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CEOs and senior business executives expect 21% or more of their revenue to come from machine … [+]
By 2028, an estimated nine billion internet-connected B2B products—also known as Internet of Things devices—will have the potential to become “machine customers,” according to Gartner estimates. Machine customers represent a specialized subset of AI agents—designed specifically to autonomously purchase goods, negotiate transactions and influence commercial decisions.
While AI agents broadly encompass digital assistants, chatbots and automation tools, machine customers are unique in their ability to act as independent economic actors, making purchasing decisions without human intervention. As AI-driven commerce accelerates, businesses must recognize that not all AI agents buy—but all machine customers are AI-powered buyers.
Author and Gartner analyst Don Scheibenreif coined the term in his book When Machines Become Customers, based on years of research, which appears to be reaching a technological tipping point.
“Ten years ago, the focus was IoT. Then in 2018, my co-author Mark Reskino and I realized we had enough research notes for a book. He agreed, and we started writing it. In the course of that, we switched from ‘thing customers’ to ‘machine customers’ because that’s what they were. A machine customer is basically a non-human economic actor that obtains goods or services in exchange for payment,” he explained.
Scheibenreif shared during a Zoom interview that machine customers will be playing an increasingly important role in automated buying decisions in the near future.
Gartner highlights “Phase One” examples such as HP Instant Ink, Amazon Dash Replenishment and … [+]
Automated AI Buyers Will Quickly Come Of Age
Consider the following Gartner data that suggests machine customers are not only coming but are already here:
- By 2030, CEOs and senior business executives expect machine customers to generate at least 21% of their revenue.
- Gartner modeling predicts that by 2030, machine customers will directly influence or participate in $30 trillion worth of purchases.
- Digital revenue fees from machine-customer-based brokerage services will exceed $100 million by 2026 as IoT products start to sell shared services on behalf of their owners.
A significant percentage of surveyed CEOs believe they must start retooling their businesses to accommodate machine customers and AI agents, which will be conducting a large share of purchases on behalf of actual customers by next year.
“There is a general recognition that this is coming. Our recent research found that over 50% of CEOs plan to have a strategy in place within the next two years to deal with machines as being part of the buying or selling process, which was stunning to us. We didn’t realize it was that high,” said Scheibenreif.
Most Businesses Are Not Ready For AI Buyers
Despite the early consensus of CEOs regarding the trillion-dollar machine-customer opportunity, most businesses are simply not equipped to sell to bots—especially marketing departments.
Scheibenreif explains that most marketing activities rely on emotional selling—an ineffective tactic for machine customers, as they lack emotions.
“The traditional tricks that marketers use won’t work on machines, so you have to rethink your entire approach. A brand for a machine will be different than a brand for a human. The machine’s going to care about: Is the product available when I need it? What’s the pricing? What is your environmental record? What is your DEI record? So the machine’s decision-making will be based on different factors, and marketers will have to adjust to that reality,” he said.
How Businesses Can Adapt To Automated AI Buyers
Sirte Pihlaja, one of Europe’s first certified customer experience professionals, has over 25 years of international expertise in customer and employee experience. She recently shifted her focus to machine customers. She’s also a best-selling CX author and was named a top-25 AI Leader to Follow in CX this year. She agrees that marketers need to adapt to maximize the potential of automated bot buyers.
“Marketing teams play a critical role in this transition, as content must be rewritten with machine customers in mind, ensuring that AI-driven agents can find, interpret and act upon information efficiently. Machine customers don’t browse like humans—they scan, analyse and execute decisions instantly. At the bare minimum, businesses should optimize their web pages for AI-based browser agents for an interim period while people learn to trust their agents,” Pihlaja wrote via message exchange.
She added that the biggest challenges to machine customer adoption are not unique to automated AI buyers.
“Companies struggle to leverage AI for customer and employee experience, primarily due to skills gaps and slow AI literacy upskilling efforts. Decision-makers also hesitate between technologies, failing to realize that ensuring rapid adaptation capability is now more essential than choosing the ‘right’ technology at this point,” Pihlaja added.
While the machine customer segment is projected to generate trillions of dollars worth of transactions in the next few years, Pihlaja says the biggest insight might be that automated AI buyers are here to stay.
“The real takeaway is that this is not a passing trend—businesses must start preparing now. The key to success lies in convenience. Customers should be able to buy seamlessly through their digital assistants. This requires redesigning customer journeys to accommodate both human and AI decision-makers, ensuring that products, services and transactions are optimised for machine customers,” she concluded.
