Generative AI in Data Labeling Solution and Services Market Revenue to Attain USD 29.75 Bn by 2035

Published: 20 Feb 2026

Author: Precedence Research

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Generative AI in Data Labeling Solution and Services Market Revenue and Trends 2026 to 2035

The global generative AI in data labeling solution and services market revenue was valued at USD 2.95 billion in 2025 and is expected to attain around USD 29.75 billion by 2035, growing at a CAGR of 26.00% during forecast period.The market's growth is driven by the growing demand for high-quality training data and rapid technological progress in generative AI.

What Drives the Generative AI in Data Labeling Solution and Services Market?

The increasing demand for data-driven decision-making in numerous organizations increases the dependence on generative AI for efficient data labelling, accelerating the growth of the market in the coming years. The rising AI adoption across various industries like automotive, finance, healthcare, and retail and e-commerce is driving the need for precise and large-scale labeled datasets. Generative AI tools are used to automate the annotation process, which significantly reduces the time and high costs associated with manual labeling.

The market's growth is also largely driven by the growing need for automation and the rising trend toward multimodal AI systems that process text, images, and video.

Segment Insights

• By offering, the labeling solutions segment accounted for the highest revenue share of approximately 44% in 2025, driven by the surging demand for high-speed, scalable, and high-quality data annotation to train complex models. Automated tools process data rapidly to meet the demand for high-quality datasets required for generative AI.
• By data type/labeling type, the image and video labeling segment contributed the largest revenue share, nearly 41%, in 2025. The segment dominance is primarily attributed to the growing demand for high-quality visual content. Image and video data labeling are crucial for developing and training artificial intelligence models in various sectors.
• By end-user industry, the technology and Internet/LLM providers segment dominated the global generative AI data labeling solutions and services market, with a share of nearly 24% in 2025, owing to the rising demand for scalable and secure AI model training. LLMs automate and enhance the accuracy of data labeling for natural language tasks and multi-modal data.

Regional Insights

North America holds the dominant share of the global generative AI in data labeling solution and services market. The region’s leadership is driven by the robust presence of major AI technology firms, rising R&D investments, stringent data protection regulations, increasing demand for high-quality and compliant data labeling, rising demand for advanced AI models, and increasing demand from various sectors across sectors like retail and e-commerce, autonomous vehicles, financial services, healthcare and medical imaging, manufacturing and robotics, and others.

On the other hand, Asia Pacific is anticipated to grow at the fastest rate in the market during the forecast period. The fastest growth of the region is attributed to the rising shift toward multimodal AI systems, the growing need for large-scale datasets for advanced AI model training, increasing demand for automation in data labeling, and the rising adoption of AI applications.

Generative AI in Data Labeling Solution and Services Market Coverage

Recent Developments

• In July 2025, Cognizant announced the launch of AI Training Data Services, a new offering designed to help enterprises build, fine-tune, and implement AI models at speed and scale. Leveraging deep experience as a data and AI model training partner to select digital native pioneers. (Source: https://news.cognizant.com)
• In March 2025, NTT DATA, a global leader in digital business and technology services, announced the launch of its Agentic AI Services for Hyperscaler AI Technologies. This transformative suite of services helps organizations easily adopt, build, manage, and scale AI-powered agents to improve efficiencies, unlock innovation, and enhance employee and customer experiences, maximizing returns on AI investments. (Source: https://services.global.ntt)

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