What is agentic commerce? The 2026 introductory guide

Over the last decade, ecommerce has largely followed the same pattern: consumers search, browse, compare options, and make a purchase. Whether someone was shopping on Amazon, booking a trip, or ordering groceries, the consumer shouldered the burden of research and decision-making. 

Agentic commerce changes that. Now, consumers utilize agents to evaluate options, compare tradeoffs, consider recommendations, and—in some cases—complete purchases on their behalf.

In the midst of this technological evolution, we’ve already seen how shifting consumer behavior inevitably impacts business strategy. Entire industries must now rethink how to create a valuable customer experience when AI becomes part of the buying journey itself.

In this guide, we’ll break down what agentic commerce is, how it works, why it’s gaining momentum, and what both consumers and businesses should expect next. And specifically for our industry, we’ll explore how agentic commerce impacts commerce media.

What is agentic commerce?

Agentic commerce is the application of AI agents to buying, selling, and monetization, where AI systems actively participate in product discovery, evaluation, recommendations, and even purchasing decisions.

In this case, AI goes beyond merely surfacing products and instead actively participates in consumer decisions. Rather than consumers manually researching products, comparing alternatives, and weighing the pros and cons on their own, AI agents increasingly perform these tasks for them.

Because agents assume the work of searching and browsing, consumers spend their time deciding what to purchase and when. Businesses, in turn, must create an entirely new shopping experience where products aren’t optimized for visibility, but for consideration and recommendation within AI-driven decision systems. 

Why is everyone talking about agentic commerce?

Agentic commerce isn’t entirely new. Recommendation engines, personalized shopping experiences, automated replenishment services, and conversational assistants have existed for years.

However, due to the rapid advancement of large language models and AI agents, platforms like ChatGPT, Gemini, Perplexity, Claude, and others have transformed consumer expectations around information (and now product) discovery. Rather than searching through pages of links, or pages of search results, consumers can now ask complex questions and receive personalized answers in seconds.

The shopping journey becomes conversational rather than navigational. Across commerce companies, from travel to fintech to retail, it forces significant changes within their tech stack, operations, go-to-market strategy, and more. Specifically, it means things like including adopting UCP and ACP-ready infrastructure within their platforms today.

How does agentic commerce work?

At a high level, agentic commerce shifts consumers from browsing to goal-setting.

Traditional ecommerce often looks like this:

Search → Browse → Compare → Purchase

Agentic commerce increasingly looks like this:

Goal → Conversation → Recommendation → Purchase

What this means specifically for commerce is instead of searching: “Best running shoes under $150,” a consumer can now ask: “I’m training for my first marathon, have flat feet, and need a durable running shoe under $150. What should I buy?”

Previously, the consumer had to sort through perhaps hundreds of results, ideally organized and optimized to show the most relevant listings first. But comparing these online was a challenge, and knowing with certainty which shoe was ideal for their specific needs was difficult, requiring reading product descriptions and reviews. Now, the AI agent can take the grunt work off their plate:

• Researching options
• Comparing products
• Evaluating tradeoffs
• Explaining recommendations
• Potentially facilitating a purchase

Instead of manually navigating dozens of product pages, consumers describe what they want, and AI systems help them to determine the best path forward. 

And this works across industries, for example, in travel, someone might say: “Plan a four-day trip to Austin for under $1,500. I’ll bring my spouse, and we’re looking for an outdoorsy trip that balances rest with a few activities each day.”

An AI agent could:

• Compare flights
• Evaluate hotel options
• Recommend restaurants
• Build an itinerary
• Complete bookings

As consumers receive these tailored recommendations without sorting through hundreds of product listings, commerce companies can provide new value to consumers and their brands alike.

Agentic shopping vs. agentic purchasing

One of the biggest misconceptions about agentic commerce is that consumers want AI to purchase products entirely on their behalf. The research suggests otherwise, as consumers are far more comfortable with agentic shopping than agentic purchasing. The difference looks like:

Agentic shopping

Agentic shopping involves AI helping consumers:

• Research products
• Discover options
• Compare alternatives
• Evaluate tradeoffs
• Surface recommendations

Agentic purchasing

Agentic purchasing involves AI:

• Selecting products
• Making final decisions
• Executing transactions
• Completing purchases autonomously

This distinction is important because consumer comfort drops significantly when AI moves from helping to deciding. This sentiment spans across the globe with 72% of consumers in the UK, Germany, and US saying they want AI to be a “co-pilot, not a full autopilot.”

Consumers are generally comfortable allowing AI to:

• Save time
• Surface better deals
• Recommend products
• Simplify research

But they remain much more cautious about giving AI full control over purchases, particularly in high-stakes categories such as healthcare, banking, insurance, and investments.

Commerce companies, then, need to focus on the near-term opportunity of simply creating better shopping experiences.

The three waves of agentic commerce

We see agentic commerce evolving in three ways:

Wave 1: AI within existing systems

In the first wave, AI is embedded within existing shopping and advertising experiences. Most businesses are already working like this today, with tools like:

• Recommendation engines
• Personalized search results
• Automated bidding and targeting
• Product ranking optimization
• Dynamic merchandising

In Wave 1, AI improves performance but does not fundamentally change how decisions are made or how value is captured.

Wave 2: Agentic decisioning

The second wave is where much of the market sits today. AI begins actively participating in decision-making by helping consumers:

• Search
• Compare products
• Filter options
• Evaluate tradeoffs
• Consider recommendations

In Wave 2, AI moves beyond optimization and into influence.

Wave 3: Orchestration and system-level monetization

The third wave is when AI moves from supporting decisions to orchestrating them across platforms, retailers, networks, and services.

Businesses increasingly coordinate data, inventory, recommendations, fulfillment, and measurement to deliver better outcomes.

Accordingly, for commerce media networks in particular, monetization begins shifting toward access, influence, and outcomes rather than simply impressions and clicks. We anticipate many organizations will make this transition toward orchestration to accelerate over the next 12–18 months.

What consumers think about agentic commerce

While consumers are not rejecting AI, they are setting boundaries around when and how they’d like it to be used. The dominant consumer mindset is one of conditional acceptance, where consumers are willing to delegate research, filtering, comparisons, and recommendations. They are less willing to delegate commitment, payment, and irreversible decisions.

When asked about the benefits they want from AI agents, consumers prioritized:

• Saving money
• Discovering better options
• Saving time

Interestingly, reducing stress and decision fatigue ranked much lower. Consumers are primarily looking for practical improvements rather than a complete reimagining of commerce.

But trust also plays a significant role. Consumers want and expect safeguards, including:

• Secure handling of personal data
• Human review for high-value decisions
• The ability to undo or change decisions

Trust is not automatic and must be earned through transparency, control, and accountability.

The biggest opportunities in agentic commerce

While the opportunity for consumers generally is around promoting better experiences and saving time, for businesses, the opportunities are even broader. Organizations that successfully adapt may benefit from:

• Increased conversion rates
• Better customer experiences
• Stronger personalization
• New monetization models
• More efficient customer acquisition

Agentic commerce has the potential to create entirely new ways for businesses to connect with consumers at the moment decisions are made.

The future of agentic commerce

As consumers change how they discover and purchase products, commerce will need to meet them with trustworthy, relevant, and seamless experiences. Businesses have more power than ever to influence purchasing decisions, but they need the right infrastructure to do so. 

As the industry transitions from a model based on placements and impressions to one based on access, influence, and outcomes, brands will fight for inclusion within AI searches. To learn more about what it takes to show up and stand out in those searches, view our guide to UCP vs ACP here.