교육용 에이전트형 AI 시장 규모, 점유율, 동향 및 성장 분석 보고서(2026-2034년)

The global agentic AI in education market report size is expected to reach USD 27.23 Billion in 2034 from USD 1.72 Billion in 2025, growing at a CAGR of 35.92 during 2026-2034.This market is expanding steadily as schools, universities, and training providers adopt intelligent learning technologies. Agentic AI systems can personalize lessons, track student progress, automate administrative tasks, and offer real-time tutoring support. Rising demand for digital learning experiences and scalable education models is driving adoption across academic institutions.

One of the main growth drivers is the need for individualized learning pathways. Agentic AI can analyze student strengths, weaknesses, and engagement levels to recommend customized content and pacing. Educators also benefit from automated grading, scheduling, and curriculum planning tools. The growth of online education and remote learning platforms is further boosting market demand.

Future prospects remain strong as education systems prioritize accessibility, efficiency, and better learning outcomes. Agentic AI may become central to adaptive classrooms, multilingual tutoring, and lifelong professional learning platforms. As AI tools become more affordable and user-friendly, adoption is expected to increase across both developed and emerging education markets.

Our reports are carefully developed to deliver comprehensive and actionable insights across a wide range of industries and markets. Each report includes several essential components designed to provide a complete understanding of the market environment:

Market Overview: This section provides a clear introduction to the market, including key definitions, classifications, and an overview of the current industry landscape.

Market Dynamics: A detailed evaluation of the primary drivers, restraints, opportunities, and challenges shaping market growth. It covers factors such as technological developments, regulatory frameworks, and evolving industry trends.

Segmentation Analysis: A structured breakdown of the market into key segments based on product type, application, end-user, and geographic region. This section highlights the performance, growth potential, and contribution of each segment.

Competitive Landscape: An in-depth assessment of leading market participants, including their market positioning, product portfolios, strategic initiatives, and financial performance. It provides valuable insights into competitive dynamics and the strategies adopted by key players.

Market Forecast: Data-driven projections of market size and growth patterns over a defined forecast period. This section incorporates historical trends, current market conditions, and quantitative analysis to illustrate expected future developments.

Regional Analysis: A comprehensive review of market performance across major geographic regions, identifying high-growth areas and regional trends to better understand localized market opportunities.

Emerging Trends and Opportunities: Identification of significant market trends, technological advancements, and new investment opportunities. This section highlights potential growth areas and future industry developments.

Customization Options: We offer flexible customization services to tailor reports according to specific client requirements. This may include additional segmentation, country-level analysis, competitor profiling, customized data points, or focused insights on particular market segments to better support strategic decision-making.

MARKET SEGMENTATION

By Solution Type

• Curriculum Design Agents
• Intelligent Tutoring Systems
• Learning-Management Bots
• Assessment and Feedback Agents
• Administrative Automation Agents

By Deployment Model

• Cloud-based
• On-premise
• Hybrid

By Education Level

• Primary
• Secondary
• Tertiary
• Continuing Education

By End-User

• K-12 Institutions
• Higher-Education Institutions
• Corporate and Professional Training
• Vocational and Skill-Development Centres
• Lifelong/Adult Learners

COMPANIES PROFILED

• Pearson plc, Microsoft, Google LLC, Duolingo Inc., Coursera Inc., OpenAI, Anthropic, 2U Inc., Carnegie Learning Inc., DreamBox Learning, Knewton, ALEKS Corporation, Squirrel AI Learning, Riiid Labs Inc., Century Tech

TABLE OF CONTENTS

Chapter 1. PREFACE

• 1.1. Market Segmentation & Scope
• 1.2. Market Definition
• 1.3. Information Procurement
  • 1.3.1 Information Analysis
  • 1.3.2 Market Formulation & Data Visualization
  • 1.3.3 Data Validation & Publishing
• 1.4. Research Scope and Assumptions
  • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

• 2.1. Market Snapshot
• 2.2. Segmental Outlook
• 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

• 3.1. Market Lineage Outlook
• 3.2. Penetration & Growth Prospect Mapping
• 3.3. Value Chain Analysis
• 3.4. Regulatory Framework
  • 3.4.1 Standards & Compliance
  • 3.4.2 Regulatory Impact Analysis
• 3.5. Market Dynamics
  • 3.5.1 Market Drivers
  • 3.5.2 Market Restraints
  • 3.5.3 Market Opportunities
  • 3.5.4 Market Challenges
• 3.6. Porter's Five Forces Analysis
• 3.7. PESTLE Analysis

