Gitnux/Report 2026

Data Annotation Industry Statistics

See how Data Annotation Industry’s latest measurements show what’s changed fastest for the workforce and budgets behind labeling quality, including the sharp 2025 jump in average annotation rates. If you think costs are rising evenly, the 2025 benchmarks for turnaround time and pricing will challenge that assumption and show where the real pressure is building.
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November 11, 2026Updated
Data Annotation Industry Statistics
James OkoroWritten by James Okoro·Edited by Thomas Lindqvist·Fact-checked by Rebecca Hargrove
Published ·Updated
How this report is researched
01Editorial Scope

Gitnux editors write the brief first: the topic, the inclusion rules, and the frame for what belongs.

02Source Research

Agents search the published record and log every extracted figure back to the passage it came from.

Read our full methodology →

Search agents attach provenance to every extracted figure.

Next review: within 31 days

01 Industry overview

The data annotation industry at a glance

The global data annotation tools market was valued at $1.7 billion in 2025 and is forecast to expand rapidly as generative AI, computer vision and autonomous systems increase demand for labeled data.

$1.7B[16]
Market size, 2025
25.4%[16]
Forecast CAGR, 2026–2033
35.0%[16]
North America share, 2025
$230.8M[49]
Appen revenue, 2025
Market size
The global data annotation tools market was valued at $1.7 billion in 2025. A broader Oxford Economics estimate for data annotation and related services placed global 2024 revenue between $8.2 billion and $15.1 billion, reflecting differences in market scope.[16][33]
Forecast & CAGR
Grand View Research projects the data annotation tools market to reach $10.3 billion by 2033 from an estimated $2.1 billion in 2026, representing a 25.4% CAGR. The Business Research Company forecasts the broader data annotation and labeling market to reach $9.27 billion by 2030 at a 32.8% CAGR.[16][50]
Market share & regions
North America held a 35.0% revenue share of the data annotation tools market in 2025 and was the largest regional market. Asia-Pacific was identified as the fastest-growing region during 2026–2033.[16]
Segmentation
Image and video annotation was the largest type segment in 2025, with more than 36.8% of revenue, while manual annotation accounted for more than 79.1%. The market is also segmented by text and audio data, semi-supervised and automated methods, and end-use sectors including automotive, healthcare, government, information technology and financial services.[16]
Key players & concentration
Public market-share data for individual suppliers is limited. Appen reported $230.8 million in 2025 operating revenue, including $127.9 million from Appen Global and $102.9 million from Appen China; the company said generative-AI work represented 33% of group revenue.[49]
Trends, drivers & challenges
Growth is being driven by generative AI, large language models, computer vision, autonomous systems and demand for higher-quality labeled datasets. Appen reported that generative-AI-related work rose to 33% of group revenue in 2025 from 22% in 2024, while automation and changing project volumes remain important operational challenges.[16][49]
M&A
In June 2025, Meta finalized a $14.3 billion investment for a 49% stake in Scale AI, valuing the data-labeling company at more than $29 billion. The transaction also brought Scale AI chief executive Alexandr Wang to Meta, highlighting competition among major technology companies for AI data and model-development capabilities.[51][52]
Regulation
The EU Artificial Intelligence Act requires providers of AI systems that generate synthetic audio, images, video or text to mark outputs in a machine-readable and detectable format. For systems placed on the market before August 2, 2026, the consolidated regulation sets December 2, 2026 as the compliance deadline for Article 50(2).[53]
Latest news
Appen’s latest reported full-year results, published February 25, 2026, showed 2025 operating revenue of $230.8 million, up 4.5% excluding the impact of the prior Google contract termination. Appen guided to 2026 revenue of $270 million to $300 million.[49]

02 Ranking

Top 10 Companies in the Data Annotation Industry

The leading companies in the data annotation industry, ranked on market impact, performance, momentum, innovation and brand popularity.

Updated November 11, 2026 · Next review December 11, 2026

Verdict

TELUS Digital leads Gitnux's 2026 data annotation ranking with an Overall score of 9.1, with over 6 billion annotations to date. Scale AI is the highest-ranked data engine and evaluation provider at 9.0, with an Data Engine for annotation, data generation, evaluation and alignment.

Ranked by Overall score · How we score ↓

Editor's top 3 picks

Where to start, by need.

  1. #1 Overall · Leader in human annotation services

    TELUS Digital

    CA

    Ranked #1 · 9.1 · Human annotation services

    Why we picked it: TELUS Digital’s AI Community and large-scale annotation volumes support global labeled-data delivery for AI training.

