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市场调查报告书
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2021755

2034年教育领域人工智慧市场预测：按组件、技术、部署模式、应用、最终用户和地区分類的全球分析

AI in Education Market Forecasts to 2034 - Global Analysis By Component (Solutions and Services), Technology, Deployment Mode, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，预计到 2026 年，全球教育领域的 AI 市场规模将达到 45 亿美元，并在预测期内以 25.5% 的复合年增长率增长，到 2034 年将达到 280 亿美元。

在教育领域，人工智慧利用机器学习和智慧演算法来优化学习和教学。这使得每个学生都能获得个人化的学习体验，简化了行政工作，促进了自适应教学，并从教育资料中提取有价值的资讯。透过识别模式和预测学习进度，人工智慧帮助教育者量身定制课程，提高学生的学习动力，并改善学习成果。这些科技的融合促进了各种教育环境中更有效率、更便利、更有效的教育。

个人化学习和市场成长

传统的、千篇一律的教学模式往往无法满足学生的个人需求，导致学习动机下降和学业差距扩大。人工智慧驱动的自适应学习平台能够即时分析学生的学习表现、学习风格和学习进度，提供客製化的学习内容、练习题和补习路径。这种个别化教学能够提高知识保留率和学业成绩。此外，教师还可以利用实用的仪錶板来识别学习困难的学生，以便及时介入。随着全球教育体係向以学生为中心的模式转型，人工智慧驱动的个人化工具的应用正在加速，推动市场成长并变革课堂教学。

实施过程中的挑战以及对资料安全的担忧

实施人工智慧解决方案需要对云端基础设施、软体授权和教师培训进行大量投资，这对开发中地区资金不足的学校和教育机构构成重大挑战。此外，人工智慧系统会收集大量敏感的学生数据，包括学业成绩、行为模式和生物识别资讯。诸如《小规模的教育机构可能缺乏足够的网路安全资源，这可能会限制其市场扩张，因为它们会因此而对采用人工智慧犹豫不决。

创新应用与成长机会

生成式人工智慧模式可以创建客製化的课程计画、测验、互动模拟，甚至完整的学习材料，从而减轻教师的工作负担。由自然语言处理（NLP）驱动的虚拟助教提供全天候的学生支持，解答疑问并协助完成作业。此外，人工智慧监考解决方案在线上考试中日益受到关注，确保了学术诚信。随着混合式和远距学习模式的日益普及，学校和大学都在寻求高度扩充性的人工智慧工具。那些能够提供价格合理、安全可靠且用户友好的生成式人工智慧解决方案的早期采用者，将在未来几年获得显着的市场份额。

偏见、过度依赖和监管风险

演算法偏见和过度依赖自动化带来的风险对教育领域的人工智慧构成严重威胁。基于存在偏见的历史资料训练的人工智慧模型可能会无意中偏袒某些学生群体，从而导致不公平的评分和不均衡的学习建议。例如，自然语言处理演算法可能会误解非母语人士的语音模式，进而对学生造成不公平的劣势。此外，在评分和个别辅导中过度依赖人工智慧可能会减少对社交和情感发展至关重要的人际互动。如果没有持续的审核和纠正，存在偏见或缺陷的人工智慧系统会损害教育的公平性和品质。此类失误可能导致监管机构的强烈反对、诉讼以及公众对教育机构信任度的下降。

新冠疫情的感染疾病：

新冠疫情大大加速了人工智慧在教育领域的应用，全球学校纷纷转向远距教学。封锁措施迫使教育机构探索用于线上授课、自动监考和追踪学生学习进度的数位化工具。人工智慧平台使教师能够管理大规模虚拟课堂，聊天机器人则处理日常咨询。然而，由于部分弱势学生缺乏设备和网路接入，数位落差问题也日益凸显。学校重新开放后，混合式学习模式依然存在，持续推动对人工智慧分析和个人化学习解决方案的需求。政府加大对教育科技的投入，以及许多教育机构将人工智慧视为必需品而非可选项，正在为市场创造长期发展动力。

