New York, Dec. 11, 2024 (GLOBE NEWSWIRE) -- Market Overview
Global Generative AI in Data Labeling Solutions and Services market is set to reach USD 15.5 billion by the end of 2024 and is expected to grow significantly, reaching approximately USD 99.7 billion by 2033, with a CAGR of 23.0%.
This market offers advanced tools and services crucial for labeling data to effectively train generative AI models. As AI technologies such as natural language processing and computer vision rapidly advance, the need for accurate, diverse, and comprehensive data labeling has increased.
The explosive growth in the market is driven by the demand for scalable and precise labeling services, as generative AI enhances efficiency by automating complex tasks, reducing manual effort, and improving data quality.
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The US Generative AI in Data Labelling Solution and Services Market
In the US, the Generative AI in Data Labeling Solutions and Services market is expected to reach USD 5.0 billion by the end of 2024 and is projected to grow substantially to an estimated USD 28.7 billion by 2033, with a CAGR of 21.6%.
As organizations generate more data, they need high-quality labeled datasets to train machine learning models effectively, driving the demand for AI solutions that facilitate efficient and accurate data labeling.
Semi-supervised and self-supervised learning methods in generative AI for data labeling are becoming increasingly popular in the US. These approaches reduce the reliance on large labeled datasets by utilizing both labeled and unlabeled data, enhancing efficiency and reducing costs.
Important Insights
- Market Growth: The global Generative AI in Data Labeling Solutions and Services market is projected to grow by USD 81.0 billion at a CAGR of 23.0% from 2025 to 2033.
- Sourcing Type Analysis: In-house sourcing is anticipated to lead the Generative AI in Data Labeling Solutions and Services market, with a projected revenue share of 55.3% in 2024.
- Type Analysis: Image and video-based labeling is expected to dominate the market, accounting for over 40.0% of the share in 2024.
- Labeling Type Analysis: Semi-supervised labeling is set to be the leading approach in the generative AI data labeling market, with a revenue share of 39.6% in 2024.
- Vertical Analysis: IT data is forecasted to be the largest segment in the generative AI data labeling market, holding a 29.1% market share in 2024.
- Regional Analysis: North America is predicted to lead the global Generative AI in Data Labeling Solutions and Services market, with a 39.1% market share by 2024.
Latest Trends
- Shift Towards Semi-Automated and Automated Labeling:Companies are increasingly adopting semi-automated and fully automated data labeling techniques. Generative AI models help cut down on the time and costs of manual labeling while boosting scalability and efficiency.
- Integration of AI with Human-Assisted Systems:There's a growing trend to combine AI-driven data labeling with human-assisted systems. This hybrid approach enhances accuracy by merging AI's speed with human annotators' nuanced understanding, especially for complex or ambiguous tasks.
Competitive Landscape
- Intense Competition: The market is highly competitive with numerous large and small players offering both software and services domestically and internationally.
- Market Fragmentation: Currently moderately fragmented, the market is trending towards increased fragmentation. Major companies include IBM Corporation, OpenAI, and DataRobot.
- Strategic Approaches: Leading players are innovating their products and services, and engaging in mergers and acquisitions to enhance their product portfolios and stay competitive.
- Leading Platforms: Scale AI and DataRobot are prominent, providing advanced data labeling platforms essential for AI development across various industries.
Some of the prominent market players:
- Scale AI
- DataRobot
- Amazon Web Services (AWS)
- OpenAI
- Cognilytica
- Snorkel AI
- Google (DeepMind)
- iMerit
- IBM
- Salesforce
- Alegion
- Microsoft
- Other Key Players
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Generative AI in Data Labeling Solution and Services Market Scope
| Report Highlights | Details |
| Market Size (2024) | USD 15.5 Bn |
| Forecast Value (2033) | USD 99.7 Bn |
| CAGR (2024-2033) | 23.0% |
| North America Revenue Share | 39.1% |
| The US Market Size (2024) | USD 5.0 Bn |
| Historical Data | 2018 - 2023 |
| Forecast Data | 2025 - 2033 |
| Base Year | 2023 |
| Estimate Year | 2024 |
| Segments Covered | By Sourcing Type, By Type, By Labeling Type, By Vertical |
| Regional Coverage | North America, Europe, Asia Pacific, Latin America, Middle East & Africa (MEA) |
Market Analysis
IT data is anticipated to dominate the generative AI in data labeling solutions and services market with a 29.1% market share in 2024, driven by the extensive volume and complexity of data generated within the IT sector.