    See in ranking ↓Visit telusdigital.com ↗

  2. Leader in AI data engine & evaluation

    Scale AI

    US

    Ranked #2 · 9.0 · AI data engine & evaluation

    Why we picked it: Scale AI ties annotation outputs to evaluation and alignment services for AI model development.

    See in ranking ↓Visit scale.com ↗

  3. Leader in multilingual labeling & transcription

    TaskUs

    US

    Ranked #4 · 8.9 · Multilingual labeling & transcription

    Why we picked it: TaskUs supports labeling and transcription for machine-learning systems in AI Services.

    See in ranking ↓Visit taskus.com ↗

Pick 1 is the #1 company overall. Picks 2 and 3 are the highest-ranked companies in the top 5 that add a new segment.

Full ranking

Sort by
Top 10 companies in the data annotation industry, 2026 – Gitnux ranking
#CompanyOverall ↓Company snapshot
1

TELUS Digital

Human annotation services · CA

9.1
2

Scale AI

AI data engine & evaluation · US

9.0
3

Surge AI

Human annotation services · US

9.0
4

TaskUs

Multilingual labeling & transcription · US

8.9
5

Appen

Multilingual labeling & transcription · AU

8.8
6

Centific

AI data collection, annotation and model evaluation · US

8.7
7

Innodata

AI data engineering, annotation and model training · US

8.6
8

Sama

Managed computer-vision and multimodal annotation · US

8.5
9

LXT

Multilingual speech, text and image data services · CA

8.3
10

Toloka

Crowdsourced data labeling and AI evaluation · NL

8.2

How we score

  • Impact (30%): scale and weight in the market (revenue, market share, employees, market position).

Popularity (brand search demand, 15%) counts toward Overall but is not published as a column. Overall leaves out what is not known.

Scale Scores are shown on a 7–10 scale with one decimal; bars start at 7.0.

Cadence Recalculated when new figures are published; next review December 11, 2026.

Independence. Rankings are editorially independent. Scores, ranks, picks and the verdict follow the method above; no company can pay to change them.

Cite this ranking

APA

James Okoro. (2026, February 13). Top 10 companies in the data annotation industry. In Data Annotation Industry Statistics. Gitnux. https://gitnux.org/data-annotation-industry-statistics/#top-companies

report visual · Breakdown

Global data annotation and related services market revenue, high estimate

Non-US holds the largest share at $10.1B.

$5.0B
US
$10.1B
Non-US
source-verifiedstatic.scale.com

04 Statistics

Technology & Innovation

US GDP impact is projected at $19.2 billion by 2030, while teams report pain points in identifying worth-labeling samples. Security/privacy, quality/consistency and tooling limitations are also cited in 2026.

AI in the data annotation industry

  • $19.2 billion is the projected US GDP impact of data annotation by 2030.[1]
  • 58% of the world’s AI-training workers were based in the United States in 2025.[2]
  • 7.2% of global AI-training roles were located in India in 2025.[2]
  • 283% was the worldwide increase in demand for AI-training roles in 2025.[2]
  • $2.7–$5.0 billion was the estimated US data annotation market size in 2024.[1]
  • $5.7 billion was the US data annotation industry’s contribution to GDP in 2024.[1]

Automation in the data annotation industry

  • 46% of visual-AI teams struggled to identify which samples were worth labeling in 2026.[3]
  • 24% of visual-AI teams cited security or privacy concerns as an annotation-process pain point in 2026.[3]
  • 58% of visual-AI teams cited annotator quality or consistency as an annotation-process pain point in 2026.[3]
  • 35% of visual-AI teams cited tooling limitations as an annotation-process pain point in 2026.[3]
  • 99% of visual-AI teams described their annotation process as painful in 2026.[3]
  • 65% of visual-AI teams identified annotation cost or speed as their biggest annotation-process pain point in 2026.[3]

Digital Transformation in the software and IT services sector (sector benchmark)

  • 54.8% of surveyed organizations reported having a chief digital officer or another executive responsible for digital transformation.[4]
  • 75% of digital leaders globally planned to increase AI-related business expenditure in 2024.[5]
  • 72% of digital leaders globally expected to increase technology spending in 2024, compared with 50% of digital laggards, according to a survey of 855 technology and business decision-makers.[5]
  • 34% of surveyed organizations globally identified replacing or upgrading legacy technology as a top digital-transformation goal in 2024.[5]
  • 45% of North American technology and business decision-makers planned to adopt AI and machine learning to improve business within 12 to 24 months.[5]

Technology Adoption in the software and IT services sector (sector benchmark)

  • More than 50% of surveyed global IT decision-makers were exploring AI use cases or piloting AI technologies in 2024.[5]
  • 57.7% of surveyed organizations reported having a chief information security officer or equivalent in 2024.[4]
  • 51.8% of surveyed organizations reported that AI solutions were somewhat or extremely rare in 2024.[4]
  • 67.6% of IT services were delivered through cloud infrastructure among surveyed organizations in 2024.[4]

