Amazon Mechanical Turk has closed for good. The notice on mturk.com is short: "Amazon Mechanical Turk permanently closed on September 30, 2026." New customers had been turned away since July 30, 2026. If you ran HITs there, that work needs a new home.
Where it should go depends on what you need back, and on who checks it before anyone is paid.
Short answer
The best Amazon Mechanical Turk alternative depends on the work you ran there. For research participants and surveys: Prolific or CloudResearch Connect, which screen their participant pools, or User Interviews and Respondent for user-research sessions. Respondent identity-verifies every participant; User Interviews relies on AI-powered matching and fraud detection. For AI training data and labeling at volume: Clickworker for a filtered crowd, or Appen and Toloka if you are an AI team buying human data, with Toloka also offering a self-service platform. For a job that repeats with clear steps, which you would rather automate than send to a crowd: an AI agent from Pond, which you build yourself with Pond's ready-made tools and data, or have Pond build for you. For work that was already on MTurk, HIT submission closed on September 30, and Amazon gave requesters until October 30, 2026 to approve or reject what was submitted.
What happened when Mechanical Turk closed
Amazon's requester FAQ spells out the end state. "HIT submission closed on September 30, 2026. Requesters have 30 days (until October 30, 2026) from the closure to approve submitted HITs. All remaining unsubmitted HITs have automatically expired." For completed HITs a requester does not approve or reject, the FAQ says "they will be auto-approved," so workers are paid for work that arrived in time. Bonuses share the same cutoff: "Requesters can award bonuses until October 30, 2026."
The closure reaches further than the MTurk website. The same requester FAQ says it "also applies to SageMaker Ground Truth and Amazon Augmented AI," and that the Mechanical Turk Worker type is no longer available for creating labeling jobs or human review workflows as of September 30, 2026. A team that never logged into mturk.com, but routed labeling through SageMaker, is affected too.
The first step came earlier. TechCrunch reported on July 5, 2026 that the service would close to new customers on July 30, and quoted Amazon's statement that existing customers "can continue to use the service as normal." That access lasted until the September 30 shutdown.
Real buyers were caught by the date. As reported in CNBC's coverage of the shutdown, Turkopticon organizer Krista Pawloski said some insurance and travel companies still depended on MTurk for data workers and were scrambling to find alternative platforms.
The quality gap MTurk leaves behind
MTurk was quick to start and easy to scale. It was never strong on what matters most for work you need to trust: knowing whether a submission is real.
Look at who judged the work. Amazon's worker FAQ was explicit: "Amazon Mechanical Turk does not determine whether or when to approve or reject HITs," which left the decision to the requester, within 30 days. If a worker thought a rejection was wrong, the FAQ's advice was that they "may decide to contact the Requester directly." There was no referee between the two sides. Turkopticon, the worker-run group that grew up around MTurk, describes its mission as holding platforms and companies "accountable to the labor they rely on."
MTurk's own quality signal was the Masters Qualification. Amazon granted it with statistical models across requester and marketplace data. Amazon said workers "cannot apply for this status," and the status could be revoked if performance declined. A requester who added it to a HIT was relying on a judgment made by Amazon's models.
The research on what came back is not flattering.
- LLM-written work, submitted as human work. Researchers at EPFL reran a text-summarization task on MTurk and, using keystroke logging and a synthetic-text classifier, estimated that "33-46% of crowd workers used LLMs when completing the task" (Veselovsky, Ribeiro and West, 2023). That was one summarization task, with 48 summaries from 44 workers, and the authors note that "generalization to other, less LLM-friendly tasks is unclear." On a text task like that one, a sizable share of what a requester paid for as human writing may have come from a model.
- Location fraud. A study of 38 surveys over five years, covering 24,930 respondents, found that "VPS and non-US respondents have spiked." The peak came in summer/fall 2018, when about 20 percent of respondents were "coming either from a VPS or a non-US IP address," and the authors found these respondents "provide particularly low-quality data" (Kennedy et al., Political Science Research and Methods, 2020).
- Filters that leak. A 2022 comparison of platforms in Behavior Research Methods noted that even with the US-only filter on MTurk, as much as five to ten percent of a sample may be recruited from outside the United States, citing earlier work by Feitosa and colleagues (Peer et al., 2022).
- Attention and follow-through. A 2023 PLOS ONE study compared five data sources and found that, compared with MTurk, participants on Prolific and CloudResearch "were more likely to pass various attention checks, provide meaningful answers, follow instructions," and have a unique IP address and geolocation (Douglas, Ewell and Brauer, 2023). The CloudResearch arm was its MTurk Toolkit, which posts surveys to MTurk and filters which workers can take them. So the CloudResearch result is about screened MTurk workers. The study did not test CloudResearch's Connect pool.