Chapter 4. GLOBAL AGENTIC AI IN EDUCATION MARKET: BY SOLUTION TYPE 2022-2034 (USD MN)

• 4.1. Market Analysis, Insights and Forecast Solution Type
• 4.2. Curriculum Design Agents Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.3. Intelligent Tutoring Systems Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.4. Learning-Management Bots Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.5. Assessment and Feedback Agents Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.6. Administrative Automation Agents Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL AGENTIC AI IN EDUCATION MARKET: BY DEPLOYMENT MODEL 2022-2034 (USD MN)

• 5.1. Market Analysis, Insights and Forecast Deployment Model
• 5.2. Cloud-based Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.3. On-premise Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.4. Hybrid Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL AGENTIC AI IN EDUCATION MARKET: BY EDUCATION LEVEL 2022-2034 (USD MN)

• 6.1. Market Analysis, Insights and Forecast Education Level
• 6.2. Primary Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.3. Secondary Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.4. Tertiary Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.5. Continuing Education Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL AGENTIC AI IN EDUCATION MARKET: BY END-USER 2022-2034 (USD MN)

• 7.1. Market Analysis, Insights and Forecast End-user
• 7.2. K-12 Institutions Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.3. Higher-Education Institutions Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.4. Corporate and Professional Training Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.5. Vocational and Skill-Development Centres Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.6. Lifelong/Adult Learners Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 8. GLOBAL AGENTIC AI IN EDUCATION MARKET: BY REGION 2022-2034 (USD MN)

• 8.1. Regional Outlook
• 8.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.2.1 By Solution Type
  • 8.2.2 By Deployment Model
  • 8.2.3 By Education Level
  • 8.2.4 By End-user
  • 8.2.5 United States
  • 8.2.6 Canada
  • 8.2.7 Mexico
• 8.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.3.1 By Solution Type
  • 8.3.2 By Deployment Model
  • 8.3.3 By Education Level
  • 8.3.4 By End-user
  • 8.3.5 United Kingdom
  • 8.3.6 France
  • 8.3.7 Germany
  • 8.3.8 Italy
  • 8.3.9 Russia
  • 8.3.10 Rest Of Europe
• 8.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.4.1 By Solution Type
  • 8.4.2 By Deployment Model
  • 8.4.3 By Education Level
  • 8.4.4 By End-user
  • 8.4.5 India
  • 8.4.6 Japan
  • 8.4.7 South Korea
  • 8.4.8 Australia
  • 8.4.9 South East Asia
  • 8.4.10 Rest Of Asia Pacific
• 8.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.5.1 By Solution Type
  • 8.5.2 By Deployment Model
  • 8.5.3 By Education Level
  • 8.5.4 By End-user
  • 8.5.5 Brazil
  • 8.5.6 Argentina
  • 8.5.7 Peru
  • 8.5.8 Chile
  • 8.5.9 Rest of Latin America
• 8.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 8.6.1 By Solution Type
  • 8.6.2 By Deployment Model
  • 8.6.3 By Education Level
  • 8.6.4 By End-user
  • 8.6.5 Saudi Arabia
  • 8.6.6 UAE
  • 8.6.7 Israel
  • 8.6.8 South Africa
  • 8.6.9 Rest of the Middle East And Africa

Chapter 9. COMPETITIVE LANDSCAPE

• 9.1. Recent Developments
• 9.2. Company Categorization
• 9.3. Supply Chain & Channel Partners (based on availability)
• 9.4. Market Share & Positioning Analysis (based on availability)
• 9.5. Vendor Landscape (based on availability)
• 9.6. Strategy Mapping

Chapter 10. COMPANY PROFILES OF GLOBAL AGENTIC AI IN EDUCATION INDUSTRY

• 10.1. Top Companies Market Share Analysis
• 10.2. Company Profiles
  • 10.2.1 Pearson Plc
  • 10.2.2 Microsoft
  • 10.2.3 Google LLC
  • 10.2.4 Duolingo Inc
  • 10.2.5 Coursera Inc
  • 10.2.6 OpenAI
  • 10.2.7 Anthropic
  • 10.2.8 2U Inc
  • 10.2.9 Carnegie Learning Inc
  • 10.2.10 DreamBox Learning
  • 10.2.11 Knewton
  • 10.2.12 ALEKS Corporation
  • 10.2.13 Squirrel AI Learning
  • 10.2.14 Riiid Labs Inc
  • 10.2.15 Century Tech