Consumer AI is young enough that market positions are still fluid. The leading providers are spending heavily on models and computing capacity, and the subscription revenue that helps pay for it comes from the roughly one in four AI users who pay for a tool. Every few months a provider releases a model that does some tasks better than its rivals, and anyone can try it within minutes. There is no contract to end and no number to port. Whether people actually move when a better tool appears, measured here as AI tool switching, shows which providers are building the habits and the spending that will be hard to dislodge once the market settles.

The question also tests a strategic bet. Companies that already own a screen or a speaker in the home have built an assistant into it, betting that distribution will decide this market. Standalone AI tools are betting that people will go looking for a better product. Where switchers land, and the reasons they give, is the most direct evidence of which bet is paying off. 

Measuring it takes care, because AI tool switching works differently from switching in the subscription businesses it is usually compared with. A wireless customer who ports a number leaves one carrier for another, and a household that cancels a streaming service loses its shows. Most AI users never face that choice, because they already use more than one tool. Among the AI users Recon Analytics surveyed in the 13 weeks to September 18, 2026, 62% had tried two or more AI tools, 52% named a second tool they use regularly and 29% named a third. Someone can draft in Claude, look things up in Gemini and keep ChatGPT open for everything else. Adding a tool costs little and dropping one is rarely necessary, so a count of a product’s users says little about whether it is gaining ground. 

Two positions in that rotation still carry weight. One is the primary tool, the one a person reaches for first and uses most. The other is the subscription, and the two travel together. Of AI users who pay for any AI tool, 87% pay for their primary; only 13% pay solely for a second or third tool. Paying rates also fall down the list: 22% of AI users pay for their primary tool, against 9% of second-tool users who pay for that tool. When a person changes primary tool, the default habit and usually the spending move with it. That change is the AI equivalent of a carrier switch for the purposes of this note, and it is what we measure here. AI Pulse is a consumer and prosumer survey: it captures the tools individuals choose for personal use and for their own work, and it does not measure enterprise contracts or developers buying AI models through an API. 

AI tool switching runs at about 6% of AI users a month

Of 31,569 AI users asked, 18% said they had changed their primary AI tool in the previous three months, an average of 6% a month. The monthly rate has stayed between 5% and 7% in every weekly wave since the question was added in December 2025. That is roughly six to seven times the monthly postpaid churn the three national wireless carriers reported for the second quarter of 2026 (i). The comparison overstates the disruption in one respect: a carrier disconnect ends a paid relationship, while most people who switch AI tools keep using the old one. About two-thirds of switchers answered a follow-up on the other tools they use, and about 90% of them still use the tool they left as their second or third. 

Heavy users drive the rate. People who use AI several times a day switch at 9% a month; those who use it a few times a month switch at 3%. Frequent users were more likely to switch, and they also made up a larger share of the people who answered the switching question than they do of AI users overall. Adjusted to the usage mix of all AI users, the rate is still about 6% of AI users in an average month. IT decision makers, the respondents responsible for AI choices for their firm or department and more often developers and product leaders, make up about a fifth of those asked. They switch at 31% over three months, roughly twice the rate of everyone else. Without them the monthly rate is 5%. Over a year, switches add up to nearly three-quarters of the AI user base, though some of those are the same people switching more than once. 

Three tools gain from AI tool switching

Among the 5,751 switchers who named both the tool they left and the tool they chose, 40% moved to ChatGPT and 33% left it, a net gain equal to about 8% of switchers. Claude took 11% and lost 7%, a net gain of about 4%. Google Gemini took 24% and lost 22%, a net gain of about 3%. Every other tool in the survey lost ground or broke even. 

Chart 1: Net change in primary users from AI tool switching by general-purpose assistant, percent of switchers: ChatGPT +8, Claude +4, Google Gemini +3, Alexa+ -4, Meta AI -3, Microsoft Copilot -2, DeepSeek, Grok and Perplexity -1 each, AI Pulse, June to September 2026

Source: Recon Analytics AI Pulse, 5,751 switchers naming both tools, 13 weekly waves opening June 26 to September 18, 2026. General-purpose assistants with the largest net changes shown; phone-based assistants (Apple Intelligence, Galaxy AI) are discussed separately. 

Between the two largest tools the exchange is close: of people who switched between ChatGPT and Gemini, 52% chose ChatGPT. Between ChatGPT and Claude, 63% chose Claude. ChatGPT’s lead among switchers leans on IT decision makers, who account for about three-quarters of its net gain. Among all other respondents, Gemini gains about 1.3 primary users for each one it loses, against about 1.1 for ChatGPT. Winning switchers has also not stopped the share of panel respondents naming ChatGPT as their primary tool from slipping, from 47% to 45% between the last two quarters. 