在预测期内，解决方案领域预计将占据最大的市场份额。

解决方案领域，尤其是智慧辅导系统 (ITS) 和学习分析仪錶盘，预计将占据最大的市场份额。这些软体平台构成了人工智慧主导个人化教学的核心，为教育工作者提供即时自适应学习路径和预测分析。对可衡量的学生进展追踪和自动化内容交付的迫切需求推动了这一领域的领先地位。随着中小学和高等教育机构逐步推动课程数位化，对综合人工智慧解决方案的投资仍然是一项重要的支出项目，超过了服务业。

在预测期内，生成式人工智慧细分市场预计将呈现最高的复合年增长率。

在预测期内，生成式人工智慧领域预计将呈现最高的成长率。生成式模型能够创建原创的课程规划、评估问题和互动式模拟，从而显着缩短内容开发时间。诸如 ChatGPT for Education 等用户友好型工具的出现，以及对客製化学习材料日益增长的需求，正在加速其应用。此外，生成式人工智慧还支援能够进行自然对话的虚拟教学助手，这使其对那些寻求扩充性的全天候学生支援而无需额外人员配备的教育机构极具吸引力。

市占率最大的地区：

在预测期内，北美预计将占据最大的市场份额。这主要得益于该地区早期对数位化学习技术的应用、对教育科技的巨额投资，以及IBM、微软和谷歌等领先的人工智慧供应商的存在。该地区资金雄厚的学区和大学正在积极采用人工智慧技术进行个人化学习和自动评分。此外，政府对STEM教育的支持以及强大的云端基础设施也促进了人工智慧技术的广泛应用。

复合年增长率最高的地区：

在预测期内，亚太地区预计将呈现最高的复合年增长率，这主要得益于中国、印度和东南亚教育科技产业的快速扩张。世界各国政府正在推出大规模的数位化教育项目，例如印度的「DIKSHA」和中国的「智慧教育倡议」。智慧型手机普及率的提高、网路价格的下降以及庞大的学生群体，正在推动对人工智慧驱动的个人化辅导和语言学习解决方案的需求，使亚太地区成为成长最快的市场。

免费客製化服务：

所有购买此报告的客户均可享受以下免费自订选项之一：

  • 企业概况
    • 对其他市场参与者（最多 3 家公司）进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域细分
    • 应客户要求，我们提供主要国家和地区的市场估算和预测，以及复合年增长率（註：需进行可行性检查）。
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    • 根据产品系列、地理覆盖范围和策略联盟对主要企业进行基准分析。

目录

第一章执行摘要

  • 市场概览及主要亮点
  • 驱动因素、挑战与机会
  • 竞争格局概述
  • 战略洞察与建议

第二章：研究框架

  • 研究目标和范围
  • 相关人员分析
  • 研究假设和限制
  • 调查方法

第三章 市场动态与趋势分析

  • 市场定义与结构
  • 主要市场驱动因素
  • 市场限制与挑战
  • 投资成长机会和重点领域
  • 产业威胁与风险评估
  • 技术与创新展望
  • 新兴市场/高成长市场
  • 监管和政策环境
  • 新冠疫情的影响及復苏前景

第四章：竞争环境与策略评估

  • 波特五力分析
    • 供应商的议价能力
    • 买方的议价能力
    • 替代品的威胁
    • 新进入者的威胁
    • 竞争公司之间的竞争
  • 主要企业市占率分析
  • 产品基准评效和效能比较

第五章：全球教育领域人工智慧市场：按组件划分

  • 解决方案
    • 智慧辅导系统
    • 学习分析和仪錶板
    • 人工智慧驱动的学习管理系统（LMS）
    • 人工智慧驱动的评估和评分工具
    • 聊天机器人和虚拟教学助手
  • 服务
    • 咨询和策略服务
    • 託管服务
    • 整合和配置服务
    • 培训和支援服务

第六章：全球教育领域人工智慧市场：按技术划分

  • 机器学习（ML）
  • 自然语言处理（NLP）
  • 深度学习
  • 电脑视觉
  • 语音辨识
  • 人工智慧世代
  • 其他技术

第七章：全球教育人工智慧市场：依部署模式划分

  • 基于云端的
  • 现场

第八章：全球教育领域人工智慧市场：按应用领域划分

  • 个人化学习与自适应学习
  • 自动评分和回馈
  • 智慧辅导与虚拟指导
  • 学生参与度和留存率分析
  • 课程设计与教案设计
  • 行政任务自动化
  • 考试监督和考试公平性
  • 其他用途