Cloud Computing in the software and IT services sector (sector benchmark)

  • 71.5% of EU enterprises using paid cloud services used them for file storage in 2025.[6]
  • 52.7% of EU enterprises with at least 10 employees used paid cloud-computing services in 2025.[6]
  • 71.7% of EU enterprises using paid cloud services used them for office software in 2025.[6]
  • 26.1% of EU enterprises using paid cloud services used computing platforms for application development, testing or deployment in 2025.[6]
  • 85.2% of EU enterprises using paid cloud services used them for email in 2025.[6]
  • 65.5% of EU enterprises using paid cloud services used them for security software applications in 2025.[6]

Big Data in the software and IT services sector (sector benchmark)

  • 14% of enterprises with at least 10 employees across the OECD used big-data analytics on average, based on 2022 data or the latest available year.[7]
  • 40% was the highest reported enterprise adoption rate for big-data analytics across OECD countries in the latest available data through 2023.[7]
  • 3% was the lowest reported enterprise adoption rate for big-data analytics across OECD countries in the latest available data through 2023.[7]

05 Statistics

Data & Analytics

Measured outcomes appear in customer and model case studies, including 93.8% fact-extraction accuracy and 95.6% coverage-recommendation accuracy. These figures sit alongside large accuracy and quality-structure gaps reported by organizations.

Business intelligence in the data annotation industry

  • More than 80% was the citation-intent-task accuracy reported by the Allen Institute for AI using Appen.[8]
  • Over 10 million papers are covered by the citation-intent feature supported by Appen for Semantic Scholar.[8]
  • 8 million scholars globally use Semantic Scholar each month, according to the Appen case study.[8]
  • More than 100 million citations are classified by the citation-intent feature supported by Appen for Semantic Scholar.[8]

Data analytics in the data annotation industry

  • 93.8% was fact-extraction accuracy after post-training in Scale AI’s global-insurance customer-service copilot.[9]
  • 8.2 mean pixels was the LEAP model’s tracking error on the Johns Hopkins spider-web dataset annotated through Appen.[8]
  • 95.6% was coverage-recommendation accuracy for the post-trained insurance copilot in Scale AI’s case study.[9]
  • 85% or more was EmPushy’s F1 score after its Appen-supported annotation project.[8]
  • 10,000 high-quality annotations were selected for model training in the Johns Hopkins University Appen project.[8]
  • 60% was EmPushy’s F1 score before its Appen-supported annotation project.[8]

Data Quality in the software and IT services sector (sector benchmark)

  • In 2025, 46% of organizations globally said they were fully confident in their data quality, across surveyed technology and business organizations.[10]
  • In 2024, 95% of enterprise data leaders and practitioners reported a data-quality issue with a direct impact on business outcomes, across companies with at least $1 billion in revenue.[11]
  • In 2025, 46% of organizations globally rated their data excellent for accuracy and integrity, across surveyed technology and business organizations.[10]
  • In 2025, 35% of organizations globally rated their data excellent for consistency and standardization, across surveyed technology and business organizations.[10]
  • In 2025, 34% of organizations globally rated their data excellent for relevance and suitability, across surveyed technology and business organizations.[10]
  • In 2025, 43% of organizations globally rated their data excellent for quality and completeness, across surveyed technology and business organizations.[10]

Data Governance in the software and IT services sector (sector benchmark)

  • In 2024, 61% of supply-management organizations reported having a dedicated data-governance function, based on an Institute for Supply Management survey.[12]
  • In 2024, 81.7% of organizations reported having no data-governance or catalog solution as part of their governance program, according to a global governance study.[13]
  • In 2024, 35% of U.S. technology executives prioritized data governance among their data-management areas for the next 12 months.[14]
  • In 2024, 32% of global technology leaders prioritized data governance among their data-management areas for the next 12 months.[14]
  • In 2024, 18.3% of organizations reported having a data-governance or catalog solution as part of their governance program, according to a global governance study.[13]
  • In 2026, 76% of global data leaders said their company’s AI governance did not completely keep pace with employee use of AI technology.[13]

KPIs in the data annotation industry

  • 4.5% of LEAP model tracking errors were at least 25 pixels in the Johns Hopkins University Appen project.[8]
  • $100,000-plus was the reported saving for Charles River Analytics from CloudFactory’s data-labeling solution.[15]
  • 20× was the annotation-speed improvement reported by CloudFactory for Charles River Analytics.[15]
  • 3.3% of DeepLabCut model tracking errors were at least 25 pixels in the Johns Hopkins University Appen project.[8]

06 Statistics

Strategy & Growth

Industry estimates show tools moving from $1.7 billion in 2025 to $2.1 billion in 2026, with Asia-Pacific identified as fastest-growing during 2026–2033. TELUS Digital and Appen report high-volume multilingual and generative-AI-related work shares.

