Agentic Commerce Is Redefining the Future of Shopping

Agentic commerce, also abbreviated as “a-commerce,” represents the next practical application of artificial intelligence in retail. Rather than consumers browsing websites or apps to find and purchase products, AI agents, pieces of software programmed with specific parameters around price, quality and preferences, handle the discovery, comparison and transaction on their behalf.

The Third Wave of Shopping

To understand agentic commerce, it helps to situate it within the broader evolution of retail. The first wave was bricks-and-mortar stores. The second wave was internet-based shopping, first on desktop computers and then on mobile devices, a shift that the iPhone fundamentally enabled. The third wave, according to industry observers, is agentic commerce: getting AI agents to handle shopping tasks autonomously.

The logic is straightforward. Consumption accounts for approximately 70% of GDP in economies like the United States and the United Kingdom, making shopping an obvious vertical for the monetisation of AI. If AI tools like ChatGPT, Claude and Gemini have become familiar to hundreds of millions of users, the next logical step is to extend their capabilities from answering questions to completing transactions.

The Market Opportunity

The scale of the agentic commerce opportunity, as projected by multiple research firms, is substantial.

Juniper Research estimates that the total agentic commerce transaction value could grow from $8 billion in 2026 to $3.5 trillion by 2031, an increase of 43,240 percent. The same firm projects that the market will reach 1.3 billion users by 2031, up from approximately 300 million in 2026.

Other forecasts vary in methodology but point in the same direction. Research and Markets estimated the global agentic commerce market at $5.71 billion in 2025, projecting it to reach $65.47 billion by 2033 at a compound annual growth rate of 35.7 percent. Bain & Company forecasts that the US market alone could be worth $300 billion to $500 billion by 2030, representing 15 to 25 percent of total e-commerce sales.

More ambitious projections suggest global agentic commerce revenue could reach $3 trillion to $5 trillion by 2030. The Financial Times, in a January 2026 analysis, described agentic AI as a potential step forward “similar in significance to the start of online shopping in the 1990s or the advent of smartphones in the 2000s”.

The Trust Gap

Despite the market enthusiasm, a significant gap exists between consumer interest in AI-assisted shopping and consumer willingness to delegate actual purchases.

A Q1 2026 survey found that while 61.5 percent of consumers have used AI tools for product discovery and recommendations, 55 percent are not comfortable with AI agents making purchases on their behalf. Another study found that 53.9 percent of consumers believe AI could increase the risk of online fraud.

The tension, as one industry observer explained, is rooted in human psychology. “We as humans are lazy, but we’re also fearful of change,” Alex Gunz, a fund manager at Heptagon Capital, noted in a July 2026 podcast interview. The promise of agentic commerce is the removal of complexity, the ability to delegate mundane tasks like grocery shopping, concert ticket purchases or holiday planning to an AI. The catch is that the technology is new, unproven and requires handing over personal financial details to a piece of software.

This trust gap has practical consequences. One analysis noted that “the trust factor has not yet been fully met for the stages of the agentic lifecycle, delaying market adoption of a customer-facing agentic-driven business model”. Research has found that one in four consumers say they will never delegate purchases to AI and 27 percent trust no organisation to operate an AI shopping agent.

The Impact on Brands

The rise of agentic commerce could fundamentally shift the dynamics of brand power. Traditional consumer behaviour is driven by brand affinity, social influence and emotional attachment, what economists might call irrational decision-making.

AI agents, by contrast, are not programmed to be irrational. They search for the best deal based on the parameters they are given, without brand loyalty or emotional bias. An agent will not prefer Nike over Adidas simply because it likes the brand; it will evaluate products based on price, quality and fulfilment reliability.

This has significant implications. As one observer put it, power may shift away from branding and consumer attention and more towards pricing transparency, data quality and fulfilment reliability. In an agentic world, the ability to fulfil orders quickly and seamlessly becomes more important than brand marketing.

The potential losers could be companies that have sought to differentiate themselves primarily through brand, including apparel, luxury and food and beverage businesses. Meanwhile, winners could include the providers of the underlying infrastructure: payment processors, distribution networks and logistics companies.

The Infrastructure Race

Payment companies, including major card networks and financial technology firms, are positioning themselves aggressively in the agentic commerce space. The logic is straightforward: if agentic commerce requires new protocols for verifying agents, authorising payments and processing transactions, the companies that already provide the “rails” for financial transactions are well-positioned to extend their role.

In June 2026, a major global payments provider launched a service designed to enable agentic transactions to be permissioned, orchestrated and settled at machine speed across its payments network. Around the same period, another leading payments technology company introduced tools to help merchants integrate agentic commerce capabilities into their platforms. In July 2026, a live agentic payment proof of concept was completed involving a global payment processor, a merchant technology provider,and a fashion brand, demonstrating the potential for AI agents to complete transactions autonomously.

Other companies are focusing on the trust and verification layer required for agentic commerce to scale. New solutions are emerging to help merchants verify AI agents and ensure secure transactions, addressing a key challenge: agentic commerce only works if businesses can confidently understand who they are transacting with and if AI agents can pay as reliably as human customers. The rise of AI merchant impersonation scams, where fraudulent websites mimic legitimate retailers to deceive AI shopping agents, has further highlighted the need for robust identity verification and trust frameworks.

China’s Lead

Several industry observers have noted that China is ahead of the United States in practical adoption of agentic commerce. The reasons are structural and cultural.

China has less legacy infrastructure and a greater trust in automation. The country’s “super apps” that integrate shopping, transportation, banking and other services into a single ecosystem have already accustomed consumers to having their personal and financial information integrated across multiple functions. This makes the conceptual leap to delegating purchases to AI agents psychologically and structurally easier.

As one analysis noted, “China has always been a little bit more advanced digitally” with a tacit acceptance that certain liberties may be exchanged for economic growth.

The Timeline Question

Despite the excitement, industry observers caution that adoption will take time. Even today, 25 years after the internet became mainstream, only about 30 percent of all purchases by value in the United States and Western Europe are conducted online.

“Revolutions take time,” one observer noted. Agentic commerce will change the world “in a massive way,” but the timeline is likely measured in years rather than months. Adoption is expected to scale unevenly, starting with low-risk, repeatable categories before expanding further.

Current implementations of agentic commerce remain in an experimental phase. Some retailers have reported that in-chat checkout has performed worse than traditional channels, one major retailer reportedly measured conversion three times worse inside ChatGPT than on its own site. Existing AI shopping assistants are often described as “enhanced shopping assistants” that can curate lists but still require the human to click to complete the payment.

Conclusion

Agentic commerce represents a significant potential shift in how shopping is conducted, a move from consumers doing the work of searching, comparing and purchasing to delegating those tasks to AI agents. The market projections are substantial, with forecasts ranging from hundreds of billions to trillions of dollars in transaction value within the next five to ten years.

However, significant barriers remain. Consumer trust is not yet fully established, with a majority of consumers expressing discomfort with delegating actual purchases to AI. The technology is still in its early stages and the infrastructure to support agentic transactions, including verification protocols, payment systems, and fraud prevention, is still being built.

As one industry observer put it: “The things which sound and feel unfamiliar will within five to 10 years be totally normal”. Whether agentic commerce achieves that level of normalcy will depend on whether the technology can earn the trust it requires.

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