all global retailers are exploring agentic commerce, they are not moving fast enough. Those who move now by investing in agentic capabilities and building AI-native experiences will define the next era of customer engagement, brand relevance, and operational efficiency. Those who wait risk becoming invisible, disintermediated from the customers they once knew.

And history offers a clear warning. In the early days of e-commerce, many who lagged found themselves left behind or even out of business. The same inflection point is emerging again. The imperative for leaders is clear: rethink existing models, embrace structural change, and act decisively – or risk repeating the mistakes of the past.

The window to lead is rapidly closing, but for those bold enough to act, the upside is transformative.

“This is not a wait-and-see moment. Before long, nearly all retailers will have to grapple with the fact that a significant percentage of their customers will not be human users but rather AI agents. The challenge will be to get out in front of it now, before your rivals do. The companies that move first, even in small ways, will be the ones that help shape the future”.

says Lareina Yee, senior partner, director of technology research at the McKinsey Global Institute, and cohead of global ecosystems and alliances

In brief:

In the agentic AI era, leaders must be willing to disrupt their own processes and models to stay ahead. Because, in a world where agents control access to demand, success will no longer be defined by who reaches the customer first, but by who the agent chooses.

Of course, there will be nuances. However, with the right steps, leaders can stay relevant in the marketplace.