Pre-installed assistants lose the most 

Among general-purpose assistants, the largest net losses as a share of switchers belong to Alexa+ at 4%, Meta AI at 3% and Microsoft Copilot at 2%, followed by DeepSeek, Grok and Perplexity at about 1% each. The three largest losers come built into something the person already owns: a speaker, a social feed and Microsoft 365. Apple Intelligence and Samsung’s Galaxy AI each lost about 1% as well. They are phone features with a narrower set of capabilities and no paid tier of their own, so we keep them out of the comparison with the general-purpose assistants. 

Being built in keeps these assistants in the rotation, since a demoted tool usually stays in use, yet in this data it has rarely won them the primary slot. Gemini is the exception among embedded assistants, collecting more primary users than it gives up. Fewer than one in ten of its arrivals wrote in a reason, and about a quarter of those point to its placement, mentioning Google search, Chrome, Android or their phone; a few describe AI answers inside Google search, which blurs the line between changing tools and searching. “It is part of Google and just starts when I type on Google search,” one wrote. Its arrivals still rank answer quality first about as often as ChatGPT’s do. 

Claude wins switchers at the best ratio, from a small base 

About 4% of AI users in our panel name Claude as their primary tool, well behind ChatGPT and Gemini, yet it has the best exchange rate among switchers. For every primary user it gave up this quarter it gained 1.7, against 1.2 for ChatGPT and 1.1 for Gemini. In the previous 13 weeks the ratios were 1.5, 1.4 and 1.1, with Claude and ChatGPT close to level. 

The small base needs context. Anthropic earns most of its revenue from businesses and developers, with usage-priced API calls estimated at about 80% of its total (ii) and a consumer and prosumer panel sees little of that. Claude’s position here measures its pull with individual users and says less about the company’s overall fortunes. 

Claude also turns over fastest. Its arrivals this quarter equal 52% of its primary users at the start of the quarter, and its departures 31%. For ChatGPT the figures are 19% and 15%, and for Gemini 18% and 16%. A quarter earlier Claude’s arrivals equaled 63% of its primary users at the start of that quarter, and its departures 41%. The better ratio came from fewer users leaving, while arrivals eased. 

 

  ChatGPT  Claude  Gemini 
Gained per user lost, Jun-Sep  1.2  1.7  1.1 
Gained per user lost, Mar-Jun  1.4  1.5  1.1 
Arrivals, % of starting users  19%  52%  18% 
Departures, % of starting users  15%  31%  16% 

Table: Primary users gained per user lost and quarterly turnover for ChatGPT (1.2), Claude (1.7) and Google Gemini (1.1), June to September 2026 vs. March to June 2026, AI Pulse

Source: Recon Analytics AI Pulse, 13 weekly waves opening June 26 to September 18, 2026; prior quarter opening March 27 to June 19, 2026. 

Switchers pay more, mostly because of who they are 

Switchers pay at a higher rate than users who stay with their tool, though much of the difference comes from who switches. Switchers include more heavy users and more IT decision makers, and they head for tools that sell subscriptions. Compared with stayers who match them on tool, usage frequency and IT decision-making role, the gap narrows to about 4 points. Within ChatGPT and Gemini, the share of new arrivals who pay is more than 10 points higher than among existing users. At Claude, whose base already pays at a high rate, the two are close. 

Chart 2: Percent paying for their primary AI tool, switchers vs. stayers: all tools 37% vs. 24%, matched mix 37% vs. 33%, ChatGPT 42% vs. 29%, Gemini 23% vs. 13%, Claude 58% vs. 55%, AI Pulse, June to September 2026

Source: Recon Analytics AI Pulse, 13 weekly waves opening June 26 to September 18, 2026. Percent using a paid version of their primary AI tool. Matched mix adjusts stayers to the switchers’ mix of tool, usage frequency and IT decision-making role. 

Some of that money is personal spending on work tools. Of paying switchers, 28% pay out of pocket for a tool they use for work, the same share as paying stayers. Because more switchers pay, that group makes up 10% of all switchers against 6% of stayers. Copilot runs the other way: 65% of its paying arrivals have an employer or team covering the cost. 

Winning a payer does not guarantee keeping one. In AI Pulse waves through early September 2026, 12% of current paying users said they had canceled an AI subscription in the previous three months. Among everyone who has ever paid for one, the figure was 17%. A provider that wins a switcher still has to keep that person paying, and with about one in six past subscribers canceling in a single quarter, keeping them after the switch deserves as much attention as winning them. 