Growth in the data annotation industry

  • The global data-labeling solutions and services market was projected to reach $57.6 billion by 2030, according to Grand View Research.[16]
  • North America represented 33.9% of global data-labeling solutions and services revenue in 2024.[16]
  • The global data-labeling solutions and services market was projected to grow at a 20.3% CAGR from 2025 to 2030.[16]
  • The global data-labeling solutions and services market was valued at $18.6 billion in 2024, according to Grand View Research.[16]
  • The United States data-labeling solutions and services market was expected to grow at a 17.4% CAGR from 2025 to 2030.[16]
  • Asia-Pacific was projected to be the fastest-growing data-labeling region, with a 21.16% CAGR through 2031.[17]

Differentiation in the data annotation industry

  • TELUS Digital supported more than 500 annotation languages and dialects in 2024.[18]
  • A TELUS Digital autonomous-driving project achieved a four-times productivity increase in 60 days in 2026.[18]
  • TELUS Digital reported more than 6 billion annotations completed in 2025.[18]
  • A TELUS Digital autonomous-driving project delivered more than 51 million high-quality labels in 2026.[18]
  • TELUS Digital’s AI Community included more than 1 million annotators, reviewers, linguists and raters in 2025.[18]
  • A TELUS Digital autonomous-driving project reported 99% average recall for outputs in 2026.[18]

Mergers and acquisitions in the data annotation industry

  • TELUS International reported more than 17 years of AI-industry experience built through strategic acquisitions, organic growth and talent recruitment in 2024.[18]
  • Innodata withdrew its non-binding proposal to acquire all Appen shares on March 13, 2024.[19]

Strategic partnerships in the data annotation industry

  • TaskUs and V7 announced a strategic partnership to scale data annotation and enterprise AI-product delivery in 2024.[20]
  • TELUS Digital partnered with the SETU Foundation to train a computer-vision workforce for current and future annotation projects in 2024.[18]
  • The U.S. Department of Defense awarded Scale AI a $99 million contract for AI research and development, including data annotation, in 2025.[9]

07 Statistics

People & Workforce

Workforce supply spans employee and flexible labor, with 9,000 full-time employee jobs supported in the US in 2024 and nearly 200,000 flexible earning opportunities. Pricing and annotation-rate data also vary by task type in 2026.

Hiring in the data annotation industry

  • 19% of AI trainers earned $50–$75 per hour for annotation work in 2025.[2]
  • 9,000 full-time employee jobs were directly supported by the US data annotation industry in 2024.[1]
  • 6% of AI trainers earned more than $100 per hour for specialized work in 2025.[2]
  • Nearly 200,000 flexible earning opportunities were directly supported by the US data annotation industry in 2024.[1]
  • 94% of US data annotators surveyed in 2024 had other work, education, or caregiving responsibilities.[9]

Employee retention in the data annotation industry

  • 94% of US data annotators surveyed in 2024 were engaged in other work, education, or caregiving responsibilities.[1]
  • 65% of US data-annotation contributors were under age 44 in 2024.[9]
  • 91% of US data annotators surveyed in 2024 said flexibility was a core reason for doing the work.[1]

Remote Work in the software and IT services sector (sector benchmark)

  • 48% of U.S. software and IT professionals surveyed worked remotely in 2026, compared with 21% in France.[21]
  • 10% of technology-services respondents worked under fully flexible arrangements in 2025, allowing employees substantial control over remote work.[22]
  • 84% of technology-services employers agreed in 2025 that the ability to work remotely is important for employee retention.[22]
  • 6% of global respondents worked fully remotely in 2025, defined as spending less than one day per week in the office.[22]
  • 34.8% of global software and IT services respondents worked remotely in 2026, according to the Stack Overflow Developer Survey.[21]

Hybrid Work in the software and IT services sector (sector benchmark)

  • 55% of technology-services respondents worked in a hybrid arrangement in 2025, the highest share among industries measured by Cisco.[22]
  • 47% of global respondents worked in hybrid arrangements in 2025, down from 63% in Cisco’s 2022 study.[22]
  • 61% of U.S. employees with remote-capable jobs preferred hybrid work in November 2025, compared with 33% preferring fully remote work.[23]
  • 52% of U.S. employees with remote-capable jobs worked in hybrid arrangements in May 2026, according to Gallup.[23]
  • 56% of IT employees worked in hybrid arrangements in 2025, while 31% were fully remote and 13% attended the office daily.[24]

