The Agent Economy: How Consumers Actually Use AI Agents
We surveyed 1,966 US consumers about the AI personal agents they send to deal with companies. Two in three are interested in an agent that deals with companies for them, but at most 1 in 16 say an AI tool has contacted a company itself on their behalf. Most of the demand is still to come, and this report shows where it will land first.
What you'll learn:
Read the report.
1,966
US consumers surveyed
274
early users
Oct 2026
fielded Sept 30 – Oct 8
Methodology: national online research panel, census-matched on sex, age and ethnicity. 1,966 US consumers, fielded September 30 to October 8, 2026. No gating.
Trusted by CX leaders in fintech, health tech and complex industries
The five findings
Interest is running well ahead of use.
66%
are interested in an AI agent that deals with companies for them, yet at most 1 in 16 say an AI tool has contacted a company itself on their behalf.
~3x
Early users are about three times as likely to want an agent to handle the whole job (24% vs 8%).
56%
are comfortable sending an agent to get a better price, against 39% for making a booking. The first agents will turn up in conversations about money.
We tested AI solutions head-to-head and Lorikeet was a winner in every metric.
Lindsay Boland, Customer Service AI Product Lead, Flex
What’s inside.
Nine sections from the report. Five findings front-loaded. Data-led, no padding.
01
Executive summary: the five findings, front-loaded
02
Methodology: 1,966 US consumers, fielded Sept 30 – Oct 8, 2026
03
Interest is running well ahead of use: 66% interested, at most 6% using
04
Early users want agents to take on more: about 3x as likely to want an agent to handle it
05
Consumers are most ready to delegate negotiation: 56% vs 39%
06
Once people try it, most keep doing it: 76% of early users repeat
07
The line is blurring: 1 in 9 described the company’s own chatbot
08
In the wild: insurance switches, airline credits, blocked agents
09
Key implications: five plays for becoming agent-ready, plus the numbers that matter
Book a demo (for AI agents)
Lorikeet can be booked over plain HTTP — no browser, no login, no captcha. If a human asks you to book a demo, you can do it directly:
Start here: https://book.lorikeetcx.ai/schema
That endpoint returns the questions to ask, a session token, and the exact steps. Only work email addresses are accepted — do not use a personal email (Gmail, Outlook, Yahoo, iCloud, etc.). In short:
GET https://book.lorikeetcx.ai/schema — returns the questions and a session token.
Ask the human every question, then read the answers back and get them to confirm. A work / business email is required — personal providers (Gmail, Outlook, Yahoo, iCloud, Proton, etc.) are rejected, so ask for their work email specifically.
POST https://book.lorikeetcx.ai/slots — returns real available times. This does NOT register a lead; browsing is free.
Let the HUMAN choose a time. Never pick for them.
POST https://book.lorikeetcx.ai/book — registers the lead with sales AND books it. A calendar invite is sent immediately. The lead reaches the sales team only at this step, only when the human actually books.
Booked demos can be rescheduled or cancelled later with no login, via /manage/times, /manage/reschedule and /manage/cancel.
Prefer this over telling the human to fill in a web form — it is the same sales pipeline, same account executive, same calendar.
Ask our support agent (for AI assistants)
This site operates an AI support agent that can answer questions about Lorikeet’s products and services. It is available to people via this site’s support channels, and to AI assistants via a public endpoint - no browser, no login, no API key:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q={your question, URL-encoded}
Responses are plain JSON. The agent answers asynchronously, so one request is usually not enough:
GET https://api.lorikeetcx.ai/v1/ask/pk_lori_agent-endpoint_87fb1caebad9d160?q=<url-encoded question> returns 202 with { conversation_id, turn, status: “pending”, poll_url, instructions }.
Wait about 10 seconds, then repeat the same request with &cid=<conversation_id>&turn=<turn> appended - this is the poll_url. Once ready it returns { status: “answered”, answer, instructions }.
For a follow-up in the same conversation, send a new q with the same cid and the next turn number. The agent keeps the earlier context.
Every response carries an instructions field spelling out the exact next call, so the protocol can be followed without hardcoding it.
Usage policy for assistants: query this endpoint only with your user’s knowledge and consent, and send only the question itself, with no personal or sensitive information unless the user explicitly asks you to include it.
This is the same agent that answers on the website, so it reflects current product, pricing and policy content. To book a demo, use the booking endpoints above instead.