Austin, Dec. 19, 2025 (GLOBE NEWSWIRE) -- The global AI Annotation Market was valued at USD 2.39 billion in 2025E and is expected to reach USD 28.31 billion by 2033, growing at a CAGR of 17.46% over 2026-2033.
Due to the quick development of AI and machine learning applications in sectors including autonomous cars, healthcare, retail, and finance, the market for AI annotations is expanding rapidly. Adoption is being fueled by the growing need for high-quality labeled data to train sophisticated algorithms as well as the development of computer vision and natural language processing technologies.
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The U.S. AI Annotation Market was valued at USD 0.66 billion in 2025E and is expected to reach USD 4.69 billion by 2033, growing at a CAGR of 27.75% from 2026 to 2033.
Due to the increased use of AI and machine learning in industries like healthcare, autonomous vehicles, and retail, the U.S. AI annotation market is expanding quickly. The industry is expanding steadily due to rising demand for high-quality labeled datasets, improvements in automated annotation technologies, and significant investments from tech companies.
Segmentation Analysis:
By Data Type
In 2025, Image led the market with 42% share due to its critical role in computer vision applications such as facial recognition, autonomous driving, and medical imaging. The Video segment is expected to grow fastest from 2026–2033 due to the rising need for real-time object detection, surveillance, and autonomous navigation.
By Annotation Type
In 2025, Manual Annotation led the market with 55% share as it ensures superior accuracy, context awareness, and quality control for complex datasets. Automatic Annotation is expected to grow fastest from 2026–2033 due to advancements in AI-assisted labeling tools that significantly reduce time and costs.
By Buyer Type Outlook
In 2025, OEMs & Large Enterprises led the market with 44% share as they have extensive AI development projects, large data requirements, and higher budgets for data labeling. SaaS Companies & Platform Owners are expected to grow fastest from 2026–2033 as they increasingly integrate AI annotation capabilities into cloud-based platforms.
By Application / Use Case
In 2025, Autonomous Vehicles & Mobility led the market with 28% share as image and sensor data labeling is vital for object detection, navigation, and safety applications. Medical Imaging and Healthcare are expected to grow fastest from 2026–2033 due to increasing use of AI for diagnostics, disease detection, and image-based clinical analysis.
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Regional Insights:
North America dominated the AI Annotation Market with a 32% share in 2025 due to the strong presence of leading AI companies, high investment in automation technologies, and early adoption of advanced machine learning models across industries. Asia Pacific is expected to grow at the fastest CAGR of about 30.12% from 2026–2033, driven by the rapid expansion of AI-based startups, growing data labeling outsourcing industry, and increasing government support for AI innovation.
Growth of Autonomous Vehicles and Advanced Driver Assistance Systems (ADAS) Augment Market Expansion Globally
The demand for data annotation is being greatly increased by the quick development of autonomous vehicles and ADAS technology. To train computer vision algorithms for lane detection, pedestrian recognition, object tracking, and traffic sign identification, these systems use well labeled picture and video datasets. Reliable, practical autonomous driving solutions are advanced by automakers and AI developers with the help of accurate annotation, which guarantees safer navigation, better decision-making, and improved vehicle perception. The demand for high-quality, large-scale labeled data is increasing as R&D speeds up.
Key Companies:
- Scale AI
- Appen
- iMerit
- Cloud Factory
- Shaip
- TELUS International
- Lionbridge AI
- Super Annotate
- Label box
- task Us
- Surge AI
- Sama (Sama source)
- Cogito Tech
- Payment
- Data loop AI
- Toloka
- Understand.ai
- Twine AI
- Zuru Tech
- DataAnnotate (or Data Annotate)
Recent Developments:
June 13 2025: Meta invested in Scale, valuing the company over US USD29 billion; Scale’s founder moved to Meta while remaining on Scale’s board, marking a strategic evolution of Scale’s enterprise partnership path.
December 18 2024: Appen blogged their review of 2024 and outlook for 2025, noting milestones and shift to supporting generative and agentic AI.
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Exclusive Sections of the Report (The USPs):
- Demand & Utilization Intensity Metrics – helps you understand how rapidly annotated data volumes are scaling across industries, along with workforce utilization rates, idle time reduction through automation, and sector-wise demand concentration.
- Annotation Cost & Pricing Dynamics – helps you evaluate historical and future trends in annotation costs per dataset and per 1,000 labels, including manual vs. automated pricing, cost elasticity, and buyer sensitivity to price-volume changes.
- Productivity & Quality Benchmarks – helps you assess operational efficiency through annotator throughput, turnaround time (TAT) reduction, error rate trends, and the impact of QA processes on final annotation accuracy.
- Automation & AI-Assisted Labeling Penetration – helps you identify how quickly the market is shifting from manual to automated annotation via automation penetration rates, AI-assisted labeling cost savings, and workforce productivity gains.
- Technology Adoption & Innovation Indicators – helps you track the maturity of AI-driven annotation workflows using automation maturity indices, ML-assisted tool adoption rates, R&D spending intensity, and patent filing activity.
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