Upskilling in the data annotation industry

  • Nearly three-quarters of US data annotators surveyed in 2024 hoped to apply their AI skills to future AI and technology roles.[1]
  • 84% of US data annotators surveyed in 2024 held at least a bachelor’s degree.[1]

Employee Engagement in the software and IT services sector (sector benchmark)

  • 54% of exclusively remote U.S. employees were thriving in May 2026, compared with 52% of hybrid employees and 49% of on-site employees with remote-capable jobs.[23]
  • 37% of exclusively remote U.S. employees were engaged in May 2026, compared with 34% of hybrid employees and 29% of on-site employees with remote-capable jobs.[23]
  • 74% of respondents approved of fully flexible hybrid policies in 2025, the highest positive sentiment among the policy types Cisco measured.[22]
  • 22.2% of global software and IT respondents were happy with their current professional role in 2026, while 32.6% were unhappy.[21]
  • 92% of employees ranked collaboration and community as very important aspects of office culture in Cisco’s 2025 global study.[22]

Change Management in the software and IT services sector (sector benchmark)

  • 42% of SAP change-management respondents cited inability to scale change management to business needs as a challenge in 2025.[25]
  • 48% of SAP change-management respondents faced pressure in 2025 to implement changes more quickly.[25]
  • 87% of SAP change-management respondents believed AI would influence change management during the five years following the 2025 survey.[25]
  • 44% of SAP change-management respondents identified requirements gathering as a challenge in 2025.[25]
  • 59% of SAP change-management respondents expected AI to automate manual processes in change management, according to the 2025 survey.[25]

08 Statistics

Customer & Sales

Customer outcomes include churn and satisfaction shifts tied to annotation projects. Examples include TELUS Digital reporting 99.55% recall/precision for a 3D autonomous-vehicle project in 2024.

Customer experience in the data annotation industry

  • Almost 20% was the reported reduction in company-wide churn attributed to improved detection of negative customer-support experiences after Peroptyx’s annotation project.[26]
  • 10% was the increase in contributor satisfaction after Appen automated support-ticket resolution globally in 2025.[27]
  • 99.55% was the recall and precision rate delivered by TELUS Digital for a 3D autonomous-vehicle annotation project in 2024.[18]
  • 30 was the online bank’s net promoter score threshold exceeded across all three markets after Peroptyx’s data-annotation project.[26]
  • 18% was the average recall uplift reported after Peroptyx annotated multilingual customer-support data for an online bank across three markets.[26]

09 Statistics

Marketing & Brand

Marketing-grade reporting intersects annotation mainly through organizational spending plans and influencer-program adoption signals in 2024–2026. For annotation budgets, technology leaders planned increases in AI-related business expenditure in 2024.

Influencer Marketing in the software and IT services sector (sector benchmark)

  • Across B2B companies, 43% of marketers reported outstanding results from their influencer programs in the 2025 B2B Influencer Marketing Report.[28]
  • Across B2B companies, another 29% of marketing organizations planned to adopt influencer marketing within the next year in 2025, based on an Ipsos survey of 1,500 marketing leaders.[29]
  • Across technology companies, 27% of marketers reported dedicated but flat budgets for creator or influencer marketing in 2026, according to Nielsen’s global marketing survey.[30]
  • Across B2B companies, 55% of marketing organizations were using influencers in 2025, based on an Ipsos survey of 1,500 marketing leaders.[29]
  • Across B2B companies, 58% of marketing teams reported using an always-on influencer marketing approach in the 2025 B2B Influencer Marketing Report.[28]

10 Statistics

Operations & Execution

Operational constraints dominate reported adoption outcomes: 65% cite cost and speed as top concerns in 2026, while 46% struggle to identify which samples are worth labeling. Managed-labeling service delivery is also tied to one week to one month windows.

Process optimization in the data annotation industry

  • 65% of surveyed organizations identify cost and speed as their top data-annotation concerns in 2026.[3]
  • 34% of surveyed organizations are satisfied with their data-annotation process in 2026.[3]
  • 46% of surveyed organizations struggle to identify which samples are worth labeling in 2026.[3]
  • 40% of organizations using managed labeling services receive high-quality labeled data within one week to one month, according to a 2024 survey.[31]
  • 1,200 visual-language tasks were collected for a Scale AI evaluation dataset, with 758 tasks passing quality-control checks.[32]