第九章：全球教育领域人工智慧市场：按最终用户划分

  • K-12教育
  • 高等教育
  • 职业培训和企业培训
  • 特殊教育
  • 语言学习中心

第十章：全球教育领域人工智慧市场：按地区划分

  • 北美洲
    • 我们
    • 加拿大
    • 墨西哥
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 荷兰
    • 比利时
    • 瑞典
    • 瑞士
    • 波兰
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 韩国
    • 澳洲
    • 印尼
    • 泰国
    • 马来西亚
    • 新加坡
    • 越南
    • 其他亚太国家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥伦比亚
    • 智利
    • 秘鲁
    • 其他南美国家
  • 世界其他地区（RoW）
    • 中东
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 卡达
      • 以色列
      • 其他中东国家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲国家

第十一章 策略市场资讯

  • 工业价值网络和供应链评估
  • 空白区域和机会地图
  • 产品演进与市场生命週期分析
  • 通路、经销商和打入市场策略的评估

第十二章 产业趋势与策略倡议

  • 併购
  • 伙伴关係、联盟和合资企业
  • 新产品发布和认证
  • 扩大生产能力和投资
  • 其他策略倡议

第十三章：公司简介

  • Coursera
  • Duolingo
  • Udemy
  • Pearson
  • Google
  • Microsoft
  • IBM
  • Carnegie Learning
  • Century Tech
  • Cognii
  • Squirrel AI
  • Knewton
  • Querium Corporation
  • Nuance Communications
  • OpenAI
Product Code: SMRC35026

According to Stratistics MRC, the Global AI in Education Market is accounted for $4.5 billion in 2026 and is expected to reach $28.0 billion by 2034 growing at a CAGR of 25.5% during the forecast period. AI in education involves leveraging machine learning and intelligent algorithms to optimize learning and teaching. It personalizes student experiences, streamlines administrative work, delivers adaptive tutoring, and generates insights from educational data. By identifying patterns and predicting progress, AI supports educators in tailoring lessons, improving student engagement, and enhancing learning outcomes. This integration of technology fosters more efficient, accessible, and effective education for learners in various academic settings.

Market Dynamics:

Driver:

Personalized Learning and Market Growth

Traditional one-size-fits-all instructional models often fail to address individual student needs, leading to disengagement and learning gaps. AI-powered adaptive learning platforms analyze real-time student performance, learning styles, and pace to deliver customized content, practice exercises, and remediation pathways. This personalization improves knowledge retention and academic outcomes. Additionally, teachers benefit from actionable dashboards that highlight struggling students, enabling timely intervention. As education systems globally shift toward student-centric models, the adoption of AI-driven personalization tools accelerates, driving market growth and transforming classroom dynamics.

Restraint:

Adoption Challenges and Data Security Concerns

Deploying AI solutions requires substantial investment in cloud infrastructure, software licenses, and teacher training, which is challenging for underfunded schools and institutions in developing regions. Furthermore, AI systems collect vast amounts of sensitive student data, including academic records, behavioral patterns, and biometric information. Strict regulations like FERPA and GDPR mandate robust data protection measures. Any breach or misuse can lead to legal liabilities and loss of trust. Smaller educational institutions may lack cybersecurity resources, making them hesitant to adopt AI, thereby limiting market expansion.

Opportunity:

Innovative Applications and Growth Opportunities

Generative AI models can create customized lesson plans, quizzes, interactive simulations, and even entire course materials, reducing teacher workload. Virtual teaching assistants powered by NLP provide 24/7 student support, answering questions and guiding homework. Additionally, AI-enabled proctoring solutions are gaining traction for online examinations, ensuring academic integrity. As hybrid and remote learning models become permanent fixtures, schools and universities are seeking scalable AI tools. Early adopters offering affordable, secure, and user-friendly generative AI solutions will capture substantial market share in the coming years.