Answer quality leads AI tool switching, with curiosity close behind

Asked to rank their reasons for switching, switchers most often put better answers first, with wanting to try something new close behind. Lower cost and a less restrictive free tier together trail answer quality alone. Claude’s arrivals are the most deliberate of the three gaining tools: 29% ranked answer quality first and 7% curiosity, and they cited better features and recommendations more often than ChatGPT or Gemini arrivals. For ChatGPT and Gemini arrivals the two leading reasons ran level, at 17% to 19% each. 

Chart 3: Reason ranked first for switching, percent of arrivals to ChatGPT, Google Gemini and Claude; better answers leads at 17%, 19% and 29%, AI Pulse, June to September 2026

Source: Recon Analytics AI Pulse, 13 weekly waves opening June 26 to September 18, 2026. Share of each tool’s arrivals who ranked each reason first: 2,291 to ChatGPT, 1,331 to Google Gemini and 614 to Claude. 

What this means for AI providers 

Because people keep several AI tools at once, total users and downloads are weak guides to competitive position. The tool a person reaches for first, and pays for, is the better measure, and it changes hands often enough to track quarter by quarter. For standalone providers, the work is winning heavy users and IT decision makers on answer quality, then keeping them paying after the switch. For companies with an assistant built into a phone, speaker or social app, placement keeps the assistant in use, yet it has rarely made it the one people choose first. Gemini, whose arrivals cite both its placement and its answers, is the case to watch. 

Some readings in the coming quarters would change this picture. If built-in assistants start collecting more primary users than they lose for two quarters running, placement is beginning to win the primary slot. A rise in switchers who say an employer or school required the change, 9% as of September 2026, would mean companies are taking the choice away from individuals, which favors tools sold through IT departments. If the weekly switching rate falls below 5% for a month or more, users are settling on a primary tool and the window to win them is closing. AI Pulse tracks each of these weekly. 

Source: Recon Analytics AI Pulse, US adults, 13 weekly waves opening June 26 to September 18, 2026, data pulled October 7, 2026: 85,083 respondents, 46,851 AI users, 31,569 asked the switching question. Multi-tool use and payment by tool position are among the 46,275 AI users who named a primary tool. AI users are respondents who use AI at least a few times a month. IT decision makers are respondents responsible for firm- or department-level AI decisions. Shares of primary tool describe panel respondents and are not projected to the US population of AI users. The switching question asks whether a person changed primary tool in the past three months, so the three-month and monthly rates count people: someone who switched twice in that period counts once, and the monthly rate is the three-month rate divided by three, assuming switches are spread evenly. The annual figure is four times the three-month rate, so a person who switches in more than one quarter counts more than once. The adjusted rate applies each usage-frequency group’s switching rate to the frequency mix of all AI users. Net flows use the 5,751 switchers who named both tools: ChatGPT gained 2,325 and gave up 1,871; Claude 633 and 376; Google Gemini 1,400 and 1,251; Alexa+ 253 and 463; Meta AI 150 and 316; Microsoft Copilot 388 and 496. A tool’s starting users for a quarter are its users who did not switch plus its departures. The matched paid comparison adjusts stayers’ paid rates by tool, usage frequency and IT decision-making role to the switchers’ mix. Who pays uses the 2,118 paying switchers and 5,670 paying stayers who said why they pay; employer-funded means employer or team payment was among their reasons. Reasons are shares of switchers who ranked a first reason (5,607 overall). Gemini arrivals’ written reasons: 119, about 9% of its arrivals, self-selected. Cancellations: three waves to September 4, 2026, 1,449 current paying users and 3,131 respondents who have ever paid. The 13-week window matches the question’s three-month recall, so the two quarters’ recalled switches overlap by about half. The panel is demographically representative of US adults through quotas set during fielding, so no post-fielding weights are applied. Percentages use the answered base and are rounded to whole points, each on its own, so a rounded net figure can differ by a point from the difference of its rounded parts. The survey lists Galaxy AI as Samsung AI and Meta AI as Meta/Facebook/Instagram. 

Contact: Tanya Masiello, Analyst and Managing Director, Recon Analytics, [email protected] 

Prepared for: investors evaluating Anthropic and OpenAI. Scope: US workplace AI use measured through the Recon Analytics AI Pulse survey.

A third pathway for growth

Two of the main growth pathways for AI companies like Anthropic and OpenAI include converting free-version users into paid-version users and increasing token consumption by developers within enterprises. Investors have only those two pathways to work with while the filings stay confidential: Anthropic submitted a draft registration statement on Form S-1 to the SEC on June 1, 2026, and OpenAI announced on June 8, 2026 that it had submitted one.