Operational efficiency in the data annotation industry

  • 25,000 full-time jobs were supported through the U.S. data-annotation industry's supply-chain and worker-spending effects in 2024.[1]
  • 9,000 additional full-time jobs were directly supported by the U.S. data-annotation industry in 2024.[33]
  • 91% of surveyed U.S. annotators cited flexibility as a core reason for doing data-annotation work.[1]
  • 200,000 flexible earning opportunities were directly supported by the U.S. data-annotation industry in 2024.[1]
  • 94% of surveyed U.S. annotators said supplemental earnings attracted them to data-annotation opportunities.[1]

Quality management in the data annotation industry

  • Approximately 20% of MTurk image annotations were classified as spam in an ECCV 2024 comparison with annotation companies.[34]
  • 1200 tasks formed the Scale AI visual-language dataset, of which 758 passed quality-control checks.[32]
  • 58% of surveyed physical-AI organizations reported difficulty maintaining annotation quality and consistency in 2026.[3]
  • Four annotation companies used an additional quality-assurance annotation round in an ECCV 2024 image-labeling experiment.[34]
  • 61.1% lower median cost accompanied higher annotation quality for professional annotation companies versus MTurk in the study.[34]

Supply chain in the data annotation industry

  • 25,000 full-time jobs were supported through the U.S. data-annotation industry's suppliers and worker spending in 2024.[1]
  • 26.6% of the open data-annotation roles on October 17, 2026, were listed by Welo Data.[35]
  • $2.1 billion of the U.S. data-annotation industry's 2024 GDP contribution came through its direct operating channel.[33]
  • $3.6 billion of the U.S. data-annotation industry's $5.7 billion GDP contribution in 2024 came through indirect and induced channels.[33]
  • $1.2 billion in federal, state and local tax revenue was generated by U.S. data-annotation activity in 2024.[1]

Outsourcing / Offshoring in the software and IT services sector (sector benchmark)

  • Across EU enterprises sourcing business functions internationally during 2021–2023, 28.7% moved information and communication technology services abroad.[6]
  • Across German digital-experience service providers, 13.2% of services for customer projects were delivered nearshore in 2024.[36]
  • Among German IT-service generalists, 10.2% of digital-experience services for customer projects were delivered offshore in 2024.[36]
  • Across European organizations, 35% planned to increase their use of nearshore outsourcing in the 2024/2025 sourcing study.[37]
  • Among German IT-service generalists, 19.5% of digital-experience services for customer projects were delivered nearshore in 2024.[36]

11 Statistics

Finance & Pricing

Listed 2026 rates show expert work at $81.51 per hour and medical/clinical annotation at $4.40 per record. Time-savings examples include $4,200 saved in a NIST human-in-the-loop technical-document case.

Pricing strategy in the data annotation industry

  • $81.51 per hour was the listed market rate for expert data and annotation work in a 2026 price tracker.[38]
  • $4.40 per record was the listed 2026 market rate for medical and clinical data annotation.[38]
  • $3.83 per square kilometer was the listed 2026 market rate for geospatial AI-training data.[38]
  • $65 per hour was the median advertised rate for all AI-training roles in the same October 2026 dataset.[35]
  • 54% lower was the median advertised data-annotation rate than the median rate for all AI-training work in October 2026.[35]

Cost reduction in the data annotation industry

  • $36 per hour was the effective wage calculated for the annotator in the NIST example after time savings.[39]
  • 24.5% of MTurk cost was the low end of the cost range reported for professional annotation companies doing the same image-labeling work.[34]
  • $4,200 in time value was saved in a NIST human-in-the-loop technical-document annotation example.[39]
  • 20% was the approximate spam share for MTurk images in the professional-annotation-company comparison.[34]
  • 5 weeks was the annotation time in the NIST example, compared with 12 weeks without the described human-in-the-loop approach.[39]

Profitability in the data annotation industry

  • $10.3 billion to $19.0 billion was the projected U.S. data-annotation market size for 2030.[1]
  • $5.7 billion was the estimated total contribution of the U.S. data-annotation industry to GDP in 2024.[1]
  • $2.7 billion to $5.0 billion was the estimated U.S. data-annotation market size in 2024.[33]
  • $214 million was TaskUs's FY2025 AI Services revenue, equal to 18.1% of company revenue.[35]
  • $252 million was Innodata's FY2025 revenue, representing 47.6% growth according to an industry revenue compilation based on company filings.[35]

Financial planning in the data annotation industry

  • $19.2 billion was the projected total GDP contribution of the U.S. data-annotation industry in 2030.[33]
  • $27 million was TaskUs's projected 2028 capital expenditure in an accelerated-AI-impact planning case.[40]
  • $62 million was TaskUs's projected 2025 capital expenditure in one management planning case.[40]
  • $1.2 billion was the estimated federal, state and local tax contribution generated by the U.S. data-annotation industry in 2024.[1]
  • 5% of revenue was TaskUs's projected capital-expenditure ratio for 2025 in one management planning case.[40]

12 Statistics

Product & Service

Image and video annotation is the largest tools segment, at more than 36.8% of 2025 revenue, with manual annotation at more than 79.1%. Multiple case studies quantify speed and error-rate changes after tool adoption.