Threat:

Bias, Over-Reliance, and Regulatory Risks

Risk of algorithmic bias and over-reliance on automation poses a serious threat to AI in education. AI models trained on biased historical data may unintentionally favor certain student demographics, leading to unfair assessments or unequal learning recommendations. For example, language processing algorithms may misinterpret non-native speech patterns, penalizing students unfairly. Moreover, excessive dependence on AI for grading and tutoring could reduce human interaction, which is critical for socio-emotional development. If not continuously audited and corrected, biased or flawed AI systems can undermine educational equity and quality. Such failures could trigger regulatory backlash, lawsuits, and decreased institutional confidence.

Covid-19 Impact:

The COVID-19 pandemic dramatically accelerated AI adoption in education as schools worldwide shifted to remote learning. Lockdowns forced institutions to seek digital tools for online instruction, automated proctoring, and student engagement tracking. AI-powered platforms enabled teachers to manage large virtual classrooms, while chatbots handled routine queries. However, the digital divide became evident, with disadvantaged students lacking devices or internet access. As schools reopened, hybrid learning models persisted, sustaining demand for AI analytics and personalized learning solutions. Governments increased ed-tech funding, and many institutions now view AI as essential rather than optional, creating long-term market momentum.

The solutions segment is expected to be the largest during the forecast period

The solutions segment, particularly intelligent tutoring systems and learning analytics dashboards, is expected to account for the largest market share. These software platforms form the core of AI-driven personalization, providing real-time adaptive learning paths and predictive analytics for educators. The essential need for measurable student progress tracking and automated content delivery drives this dominance. As K-12 and higher education institutions digitize curricula, investment in comprehensive AI solutions remains the primary expenditure, outpacing services.

The generative AI segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the generative AI segment is predicted to witness the highest growth rate. Generative models create original lesson plans, assessment questions, and interactive simulations, drastically reducing content development time. The emergence of user-friendly tools like ChatGPT for education, along with rising demand for customized learning materials, accelerates adoption. Generative AI also powers virtual teaching assistants capable of natural conversations, appealing to institutions seeking scalable, 24/7 student support without additional hiring.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, driven by early adoption of digital learning technologies, substantial ed-tech investments, and presence of major AI vendors like IBM, Microsoft, and Google. The region's well-funded school districts and universities readily implement AI for personalized learning and automated grading. Additionally, supportive government initiatives for STEM education and robust cloud infrastructure contribute to high adoption rates.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, fueled by rapidly expanding education technology sectors in China, India, and Southeast Asia. Governments are launching large-scale digital education programs, such as India's DIKSHA and China's Smart Education initiative. Increasing smartphone penetration, affordable internet, and a vast student population drive demand for AI-powered tutoring and language learning solutions, positioning APAC as the fastest-growing market.

Key players in the market

Some of the key players in AI in Education Market include Coursera, Duolingo, Udemy, Pearson, Google, Microsoft, IBM, Carnegie Learning, Century Tech, Cognii, Squirrel AI, Knewton, Querium Corporation, Nuance Communications, and OpenAI.

Key Developments:

In April 2026, IBM announced a strategic collaboration with Pearson to develop AI-powered tutoring systems that help higher education institutions deliver personalized learning pathways with greater flexibility and real-time analytics. IBM's leadership in hybrid cloud and AI has enabled scalable, secure solutions for mission-critical academic workloads.

In March 2026, NVIDIA and Duolingo announced a strategic partnership to optimize large language models for language learning, offering users more natural conversational practice and real-time pronunciation feedback. The companies will also collaborate on edge AI solutions for offline language tutoring applications.

Components Covered:

  • Solutions
  • Services

Technologies Covered:

  • Machine Learning (ML)
  • Natural Language Processing (NLP)
  • Deep Learning
  • Computer Vision
  • Speech Recognition
  • Generative AI
  • Other Technologies

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises

Applications Covered:

  • Personalized Learning & Adaptive Learning
  • Automated Grading & Feedback
  • Intelligent Tutoring & Virtual Mentoring
  • Student Engagement & Retention Analytics
  • Curriculum Design & Lesson Planning
  • Administrative Automation
  • Proctoring & Exam Integrity
  • Other Applications

End Users Covered:

  • K-12 Education
  • Higher Education
  • Vocational & Corporate Training
  • Special Education
  • Language Learning Centers

