The Synthetic Economy, Explained: When AI Agents Buy From AI Agents, Who Is the Customer?

TL;DR

• What: the “synthetic economy” describes a market where AI agents increasingly search, compare, buy and sell on behalf of people – and often deal with other AI systems.
• Why now: in January 2026, Google introduced the Universal Commerce Protocol, an open standard that lets AI agents check out with merchants; people can buy directly in AI Mode and the Gemini app.
• The shift: past technologies took over physical work, calculation and memory. Generative AI is the first to take over parts of thinking: analysis, writing and judgment.
• The risk: people already over-trust screens – from navigation errors to “selfie-driven” cosmetic surgery – and 72% of US teens have used AI companions.
• What it means: trust, reputation and human intent become the scarce resources; marketing increasingly has to persuade agents, not only people.

Contents

1. What the synthetic economy is
2. Who the customer is when agents buy
3. From delegating muscle to delegating thinking
4. Digital-first thinking
5. AI companions and synthetic relationships
6. What changes for businesses and marketers
7. Vyara’s take

Recommendation systems already shape much of what people choose. According to two Netflix executives, about 80% of the hours streamed on Netflix come from recommendations. AI agents extend that logic from what we watch to what we buy, book and decide.

What the synthetic economy is

Classical economics starts with people: people build businesses and sell to other people. The software era added a layer – people built software and sold it to people.

The term “synthetic economy” describes the next step: AI systems create offers, AI agents evaluate them, and AI agents complete transactions for people. In this model, identity, trust and even memory become partly synthetic – stored in, and judged by, machines.

Who the customer is when agents buy

A typical example is travel. A person asks an AI agent to plan a trip. The agent queries a booking platform’s AI, which in turn communicates with a hotel’s systems. Three automated layers act so that one human gets one booking.

The infrastructure for this is arriving:

For more on how agents pay, see our explainer on Cloudflare Wallets and AI agent payments.

This raises a practical question for every business: is the customer the person, or the agent that shortlists, compares and buys for them?

From delegating muscle to delegating thinking

One way to read the history of technology is as a sequence of things humans stopped doing themselves:

1. Tasks, to other people – the emergence of professions.
2. Physical strength, to machines – steam engines, motors and factories.
3. Calculation, to computers.
4. Memory, to the internet – looking things up instead of remembering them.
5. Thinking, to AI – analysis, writing, comparison and judgment.

The fifth step is different in kind. Earlier technologies repeated an action; generative AI takes over parts of intellectual work. Some commentators describe the result as a crisis of expertise: when knowledge is almost free, what remains valuable? A common answer is trust – reputation, authenticity and the credibility other people assign to you.

Digital-first thinking

“Digital-first thinking” describes the habit of treating the digital representation of reality as the authoritative one.

• Navigation. A CHI 2017 study analyzed 158 catastrophic incidents linked to personal navigation technologies, including 52 deaths. Missing or incorrect road data was implicated in about 53% of the coded incidents.
• Appearance. In the 2022 annual survey of the American Academy of Facial Plastic and Reconstructive Surgery, 79% of facial plastic surgeons said the wish to look better in selfies continues to trend upward.

As AI agents begin filtering news, recommendations, relationships and risks, the same pattern may extend to everyday decisions: people could experience reality through an “AI layer” that interprets it for them first.

AI companions and synthetic relationships

People already form parasocial relationships with creators and public figures they have never met. AI companions add a new layer.

According to a Common Sense Media survey published in July 2025:

• 72% of US teens have used AI companions at least once;
• about one in three find these conversations as satisfying as, or more satisfying than, conversations with real-life friends;
• about one in three users have discussed serious matters with AI instead of real people.

What changes for businesses and marketers

• Optimize for agents as well as people. Clear product data, prices, availability and structured data help agents understand and compare offers.
• Invest in trust signals. If agents decide whom to recommend, reputation, consistent information and credible third-party mentions matter more.
• Expect funnels to compress. When an agent completes discovery, comparison and checkout, many traditional touchpoints disappear.
• Keep humans in the loop on purpose. Teams increasingly act as “orchestrators” who set goals for agents. Defining good goals – and good intent – becomes a core skill.

Vyara’s take

“If we delegate execution, judgment and choice, maybe the only thing left to humans is intent. That makes good intentions the most important thing in the economy. And maybe being human means something machines are built to avoid: consciously choosing to be inefficient, just to live.”

Further reading: If AI does everything, what’s left for humans? – Vyara Stefcheva’s personal essay on stefcheva.com.

Sources: Netflix Recommender System, ACM · Google Developers Blog on the Universal Commerce Protocol · Monks on Google Marketing Live 2026 · CHI 2017 study on navigation incidents · AAFPRS trends in facial plastic surgery · Common Sense Media survey on AI companions

About the Author

Vyara Stefcheva

Vyara Stefcheva is the founder and editor of Egorithms and an independent marketing expert. She follows how technology, AI and algorithms change the way people find, choose and buy, and writes about what that means for businesses and for the people who use them.

She has spent her career building marketing and business strategies for more than 300 brands across three continents. She built and exited a marketing agency and now works independently. She has taught more than 20,000 people through lectures, courses and corporate training, and speaks at conferences about AI and the future of the internet.

On her YouTube channel she tests new AI and marketing tools as they launch and gives each an independent verdict: adopt, watch or ignore.

See author's posts