None of this means every MTurk worker did bad work. It means the platform left verification to you, and the problems kept getting harder to spot. The EPFL team needed keystroke logging and a synthetic-text classifier to find the model-written summaries.
So when you pick a replacement, the headline number of workers matters less than three questions.
- Who verifies the worker? A one-time signup check, continuous screening, identity verification, or nothing.
- What proof comes back with the work? An answer in a box, or evidence a reviewer can check: a recording, raw output, a data source.
- Who decides whether it gets paid? You, the platform, a managed service, or a rule written down before anyone started.
The eight platforms answer those three differently.
Mechanical Turk alternatives, grouped by what you need back
We sorted eight platforms, Pond included, into three groups by what a buyer walks away with. Each description comes from the platform's own site, read on September 24, 2026 and re-checked on October 27, 2026. Pond's details come from its homepage, read on October 30, 2026.
Research participants and surveys
This is where most former MTurk requesters doing academic and market research will land. These platforms return responses and sessions from screened people rather than work products.
Prolific. Prolific has rebuilt its MTurk comparison page around the closure: "MTurk shut down permanently on September 30th." It says it has "300k+ active participants" and offers more than 300 pre-set filters that researchers use to target participants. Its own comparison adds: "Even before this, in head-to-head testing against MTurk, Prolific produced significantly higher data quality on every measure." The same passage continues: "And so did Qualtrics, Dynata, and CloudResearch, too." That is the vendor talking, but the independent PLOS ONE study points the same way.
Best for: academic studies and surveys where you need a screened sample and clean attention data. Not the fit: anything that is a deliverable rather than a response, such as a lead list or a bug report.
CloudResearch Connect. Connect is CloudResearch's own participant pool. It says the pool is "continuously vetted with behavioral screening, device fingerprinting, and AI-content detection," on every study rather than only at sign-up. Connect also lets participants rate studies and researchers rate participants. CloudResearch's Sentry product screens each respondent before they enter a survey and, in the company's words, "Proactively identifies and blocks AI-generated survey responses," a closely related failure to the one the EPFL study found on MTurk. If you would rather hand the whole study off, CloudResearch's managed research service says it replaces any participant who provides unusable results.
Best for: MTurk researchers who want the most direct continuation, with AI-response detection built in. Not the fit: buyers who need work products instead of survey data.
User Interviews. User Interviews recruits people for user research sessions. Its homepage promises "1 hour to first match," says 0.6% of sessions are reported for fraud, and names its mechanism as "AI-powered matching & fraud detection."
Best for: product and UX teams booking interviews and usability sessions with a specific kind of person. Not the fit: high-volume, short tasks of the kind MTurk was built for.
Respondent. Respondent leads with identity: "Every participant is identity-verified before they reach your study." It lists "4.3M+ identity-verified participants," four passes per study that trade off fit and fill speed, and "Four independent checkpoints" against bad actors. New members, it says, are weighed against "50+ signals on day one," from device fingerprints to work-email checks.
Best for: research with professionals, when it matters that each person really holds the job title they list. Not the fit: anonymous, quick-turn microtasks. Those sit outside what Respondent is built for.
AI training data and labeling
If you used MTurk, or SageMaker Ground Truth with the MTurk workforce, to label data or produce training examples, this is the closer match. Two of the three, Appen and Toloka, now pitch themselves mainly to AI companies buying human data.
Clickworker. Clickworker runs a crowd of "more than 8 million" people, by its own count on its crowd page. Workers are not simply let in. They register with details such as residence, native language and skills, complete "project-independent online tests/training," and have their work results evaluated, and Clickworker says it uses "specialized filtering methods" to assign the best-qualified people to each project. Survey recruiting is self-serve: its self-service page lets you "independently recruit survey participants and conduct online surveys" through a marketplace. Labeling and other data work comes two ways. The same page says other services "are provided with full support through our Managed Service," and Clickworker also sells Crowd as a Service, where your own team handles "Direct task creation and management via API or UI." That route starts with contacting Clickworker. The Crowd as a Service page's call to action is "Contact us," and a note on the Clickworker marketplace reads: "The Self-Service platform is exclusively available for online surveys. For all other services, please use our Managed Service and get in touch with us." None of the Clickworker pages we read publish a requester price list.
Best for: text, categorization and data tasks at volume, where you want the platform to filter the crowd for you. Not the fit: a one-off labeling job you want live today, before you have contacted Clickworker to set up access.
Appen. Appen's homepage now reads "Human data for frontier AI," and its listed products include Frontier Alignment, Agentic AI and Model Integrity. It cites "30 years of AI data expertise" and SOC 2 and ISO 27001 certification, and its menu links an AI Data Platform (ADAP), described as "automation meets human oversight." The homepage leads with enterprise data work. If you ran small piecework HITs, Appen is not a like-for-like swap.