Product development in the data annotation industry

  • 36.8% or more was the 2025 global revenue share of image/video annotation tools.[16]
  • $242.5 million was United States data-annotation-tools revenue in 2023.[16]
  • 22.9% is the projected United States data-annotation-tools CAGR from 2024 to 2030.[16]
  • $1.7 billion was the global data-annotation-tools market size in 2025.[16]
  • $2.1 billion is the estimated global data-annotation-tools market size for 2026.[16]

Product lifecycle in the data annotation industry

  • 5× was VirtuSense’s increase in training data created after adopting Labelbox.[41]
  • 20× was the increase in image-labeling speed achieved by Charles River Analytics with CloudFactory.[15]
  • More than 1 million evaluated assets were produced by VirtuSense after deploying its Labelbox data engine.[41]
  • More than 20% was VirtuSense’s reported increase in average model accuracy after adopting Labelbox.[41]
  • 28% to 6% was VirtuSense’s reduction in false-alarm rates after adopting Labelbox.[41]

After-sales in the data annotation industry

  • 95.6% was coverage-recommendation performance for the post-trained insurance copilot.[9]
  • 70% to 75% was the approximate inference-cost reduction versus the production model in Scale AI’s insurance copilot.[9]
  • Almost 20% was the reported reduction in company-wide customer churn after a bank used Peroptyx-annotated support data.[26]
  • 62.6% was the production model’s fact-extraction accuracy in Scale AI’s insurance copilot comparison.[9]
  • Under $1,000 was the training-compute cost per task reported for Scale AI’s insurance copilot.[9]

Value proposition in the data annotation industry

  • 223,000 judgments were collected in Appen’s EmPushy data-annotation projects.[8]
  • 48% was the reduction in Dialpad’s per-data-point labeling cost after switching to Labelbox.[41]
  • More than 200,000 campaigns were captured in Appen’s EmPushy annotation projects.[8]
  • 20% was Dialpad’s improvement in training-signal quality after switching to Labelbox.[41]
  • 41% was Dialpad’s reduction in costs required to generate high-quality signals for model improvement.[41]

13 Statistics

Sustainability & Ethics

Sustainability disclosures appear alongside pay and attrition metrics, including Sama’s 4% reported annual attrition rate and Appen’s 2030 net-zero target. Several health-impact shares come from annotator surveys in 2025.

Sustainability in the data annotation industry

  • $1.6 billion was the indirect GDP contribution generated through the US data annotation industry’s supply chain in 2024.[33]
  • 9,000 additional full-time jobs were directly supported by the US data annotation industry in 2024.[33]
  • $5.7 billion was the data annotation industry’s estimated contribution to US GDP in 2024.[33]
  • $1.2 billion in total tax revenue was supported by the US data annotation industry in 2024.[33]
  • 200,000+ earning opportunities were directly supported by the US data annotation industry in 2024.[33]

ESG in the data annotation industry

  • 2030 is Appen’s target year for achieving net-zero emissions across its business under its Net Zero Roadmap.[8]
  • 1 million+ skilled contractors worldwide are included in Appen’s ESG-related workforce model.[8]
  • 70 cents per dollar was the pre-Sama average earned by female workers in Sama’s global delivery centers compared with male workers.[42]
  • 60% more was earned on average by women trained and included in Sama’s hiring pool than by women in the control group, according to an MIT study.[42]

Ethics in the data annotation industry

  • 4% was Sama’s reported annual attrition rate across its workforce in its updated ethical-sourcing disclosure.[42]
  • 25% of surveyed data annotators reported a positive mental-health impact from data work in 2025.[43]
  • 93% of surveyed US data annotators cited the ability to set their own hours as a motivation for annotation work in 2025.[33]
  • 27% of surveyed data annotators reported a negative mental-health impact from data work in 2025.[43]
  • 9% of surveyed data workers reported a positive physical-health impact from data work in 2025.[43]

CSR in the data annotation industry

  • 2 times the living wage was the pay level Sama reported for content-moderation employees in Kenya.[42]
  • 2.2 times was the average increase in earnings reported for new Sama team members joining in 2022.[42]
  • 4% or less of Sama’s business was content moderation before the company ended its last moderation contract in March 2023.[42]
  • 3 times the minimum wage was the pay level Sama reported for content-moderation employees in Kenya.[42]

15 Statistics

Globalization & Expansion

Global delivery scale is quantified through locale reach and annotation volumes, including TELUS Digital’s network covering 450 locales in 2024 and more than 2 billion labels annually through services in 2024.

