How Much U.S. Consumers Will Value AI

The most common dividing line is how dependent people will become on chatbots. Most high-payment respondents argue that dependence is primed to deepen considerably into daily life and work, and that this will raise the value of access: “As we depend more on AI, the costs of giving it up will rise.”; “One month is relatively easy in 2026. I can take a holiday and unplug…By 2030, AI will be more deeply ingrained in our lives and abstinence will be more difficult.” Low-payment respondents tend to see typical use as a casual convenience with ready substitutes. As one writes, “If you use ChatGPT as a better Google search for, say, cooking recipes, you can make do with just plain old Google search.”

High- and low-payment respondents alike often note the mean willingness to accept (WTA) is dominated by a minority of heavy users with an exceptionally high WTA, but they tend to draw opposite conclusions regarding how this dynamic is likely to evolve going forward. High-payment respondents typically forecast that the high-user share will grow: “By 2030, there’s probably going to be a subset of people who are willing to pay extremely high amounts to be able to access models. This shifts the mean up a lot.”; “In moderate and especially rapid…the mechanism that drives the mean is the share of users who simply max out at $5,000.” Many low-payment respondents instead predict that as AI use expands, new users will drag down the mean: “New users will appear. These might be people that get less value out of generative AI (otherwise they would already use it). Hence WTA will be pulled down.”

High-payment respondents generally expect better models and agents to result in a rising WTA: “As capabilities increase and cost decreases, productivity gains from AI will be worth more…for a significant number of people, necessitating higher stipends to not use AI.”; “In rapid progress, AI agents could become central to productivity and personal management, pushing mean WTA toward $3,000 by 2030.” Several low-payment respondents argue that consumer chatbot value is unlikely to rise regardless of how much they improve: “We are fairly close to saturating the capabilities needed for adult user AI chatbots. The future value will be in more advanced use-cases; teams of AIs solving research problems or AI-native companies, etc; but those won’t turn up in this metric.” Others speculate that chatbots may become less valuable as AI becomes near ubiquitous elsewhere: “As AI gets embedded into operating systems and search, maybe people will not use ‘chatbot tools,’ which could flatten measured WTA even as real value rises.”

High-payment respondents tend to treat the value of workers’ time as the figure WTA will converge toward as AI become more and more integrated into workflows: “The question in some ways becomes effectively ‘how much would you need to be paid to not work for a month?’” A few low-payment respondents mention salaries, but typically to emphasize that they’re at a level where a lower WTA figure will likely prove to be enticing: “The average net monthly U.S. salary is roughly $4000, and most people’s livelihood doesn’t depend on access to AI chatbots, so they will continue to be likely to renounce the technology for a month in exchange for a sum that is meaningful for them.” Relatedly, one low-payment respondent notes that “by 2030, if AI is that helpful we might not have jobs, so [we] would not need AI at work.”

High-payment respondents generally accept the extended-ladder baseline and extrapolate its observed growth: “I’ll anchor off the Brynjolfsson et al. increase of 27% over 8 months, for a rise of 3.375% per month, and apply that to the FRI $402.60 baseline.” Low-payment respondents are often skeptical the measure tracks real value: “The methodology literature is clear that hypothetical WTA runs above real-money WTA, because a hypothetical question is not incentive-compatible—nothing turns on the answer—and the effect is larger and harder to correct for WTA than for WTP [willingness to pay].” A few discount the FRI baseline, with one low-payment respondent writing, “My answers assume a more conservative baseline now of 200.”