Your Next Customer Might Be an AI Agent. Is Your Business Ready to Serve It?

For years, businesses have used AI to talk to customers. The next shift runs the other way: customers are starting to send AI to talk to businesses.

Gartner calls them "machine customers," and its research suggests they're closer than they sound. In a survey of 4,879 customers conducted in early 2025, 51% said they would be willing to use a generative AI assistant to handle customer service interactions on their behalf. Meanwhile, Adobe's data shows AI-referred shoppers have gone from converting worse than everyone else to converting better.

The data: AI is already standing between you and your customers

Adobe's April 2026 analysis, based on more than 1 trillion visits to U.S. retail sites, shows how fast this has moved:

• Traffic from AI sources to U.S. retail sites grew 393% year over year in the first quarter of 2026, after rising 693% during the 2025 holiday season.
• 39% of consumers say they've used AI for online shopping, and 85% of them say it improved the experience.
• In March 2026, AI-referred traffic converted 42% better than non-AI traffic. A year earlier, in March 2025, it converted 38% worse.

Adobe's 2026 holiday forecast expects AI traffic to U.S. retail sites to rise another 130% this season, peaking on Thanksgiving at 159% year over year. In Adobe's consumer survey, 77% of people who've used AI for online shopping said they felt more confident in their purchase, and 69% said they were less likely to return it.

Today, most of that traffic is a person asking an assistant and then clicking a link. But the direction is clear: the assistant is doing more of the searching, comparing and deciding, and the person is doing less.

Why machine customers change the economics of service

Gartner's June 2025 analysis flags two problems service teams haven't planned for.

Volume goes up, not down. When an AI assistant can file a complaint, chase a refund or request a price match for almost zero effort, customers will make many more of those requests. Gartner's Brad Fager warned that "widespread adoption of AI assistants by customers poses a cost risk that could undermine any gains made by customer service automation."

You lose the relationship signal. If a machine handles the conversation, a business gets fewer chances to build loyalty and less of the voice-of-the-customer feedback that shapes products. As Gartner puts it, AI assistants "act as both a channel and a customer proxy," and leaders "must adapt to serve both human and AI assistants effectively."

Most websites aren't built for machines yet

The other problem is more basic: much of what businesses publish can't be read by AI. Adobe scored U.S. retail web pages on how much of their content language models can actually read:

• Homepages averaged 75%, so about a quarter of homepage content is invisible to AI.
• Individual product pages scored lowest at 66%.
• Customer service and help center pages averaged 79%, returns and exchanges pages 82%, and FAQ pages 80%.
• The best retailers' homepages scored 82.5%; the weakest scored 54.2%.

If an AI assistant can't read your return policy, it can't confidently recommend you, and it can't resolve a question about you without escalating to a person. For a machine customer, unreadable information is the same as missing information.

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What getting ready looks like

This doesn't require rebuilding the business. It means treating AI assistants as a real customer segment, with a few practical steps:

1. Make the basics machine-readable. Prices, availability, policies, shipping times and support hours should be in clear, structured text, not buried in images or scripts.
2. Plan for higher request volume. If filing a request becomes nearly free for customers, routine requests have to become nearly free for you to handle. That's a job for your own agents.
3. Decide what a machine can do on a customer's behalf. Which actions, such as checking an order status, rebooking or requesting a refund, can an assistant complete, and which need the human customer to confirm?
4. Verify who's acting. Know when you're dealing with an agent and whose authority it's acting under, especially before money moves or account details change.
5. Keep listening. If more conversations happen machine-to-machine, build other ways to hear directly from customers so feedback doesn't dry up.

Agents on both sides of the counter

The likely end state is agents talking to agents: a customer's assistant asks, and a business's agent answers, checks the order system, applies the policy and hands off to a person when judgment is needed. Gartner already expects the business side of that to grow quickly. In a separate March 2025 prediction, it said agentic AI will autonomously resolve 80% of common customer service issues without human intervention by 2029.

The businesses that handle this well will be the ones whose agents are connected to real systems and real rules, not just a chat window bolted onto a help page.

How Workmate approaches this

Serving machine customers well means your own agents need to do more than chat. They need to look up the order, check the policy and take the next step. Workmate builds custom AI agents around a company's existing systems and business rules, and connects them to the apps the team already uses, with custom connectors where needed. Admins control which apps and actions each agent can use, and credentials sit in a secure vault that can require human approval before anything sensitive happens. That's the kind of control you want when the customer on the other side might be a machine.

What this means going forward

Machine customers won't replace human ones. But Adobe's numbers show AI is already shaping which businesses customers find and buy from, and Gartner's research shows half of customers are open to letting AI handle service for them. The cost of being unreadable, or unprepared for a surge of automated requests, will rise each year.

The good news is that the preparation is ordinary work: clean information, clear policies and agents of your own that can keep up.

FAQ

What is a machine customer? An AI assistant or agent that shops, asks questions or makes service requests on behalf of a person or a business.

Is this only a retail issue? No. Retail data is the clearest early signal, but any business that takes bookings, handles service requests or publishes prices and policies online will see AI assistants acting for customers.

What's the first thing to fix? Make sure your key information, including prices, availability, policies and support details, is published as clear text that both people and AI can read.