Globalization in the data annotation industry

  • More than 1 million AI Community members supported TELUS Digital’s data services across more than 450 global locales in 2025.[18]
  • $8.2 billion to $15.1 billion was the estimated global data-annotation and related-services market in 2024.[33]
  • $2.7 billion to $5.0 billion of the global data-annotation market was captured by the United States in 2024.[33]
  • TELUS Digital operated secure in-facility data-collection capabilities across 32 countries in 2024.[18]
  • TELUS Digital’s AI Community covered more than 500 languages and dialects across approximately 150 countries in 2023.[18]

Cultural adaptation in the data annotation industry

  • 660,000 language prompts were included in a TELUS Digital multilingual dataset project.[18]
  • 31 languages across various locales were included in a TELUS Digital multilingual dataset project.[18]
  • 650 language professionals contributed to a TELUS Digital multilingual dataset project.[18]
  • 40.7% of language-service providers surveyed by Nimdzi offered cultural adaptation services in 2026.[48]
  • 3.5 million language tasks were completed in a TELUS Digital multilingual dataset project.[18]

Supplier management in the data annotation industry

  • More than 1 million TELUS Digital AI Community members supplied contributors for annotation and data-collection projects in 2024.[18]
  • More than 50,000 advanced-degree holders were part of TELUS Digital’s AI-training community in 2026.[18]
  • TELUS Digital used managed-crowd, remote, secure in-facility and hybrid workforce models for AI-data delivery in 2024.[18]

Stakeholder management in the data annotation industry

  • TELUS Digital’s AI data services covered more than 20 domains, including automotive, coding, STEM, logic and reasoning, in 2025.[18]
  • TELUS Digital delivered more than 2 billion labels annually through its data-annotation services in 2024.[18]
  • Approximately 50,000 TELUS Digital AI-training contributors held advanced degrees in STEM, healthcare, law or finance in 2026.[18]
  • TELUS Digital had about 77 AI-enablement clients across foundation-model, telecom, consumer-electronics, robotics, automotive, travel, fintech and healthcare sectors in 2026.[18]

Distribution channels in the data annotation industry

  • TELUS Digital’s data-collection network covered 450 locales globally in 2024.[18]
  • TELUS Digital operated data-collection facilities across 32 countries and extended reach through a global partner network in 2024.[18]
  • TELUS Digital delivered AI-data services through more than 1 million global annotators and linguists in 2024.[18]

Key questions about the Data Annotation Industry

How big is the data annotation tools market in 2025 and 2026?
The global data annotation tools market was valued at $1.7 billion in 2025. A broader estimate places global 2024 revenue between $8.2 billion and $15.1 billion for data annotation and related services. Grand View Research projects $2.1 billion for 2026.
What is the expected market growth for 2026–2033?
The global data annotation tools market is forecast to expand at a 25.4% CAGR from 2026 to 2033. Grand View Research projects the market to reach $10.3 billion by 2033 from $2.1 billion in 2026.
Which companies lead the data annotation industry?
TELUS Digital leads Gitnux's 2026 data annotation ranking with an Overall score of 9.1, with over 6 billion annotations to date. Scale AI is the highest-ranked data engine and evaluation provider at 9.0, with an Data Engine for annotation, data generation, evaluation and alignment.
Which technology shifts are most tied to annotation demand?
Generative AI, large language models, computer vision and autonomous systems are cited as growth drivers for higher-quality labeled datasets. Synthetic data also complements labeling, with 40% of visual-AI teams using synthetic data for training in 2026.
How is the market structured for tools versus services?
The market is segmented by image and video annotation, text and audio data, and manual versus automated methods. Public supplier market-share data is limited, while company-reported revenue data (for example Appen’s $230.8 million operating revenue in 2025) is used for concentration context.
What compliance requirements shape annotation provenance in 2026?
The EU Artificial Intelligence Act requires machine-readable and detectable marking for synthetic audio, images, video or text outputs. For systems placed on the market before August 2, 2026, the compliance deadline for Article 50(2) is December 2, 2026.
Reference

Cite This Report

This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.

APA
James Okoro. (2026, February 13). Data Annotation Industry Statistics. Gitnux. https://gitnux.org/data-annotation-industry-statistics
MLA
James Okoro. "Data Annotation Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/data-annotation-industry-statistics.
Chicago
James Okoro. 2026. "Data Annotation Industry Statistics." Gitnux. https://gitnux.org/data-annotation-industry-statistics.

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