They produce substantial amounts of both unstructured and structured data as organizations across various industries increasingly adopt digital technologies. This data must be accurately labeled to train generative AI models, which are important for applications like data mining, predictive analytics, cybersecurity, and infrastructure management.
The prominence of IT data is also supported by the rapid advancement of cloud computing, big data analytics, and AI-driven applications, which depend heavily on well-labeled datasets.
Generative AI in Data Labeling Solution and Services Market Segmentation
By Sourcing Type
- In-House
- Outsourced
By Type
- Image/Video-Based
- Audio-Based
- Text-Based
By Labeling Type
- Automatic
- Manual
- Semi-Supervised
By Vertical
- IT Data
- Government
- Financial Services
- Healthcare
- Automotive
- Retail
- Others
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Drivers
- High-Quality Data Demand: Increasing need for precise labeled data to improve AI and machine learning performance across industries like healthcare, finance, and retail.
- Cost Efficiency and Scalability: Generative AI solutions offer significant cost savings and scalability, driving widespread adoption.
Restraints
- Adoption Barriers:Concerns over data accuracy may hinder the adoption of AI-driven labeling solutions, affecting market growth.
- High Costs:Developing and maintaining AI-powered data labeling solutions involves significant expenses, posing a challenge for market expansion.
Opportunities
- Advanced AI Model Integration:Large-scale AI models like GPT and BERT require extensive labeled data, driving demand for efficient and scalable data labeling services.
- Market Potential:Companies integrating generative AI with these advanced models are positioned to capture significant market share.
- Localized Data Needs:Generative AI can meet the demand for localized and culturally relevant labeled data, facilitating market expansion
Regional Analysis
North America is projected to lead the generative AI data labeling solutions and services market, capturing a revenue share of 39.1% in 2024. This leadership is attributed to the region’s robust technological infrastructure, high adoption rates of AI, and presence of major industry players.
Significant investments in AI research and development, particularly in the United States, where leading tech companies are spearheading the use of generative AI for data labeling, are fueling market growth. The region benefits from a vibrant ecosystem of startups, established firms, and research institutions, all driving innovation in AI.
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By Region
North America
- The U.S.
- Canada
Europe
- Germany
- The U.K.
- France
- Italy
- Russia
- Spain
- Benelux
- Nordic
- Rest of Europe
Asia-Pacific
- China
- Japan
- South Korea
- India
- ANZ
- ASEAN
- Rest of Asia-Pacific
Latin America
- Brazil
- Mexico
- Argentina
- Colombia
- Rest of Latin America
Middle East & Africa
- Saudi Arabia
- UAE
- South Africa
- Israel
- Egypt
- Rest of MEA
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Recent Developments
- August 2023: DataRobot introduced a new generative AI offering that integrates both generative and predictive AI capabilities within the DataRobot AI Platform. This end-to-end solution is designed to accelerate the journey from concept to value, allowing users to experiment, build, deploy, monitor, and manage enterprise-grade AI applications effectively.
- October 2023: MicroStrategy Incorporated launched MicroStrategy AI, a product that integrates generative AI into data applications. This innovation simplifies and accelerates data analysis and interaction, making it more accessible and efficient for organizations.
- March 2023: Salesforce unveiled Einstein GPT, the world’s first generative AI CRM technology. This tool delivers AI-generated content across various customer interactions, including sales, service, marketing, commerce, and IT, enhancing customer experiences at scale.
- October 2022: Accenture and Google Cloud expanded their global partnership, focusing on growing talent, enhancing joint capabilities, and developing new solutions using data and AI. This collaboration aims to support clients in building a robust digital infrastructure and transforming their enterprises on the cloud.
- October 2022: Appen partnered with Novatics to enhance their client offerings in Latin America. This collaboration is part of Appen's strategy to provide comprehensive data for the AI lifecycle, with Novatics facilitating connections with key strategic clients in the region.
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