AWS announced it will shut down Mechanical Turk (MTurk) on September 30, 2026, ending the crowdsourcing microtask platform that has been in operation for about 21 years. The company stated that the decision comes from a routine evaluation of projects, tools, and services.

Launched in 2005, MTurk allowed businesses, researchers, and developers to break down tasks that machines struggle to complete reliably into human intelligence tasks, which could then be completed by dispersed online workers for payment. Typical tasks included image labeling, content moderation, data classification, surveys, and transcription.

The AWS announcement did not disclose revenue, user numbers, active worker counts, order sizes, specific evaluation metrics, or alternative product arrangements related to the shutdown. Current service terms still indicate that Amazon Augmented AI can call upon MTurk labor, but customers are prohibited from providing protected health information or personally identifiable information to that labor.

MTurk has long been a foundational node in the machine learning data supply chain: research teams quickly procured human annotations through it, and businesses could distribute image, text, or audio review tasks to global crowdsourced laborers via API. Its closure will force clients reliant on the platform to migrate task processes, rebuild worker pools, or choose alternative annotation services before September 30. cnbc+1

The platform's original name comes from the 18th-century "Mechanical Turk" chess-playing hoax; Amazon founder Jeff Bezos once referred to MTurk as "artificial artificial intelligence," meaning it allows human workers to perform tasks that appear to be completed by machines. The product emerged before the industrialization of large model training, positioning itself as a way to package human judgment as a programmable cloud service.

From a market mechanism perspective, the closure of MTurk will shift the demand for low-cost, task-based human annotation from buyers to professional data annotation vendors, crowdsourcing alternative platforms, BPO suppliers, and synthetic data tools; clients needing high-quality, multilingual, or sensitive content review will face higher migration and quality control costs. Vendors with closed expert networks, enterprise-level privacy compliance, and auditable data sources will benefit; research projects and small AI teams relying on open, cheap labor and quick access to the MTurk API will be under pressure.

Source: Public Information