Best for: AI teams buying expert human data, evaluation and alignment work under contract. Not the fit: a few hundred short tasks from a small buyer, which is not the business Appen's own pages describe.
Toloka. Toloka has made the same move. Its homepage says it builds "data solutions integrating human expertise and technology to accelerate AI development," and lists agent trajectory demonstrations, RL-gym environments and safety red-teaming. It also runs a self-service platform that opens with "Describe your data goal. The agent builds the rest." Its Self-Service Agreement, dated April 22, 2026, covers using platform.toloka.ai "to purchase and manage annotation, labeling, and data-gathering tasks."
Best for: AI teams that need training or evaluation data, whether Toloka builds the pipeline with them or they set it up on the self-service platform. Not the fit: a survey study or a round of user interviews. Research participant platforms are built for those.
Several other names come up when you search for MTurk alternatives, among them TELUS Digital, Scale AI's Outlier, CloudFactory, SproutGigs, Microworkers and DataAnnotation.tech. We did not review their own pages for this piece, so we have left them out of the groups rather than describe them secondhand.
Recurring work you want automated: an AI agent from Pond
Pond is the entry here that does not send the work to a crowd at all. In Pond's words: "Pond builds, runs and maintains custom AI agents for businesses. We also offer sales lead data and ready-made tools, like workflow templates, scrapers and data connections, so you can build your own AI agents on our existing AI infrastructure" (Pond). An agent, as Pond defines it, "connects to your tools, follows a set process and keeps going on its own".
It fits where an MTurk job came back again and again with the same steps, and you would rather automate it than keep buying it piece by piece. Pond's examples are mostly recurring jobs: "qualifying every new inbound lead and routing the best fits to your team, screening job applicants and scheduling interviews, finding new sales leads and handling outreach, replying to Google reviews and customer feedback, and keeping your CRM, inbox and spreadsheets in sync."
The homepage offers two ways in. Try Pond to build your own: "Click 'Try Pond' and describe what you need in plain language. Pond will help you turn it into AI agents that solve your problems." Or get a custom AI agent: "Need something more complex? Pond can build it for you, so you can use the AI agent and automation directly for your business." That route starts with a 30-minute consultation, which you can book on Pond's homepage.
Here is how Pond answers the same questions in its own terms.
- Who verifies the worker? There is no crowd to screen. The work is done by an AI agent, built by you with Pond's tools and data, or built for you by Pond.
- What comes back? Pond's last step is to run the agent from your AI chatbot: "Ask your AI to run the AI agent workflow. Pond handles the work, and you review the results." The finished agent runs "from the AI you already use, like Grok Bot, Muse, ChatGPT or Claude", and it "can work with your CRM, email, spreadsheets and other tools."
- What do you pay for? A custom build, or Pond's monthly plan. Pond's homepage FAQ says: "Custom AI agent builds start from $1,000, usually take 1 to 2 weeks, and come with a 7-day refund that applies only to custom builds. There's no free trial for the monthly plan." The homepage publishes no price for the monthly plan.
The checking starts earlier. On MTurk you judged each HIT after it arrived. With an agent, Pond's third step is to connect the tools and data the workflow needs, then "Review everything before getting started."
Best for: a job that repeats with clear steps, such as qualifying inbound leads, screening job applicants or keeping a CRM, inbox and spreadsheets in sync. Not the fit: a survey sample with demographic quotas, or a one-off task you need done once.
If your MTurk work was closer to freelance projects than to microtasks, our comparison of 11 Upwork alternatives covers that side of the market.
How to choose a replacement
Start from the HIT you would have posted next, and ask what you need to be holding when it is done.
- Survey responses from a screened sample. Prolific or CloudResearch Connect is the natural next home for the study. If AI-written answers worried you on MTurk, CloudResearch's AI-response detection is built for that problem.
- Interviews or usability sessions with specific people. User Interviews for fast matching, or Respondent when identity and job title matter most.
- Labeling at volume. Clickworker for a filtered crowd. Appen if you are an AI team ready to buy a managed service under contract, or Toloka, which offers both built-for-you data projects and a self-service platform.
- A job that comes back every day with the same steps. That is a process to automate. Try Pond to build an AI agent yourself, or have Pond build a custom one.
- You cannot say what "done" looks like yet. Then no platform will fix it. Write that down first.
An answer you cannot check is a guess you paid for.
What former MTurk requesters should do now
Amazon's closure FAQ sets the wind-down dates and says what applies after them.