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2032 and 2034
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI in Education Market, By Component

  • 5.1 Solutions
    • 5.1.1 Intelligent Tutoring Systems
    • 5.1.2 Learning Analytics & Dashboards
    • 5.1.3 Learning Management Systems (LMS) with AI
    • 5.1.4 AI-Based Assessment & Grading Tools
    • 5.1.5 Chatbots & Virtual Teaching Assistants
  • 5.2 Services
    • 5.2.1 Consulting & Strategy Services
    • 5.2.2 Managed Services
    • 5.2.3 Integration & Deployment Services
    • 5.2.4 Training & Support Services

6 Global AI in Education Market, By Technology

  • 6.1 Machine Learning (ML)
  • 6.2 Natural Language Processing (NLP)
  • 6.3 Deep Learning
  • 6.4 Computer Vision
  • 6.5 Speech Recognition
  • 6.6 Generative AI
  • 6.7 Other Technologies

7 Global AI in Education Market, By Deployment Mode

  • 7.1 Cloud-Based
  • 7.2 On-Premises

8 Global AI in Education Market, By Application

  • 8.1 Personalized Learning & Adaptive Learning
  • 8.2 Automated Grading & Feedback
  • 8.3 Intelligent Tutoring & Virtual Mentoring
  • 8.4 Student Engagement & Retention Analytics
  • 8.5 Curriculum Design & Lesson Planning
  • 8.6 Administrative Automation
  • 8.7 Proctoring & Exam Integrity
  • 8.8 Other Applications

9 Global AI in Education Market, By End User

  • 9.1 K-12 Education
  • 9.2 Higher Education
  • 9.3 Vocational & Corporate Training
  • 9.4 Special Education
  • 9.5 Language Learning Centers

10 Global AI in Education Market, By Geography

  • 10.1 North America
    • 10.1.1 United States
    • 10.1.2 Canada
    • 10.1.3 Mexico
  • 10.2 Europe
    • 10.2.1 United Kingdom
    • 10.2.2 Germany
    • 10.2.3 France
    • 10.2.4 Italy
    • 10.2.5 Spain
    • 10.2.6 Netherlands
    • 10.2.7 Belgium
    • 10.2.8 Sweden
    • 10.2.9 Switzerland
    • 10.2.10 Poland
    • 10.2.11 Rest of Europe
  • 10.3 Asia Pacific
    • 10.3.1 China
    • 10.3.2 Japan
    • 10.3.3 India
    • 10.3.4 South Korea
    • 10.3.5 Australia
    • 10.3.6 Indonesia
    • 10.3.7 Thailand
    • 10.3.8 Malaysia
    • 10.3.9 Singapore
    • 10.3.10 Vietnam
    • 10.3.11 Rest of Asia Pacific
  • 10.4 South America
    • 10.4.1 Brazil
    • 10.4.2 Argentina
    • 10.4.3 Colombia
    • 10.4.4 Chile
    • 10.4.5 Peru
    • 10.4.6 Rest of South America
  • 10.5 Rest of the World (RoW)
    • 10.5.1 Middle East
      • 10.5.1.1 Saudi Arabia
      • 10.5.1.2 United Arab Emirates
      • 10.5.1.3 Qatar
      • 10.5.1.4 Israel
      • 10.5.1.5 Rest of Middle East
    • 10.5.2 Africa
      • 10.5.2.1 South Africa
      • 10.5.2.2 Egypt
      • 10.5.2.3 Morocco
      • 10.5.2.4 Rest of Africa

11 Strategic Market Intelligence

  • 11.1 Industry Value Network and Supply Chain Assessment
  • 11.2 White-Space and Opportunity Mapping
  • 11.3 Product Evolution and Market Life Cycle Analysis
  • 11.4 Channel, Distributor, and Go-to-Market Assessment

12 Industry Developments and Strategic Initiatives

  • 12.1 Mergers and Acquisitions
  • 12.2 Partnerships, Alliances, and Joint Ventures
  • 12.3 New Product Launches and Certifications
  • 12.4 Capacity Expansion and Investments
  • 12.5 Other Strategic Initiatives

