AI Set to Drive Over Half of eCommerce Transactions by 2027
A new report finds AI agents could influence more than half of eCommerce transactions by 2027, as enterprises accelerate investment in agentic commerce and autonomous shopping technologies.
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Artificial intelligence is rapidly moving from assisting shoppers to actively participating in the transaction itself. As autonomous agents become capable of discovering, comparing and purchasing products on behalf of consumers and businesses, the foundations of digital commerce are beginning to shift.
Against this backdrop, Logicbroker has released its report, “The State of Agentic Commerce Adoption.” The study surveyed more than 600 enterprise eCommerce leaders and highlights how quickly organisations are preparing for a future where AI agents influence purchasing decisions.
More than 90% of enterprise leaders expect AI agents to influence at least 20% of online orders by 2027, and more than 1 in 3 believe AI could shape more than half of all transactions.
“The conversation around AI in commerce has focused heavily on discovery. Think chatbots, search assistants and product recommendations,” said Omar Qari, CEO of Logicbroker. “But what the data is actually suggesting is that AI is starting to move deeper into the transaction itself.”
“When software agents begin deciding what gets purchased and where it gets sourced from, the structure of digital commerce starts to change.”
Agentic Commerce is Not Just a Retail Phenomenon
The recent research shows that hybrid organisations operating both B2B and B2C models make up the largest share of the market at 45%, nearly double the proportion of pure retail companies (22%).
The finding suggests that the next phase of AI-driven commerce will increasingly involve complex enterprise buying environments alongside traditional consumer transactions.
“Legacy retail organisations that aren’t prepared for AI will feel the disruption first,” added Ed Bradley, Chief Growth Officer at Virtualstock, powered by Logicbroker.
“As AI agents increasingly discover, compare and purchase products autonomously, traditional SEO and paid acquisition channels will face structural pressure and therefore will need new technologies that will help them overcome those challenges.”
Nearly Half Expect Meaningful ROI within a Year
The report analysis found that 95% of enterprises have already deployed at least one AI-driven commerce capability, while nearly half (47%) plan to invest $1 million or more in AI-driven commerce initiatives over the next 12 months.
Within that group, 21% expect to spend more than $5 million.
These investments are also expected to deliver results quickly. According to the report’s findings, three out of four enterprises anticipate a return on investment within 24 months, and nearly half expect returns within the first year.
In parallel, deployment timelines are accelerating. More than half of organisations say they plan to roll out AI-shopping agents within the next six months.
“Longer-term initiatives, including AI-powered supplier management and autonomous reordering, signal the next stage of maturity, where AI will move beyond supporting human decisions to executing transactions independently,” commented Bradley.
At the same time, just 18% of enterprises position themselves as industry leaders pioneering new territory, suggesting most organisations are moving quickly once the value of AI-driven commerce tools has been proven rather than experimenting with entirely new approaches.
“Notably, we also discovered that hesitation at the executive level is minimal. Only 12% cited leadership buy-in as a barrier. This shows us that the primary challenge is not about convincing the C-suite but is instead about connecting systems, improving data quality and solving the integration complexity required to scale agentic commerce,” added Qari.
Enterprise AI Race Isn’t About Who Builds the Best Model
The report analysis found that despite widespread discussion about companies developing proprietary AI models, most enterprises are instead adopting multiple commercial AI platforms simultaneously.
In fact, less than 15% of organisations report building proprietary large language models. Findings also show that enterprises believe the bigger challenge is integration: 4 in 10 respondents report that better integration tools would accelerate AI adoption.
“The enterprise AI race isn’t about who builds the best model. It’s about whether companies can connect multiple AI platforms to the infrastructure that actually powers commerce. In a multi-model market, betting on a single provider is a risk,” concluded Qari.
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