What is agentic commerce?
Agentic commerce is a commercial application of agentic AI—any system, built with Machine Learning algorithms, most often coming in the form of a large language model (LLM), and generative AI tools that assist an individual user with a specific task.
Agentic AI in retail is used across the customer buying journey. It proactively and autonomously fulfills a range of goals, from research and discovery to purchase (this is agentic commerce), to tracking shipments and handling complex returns.
Who is ready to let AI make purchases and why?
Our research shows that the willingness to delegate purchasing power to an AI shopping assistant varies by generation, safeguards, and price thresholds.
In the survey we conducted, we asked the question, “Which of the following would make you more comfortable letting an AI agent purchase an item on your behalf?”
We found that human oversight before a transaction is placed is the main driver. It was the leading preference for 35% of consumers, but it’s particularly important to baby boomers. We found that 44% of them would prefer to sign off before an agentic AI makes a purchase decision. Baby boomers also show a comparatively higher sensitivity to purchasing only from trusted retailers, with 35% demanding this safeguard, compared with 29% of overall respondents.
Do people trust agentic commerce?
Our research, presented in the mini-report “Who’s Buying? Consumer Trust in the Age of Agentic AI,” reveals some startling emerging trends.
Take, for example, the level of trust that users are already placing in agentic AI. In fact, 39% of U.S. shoppers (and 47% of U.S. millennials) say AI understands their purchase needs better than friends and family. And across the surveyed geographies, leading AI tools have a markedly higher trust score than established channels such as newspapers, major media outlets, and social media.
This high level of trust even extends to a meaningful group of consumers who are ready to let AI move from advisor to buyer through autonomous AI purchasing.
How does the removal of safeguards impact AI purchase delegation?
Although our research revealed a subset of super-trusters—consumers who are ready for AI to buy for them, even if returns protection and a seven-day return window are not in place—for most respondents, the removal of these features led to a clear decline in trust.
For instance, removing return protection to delegate purchase control to agentic AI had a markedly stronger effect on older consumers—34% of U.S. millennials remain OK with delegating the purchase without returns protection, compared with 11% of U.S. baby boomers.
When the seven-day return window was removed from the equation, the non-U.S. decline was lower, particularly among millennials, at 27%. Gen Z and Gen X were close behind with 26% and 22%, respectively.
The data indicate that consumers at large are more comfortable using agentic commerce when provided with key safeguards. But the most striking finding for most people surely will be that a surprisingly large number of consumers are willing to trust agentic commerce to such a degree, with or without safeguards. After all, it’s natural that we should be protective of our hard-earned money and how it is spent.
How should retail leaders adapt their agentic commerce strategies?
The fact that the research and discovery phase of the purchase journey is extended by AI creates both challenges and opportunities for brands seeking to gain a foothold in this stage. With an expanded research window, maintaining engagement with retargeting becomes more important. More touchpoints mean more data, much of it widely dispersed and disordered. So brands should seek out advertising partners who have the technology to make sense of and extract insights from a more complex data landscape.
Given the huge potential for AI in ecommerce to surface new brands for consumers (we found that 62% of baby boomers use it for brand discovery), there’s a pressing need to move beyond traditional search rankings and social discovery to increase brand visibility. For LLMs to feature your brand and products, you need clear and detailed information and top-tier digital content.
Moving out of the research window and into the actual delegation of purchasing, AI commerce systems should ensure that approval steps, spending limits, trusted inventory, cancellation options, and clear returns are integrated with full and easy control.
As brands begin to offer such AI-commerce experiences, they should focus on more confident and trusting demographics (such as U.S. millennials) while building out protections and safeguards to reassure more cautious shoppers (baby boomers).