- Know the October 30 cutoff. Amazon's FAQ set October 30, 2026 as the last day to approve or reject submitted HITs, award bonuses and verify payment information in the MTurk Requester Portal. After that, payment updates go through Customer Service. For completed HITs, "If no action is taken, they will be auto-approved." Each submitted assignment could also auto-approve earlier on its own delay, which Amazon's CreateHIT API reference counts from when an assignment "has been submitted, after which the assignment is considered Approved automatically unless the Requester explicitly rejects it."
- Send payment updates to Customer Service after October 30. The FAQ asked requesters to "verify your payment information within the MTurk Requester Portal by October 30, 2026," which it says will "ensure that any refunds are processed in a timely manner." After that date, it says: "After October 30, 2026, please contact Customer Service for further payment update requests."
- Follow up on a missing refund. Amazon says requesters "should expect a full balance refund within 30 days of the September 30, 2026 closure." "If you haven't received your refund within that timeframe, please contact MTurk Customer Service."
- Replace the Mechanical Turk Worker type in SageMaker. Ground Truth labeling jobs and Amazon Augmented AI human review workflows can no longer use it as of September 30, 2026. Any pipeline that relied on it needs a new workforce.
- Save your transaction history. "Your transaction history will remain available until January 28, 2027." Keep a copy of what you need before that date.
- Rewrite your instructions as a brief. A HIT's instructions were written for anonymous workers who might not read them. A replacement works better when the instructions state what a finished result is and what evidence it carries.
- Run one small pilot before you move everything. Compare what comes back against your own MTurk results before you migrate a whole study or pipeline.
When an AI agent from Pond is the wrong call
An agent pays off when the job repeats and has clear steps. It is the wrong call for a one-off job, for work where the steps change every time and need a person's judgment, for a research sample with demographic quotas, which is what Prolific and CloudResearch are for, for relationship or retainer work where you want the same person every week, for regulated professional work such as legal or medical advice, and for physical, in-person jobs.
Frequently asked questions
Why did MTurk shut down?
Amazon's pre-closure notice gave only a general reason. "We regularly evaluate our programs, tools, and services and make adjustments based on those assessments," it said, before announcing the closure. In CNBC's reporting, Turkopticon organizer Krista Pawloski said Amazon seemed to invest less in improving MTurk while more data-labeling services arrived and many workers moved to them.
Is Amazon Mechanical Turk still available?
No. Amazon Mechanical Turk permanently closed on September 30, 2026, and mturk.com now reads: "Mechanical Turk is no longer available." It had closed to new customers on July 30, 2026. The closure also removed the Mechanical Turk Worker type from SageMaker Ground Truth and Amazon Augmented AI. Amazon gave requesters until October 30, 2026 to approve or reject submitted HITs. For HITs left without action, its FAQ says: "If no action is taken, they will be auto-approved."
Is Prolific better than MTurk?
For survey and study data, the evidence says yes. An independent 2023 study in PLOS ONE found Prolific participants more likely than MTurk participants to pass attention checks, give meaningful answers and follow instructions. Prolific also offers more than 300 pre-set filters for targeting participants. It is built for research participants, though, not for tasks that produce a deliverable.
What is similar to MTurk?
Clickworker is the closest in shape: a large crowd doing short data tasks, with filtering and qualification tests on the way in. For research, Prolific and CloudResearch Connect replace MTurk studies. Appen and Toloka now sell human data to AI companies, and Toloka also runs a self-service platform for annotation and labeling tasks. For a job that repeats with clear steps, Pond builds custom AI agents, or gives you the tools and data to build your own.
What should a former MTurk requester do now?
Amazon set October 30, 2026 as the last day to approve or reject submitted HITs, award bonuses and verify payment information in the MTurk Requester Portal. Completed HITs left without action are auto-approved. Afterward, payment updates go through MTurk Customer Service; contact it if the balance refund has not arrived within 30 days of the closure. Save your transaction history before January 28, 2027. Replace the Mechanical Turk Worker type in any SageMaker Ground Truth or Amazon Augmented AI workflow. Pick a replacement by what you need back, and run one small pilot before moving a whole study or pipeline.
Can AI agents do the work MTurk workers did?
Some of it. The 2023 EPFL study estimated that 33-46% of MTurk workers on one text task were already using LLMs, and its authors say it is unclear how far that holds for other tasks. For a recurring job with clear steps, an AI agent can take over the process itself. Pond builds custom agents, or gives you the tools and data to build your own, and you review the results.
Move the work that needs trusting first
MTurk made it easy to buy answers and hard to know which ones were real. Whatever you choose next, choose it by who checks the work and what evidence comes back with it. If the job repeats and you can write down its steps, put an AI agent on it: Try Pond and describe what you need in plain language, or get a custom AI agent built for you.