There exists a third pathway, one that Recon Analytics uncovered through our AI Pulse survey of 319,595 US respondents fielded between August 2025 and July 2026. Among US adults who use a frontier AI tool for work daily, 14.0% pay for the tool with personal money. At 14.0%, the self-funded group is nearly half the size of the 30.9% employer-funded group. The self-funded segment looks like consumer revenue but is performing work inside the enterprise. With a sales approach informed by the value and experience ratings those self-funded users provide, AI vendors like Anthropic and OpenAI can convert some of this segment’s revenue to employer-funded, contract-secured, more readily expandable enterprise revenue. Until they do so, this spend remains invisible to the employer and absent from the AI vendor’s enterprise sales forecast.

Converting free-version users into paid-version users may seem the more obvious path to growth, because free-version users are 55.1% of at-work daily users. The obvious path, however, leads to lighter, less valuable work. For example, only 30.4% of free-version users bring data analysis to their AI tools, while 43.2% of self-funded users use their AI for that high-value task.

The self-funded segment represents a growth opportunity for AI vendors

The employee paying for an AI tool with personal money has done much of the evaluation needed in advance of an enterprise sale. She tested the price against a personal budget and kept paying because the tool brought value to her work. Self-funded users rate value for what they pay at +23.7 and employer-funded users rate it +23.5. The employer is therefore being asked to fund a product its own employee has chosen and can be reasonably expected to remain satisfied with. Users who pay personally already see value in the tool. That gives the vendor evidence of employee demand before asking the employer to take over payment.

Two employer decisions stand between a self-funded user and a contract. Allowing the tool is a security and compliance decision an IT department makes, and funding it is a budget decision that comes more easily once the IT department has cleared the tool. Employees carried personal smartphones into workplaces that issued them feature phones through the late 2000s, and IT departments either supported the devices employees had chosen or bought a governed alternative. The same order holds in workplace AI: among daily workplace users on a free version, 48.7% say their employer supports or reimburses the tool they use, so employer permission runs well ahead of employer payment.

Converting self-funded users onto employer-funded contracts is only the first step toward growth; the next step is taking this more durable, contracted revenue and expanding it across work groups and with higher tier products. Durability comes from contracts that renew annually versus individual subscription accounts that may be canceled at any time. Expansion comes from better employer visibility on how the tool provides value to systems and processes followed by increases to seats and integration.

Claude’s positioning: large opportunity for a high-value product with some risks

Compared to ChatGPT, Claude has a higher percentage of its workplace users paying for the tool with personal money, 29.4% for Claude versus 14.7% for ChatGPT. Counting only the users whose subscription somebody pays for, 44.5% of Claude’s users pay for it themselves against 31.5% of ChatGPT’s. Therefore both the growth opportunity from converting to employer-paid and the risk from month-to-month individual contracts canceling are proportionally larger for Claude.

Paying users and free users grade their tools differently enough that only the paying users answer the question an employer is being asked, so the ratings here count paying users alone. Claude’s paying users rate Claude at +38.9 on making them more productive, against +29.4 among ChatGPT’s paying users, on a scale that runs from -100 to +100. That advantage sits in productivity rather than across the board. Across the seventeen at-work attributes Recon Analytics measures, paying Claude users rate Claude higher than paying ChatGPT users rate ChatGPT on ten and lower on seven, close to an even split.

Claude reaches the workplace through the employee rather than through the IT department. Technical roles account for 49.8% of Claude’s paying workplace users, against 38.9% for ChatGPT, 38.7% for Google Gemini and 36.5% for Microsoft Copilot. Among free-version users, 32.9% of those whose primary tool is Claude say their employer supports or reimburses Claude, against 51.2% of those whose primary tool is ChatGPT.

For Claude the harder of the two employer decisions is the one the IT department makes. Security and privacy is the attribute Claude’s paying users rate lowest, at -10.9 against -2.1 for ChatGPT’s paying users, and it is the attribute an IT department weighs when it decides whether to allow the tool at all. That rating is a gate in front of the contract rather than a cost inside it.

Conclusions for investors

An investor should price the conversion of self-funded users into employer-funded users as retention and expansion rather than as new revenue. Neither company has to build anything for that conversion to happen. An employee who pays for Claude with personal money can move that account into an employer’s Team or Enterprise organization, and Anthropic cancels the personal subscription and refunds the unused time. OpenAI treats an employee’s personal ChatGPT account the same way when it merges into a company workspace. The personal payment stops as the employer payment starts. The price of a personal subscription is nearly the same as the price of an enterprise subscription; the growth comes from expansion of seats and use once the employer contract enables that expansion.

Anthropic’s Claude has twice the conversion density of OpenAI’s ChatGPT on a much smaller base and still this conversion opportunity is a substantial addition to the more familiar free-to-paid conversion and API token growth pathways. Potential conversion of self-funded to employer-funded is one workplace pool where Claude leads OpenAI by two to one. The same concentration carries the larger downside, because an employer that standardizes on a rival removes the self-funded user rather than leaving the account in place.