13 Company Profiles

  • 13.1 Coursera
  • 13.2 Duolingo
  • 13.3 Udemy
  • 13.4 Pearson
  • 13.5 Google
  • 13.6 Microsoft
  • 13.7 IBM
  • 13.8 Carnegie Learning
  • 13.9 Century Tech
  • 13.10 Cognii
  • 13.11 Squirrel AI
  • 13.12 Knewton
  • 13.13 Querium Corporation
  • 13.14 Nuance Communications
  • 13.15 OpenAI

List of Tables

  • Table 1 Global AI in Education Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI in Education Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI in Education Market Outlook, By Solutions (2023-2034) ($MN)
  • Table 4 Global AI in Education Market Outlook, By Intelligent Tutoring Systems (2023-2034) ($MN)
  • Table 5 Global AI in Education Market Outlook, By Learning Analytics & Dashboards (2023-2034) ($MN)
  • Table 6 Global AI in Education Market Outlook, By Learning Management Systems (LMS) with AI (2023-2034) ($MN)
  • Table 7 Global AI in Education Market Outlook, By AI-Based Assessment & Grading Tools (2023-2034) ($MN)
  • Table 8 Global AI in Education Market Outlook, By Chatbots & Virtual Teaching Assistants (2023-2034) ($MN)
  • Table 9 Global AI in Education Market Outlook, By Services (2023-2034) ($MN)
  • Table 10 Global AI in Education Market Outlook, By Consulting & Strategy Services (2023-2034) ($MN)
  • Table 11 Global AI in Education Market Outlook, By Managed Services (2023-2034) ($MN)
  • Table 12 Global AI in Education Market Outlook, By Integration & Deployment Services (2023-2034) ($MN)
  • Table 13 Global AI in Education Market Outlook, By Training & Support Services (2023-2034) ($MN)
  • Table 14 Global AI in Education Market Outlook, By Technology (2023-2034) ($MN)
  • Table 15 Global AI in Education Market Outlook, By Machine Learning (ML) (2023-2034) ($MN)
  • Table 16 Global AI in Education Market Outlook, By Natural Language Processing (NLP) (2023-2034) ($MN)
  • Table 17 Global AI in Education Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 18 Global AI in Education Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 19 Global AI in Education Market Outlook, By Speech Recognition (2023-2034) ($MN)
  • Table 20 Global AI in Education Market Outlook, By Generative AI (2023-2034) ($MN)
  • Table 21 Global AI in Education Market Outlook, By Other Technologies (2023-2034) ($MN)
  • Table 22 Global AI in Education Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 23 Global AI in Education Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 24 Global AI in Education Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 25 Global AI in Education Market Outlook, By Application (2023-2034) ($MN)
  • Table 26 Global AI in Education Market Outlook, By Personalized Learning & Adaptive Learning (2023-2034) ($MN)
  • Table 27 Global AI in Education Market Outlook, By Automated Grading & Feedback (2023-2034) ($MN)
  • Table 28 Global AI in Education Market Outlook, By Intelligent Tutoring & Virtual Mentoring (2023-2034) ($MN)
  • Table 29 Global AI in Education Market Outlook, By Student Engagement & Retention Analytics (2023-2034) ($MN)
  • Table 30 Global AI in Education Market Outlook, By Curriculum Design & Lesson Planning (2023-2034) ($MN)
  • Table 31 Global AI in Education Market Outlook, By Administrative Automation (2023-2034) ($MN)
  • Table 32 Global AI in Education Market Outlook, By Proctoring & Exam Integrity (2023-2034) ($MN)
  • Table 33 Global AI in Education Market Outlook, By Other Applications (2023-2034) ($MN)
  • Table 34 Global AI in Education Market Outlook, By End User (2023-2034) ($MN)
  • Table 35 Global AI in Education Market Outlook, By K-12 Education (2023-2034) ($MN)
  • Table 36 Global AI in Education Market Outlook, By Higher Education (2023-2034) ($MN)
  • Table 37 Global AI in Education Market Outlook, By Vocational & Corporate Training (2023-2034) ($MN)
  • Table 38 Global AI in Education Market Outlook, By Special Education (2023-2034) ($MN)
  • Table 39 Global AI in Education Market Outlook, By Language Learning Centers (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) are also represented in the same manner as above.