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2024001

人工智慧驅動的個人化學習市場預測至2034年：按解決方案、組件、部署模式、技術、最終用戶和地區分類的全球分析

AI-Powered Personalized Learning Market Forecasts to 2034 - Global Analysis By Solution, Component, Deployment Mode, Technology, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，預計到 2026 年，全球人工智慧驅動的個人化學習市場規模將達到 958.2 億美元，在預測期內以 18.5% 的複合年成長率成長，到 2034 年將達到 3733.3 億美元。

人工智慧驅動的個人化學習是指利用人工智慧技術，根據每個學生的需求、偏好和學業表現來最佳化學習體驗的教育系統。這些系統會分析學習進度、優勢和劣勢等數據，並提供客製化的內容、評估和回饋。透過即時調整，它們能夠提高學生的學習動力、記憶力和學習成果。人工智慧驅動的平台透過自動化管理任務和提供學生進展洞察來輔助教師。數位化教育的普及和對個人化學習體驗日益成長的需求正在推動這一市場的發展。

對客製化學習體驗的需求

學習者越來越希望獲得根據自身學習進度、偏好和技能水平量身定做的內容。人工智慧演算法能夠實現動態課程調整，從而確保更高的參與度和更佳的學習效果。教育機構和企業培訓提供者正在採用個人化平台來提高效率。轉向以學習者為中心的模式進一步強化了這種需求。隨著個人化成為重中之重，人工智慧驅動的解決方案將繼續推動市場成長。

高昂的開發和實施成本

建構人工智慧驅動的學習平台需要複雜的基礎設施、專業技術以及大量投資。小規模的教育機構和組織往往難以承擔實施此類解決方案的成本。持續的維護和更新也會產生額外的費用。成本壁壘限制了此類方案的普及，尤其是在新興市場。儘管市場需求強勁，但提供價格合理的解決方案仍是實現廣泛應用的一大挑戰。

自適應學習和即時回饋

人工智慧系統能夠即時分析學習者的表現並據此調整學習內容。這提高了學習參與度，降低了輟學率，並增強了知識保留率。企業正在採用自適應平台來最佳化員工培訓。教育科技公司與人工智慧開發商之間的合作正在加速創新。隨著對持續學習需求的成長，自適應解決方案預計將迅速發展。

人工智慧驅動學習演算法中的偏見

基於有限資料集訓練的演算法可能會加劇不平等，或錯誤地反映學習者的需求。這會導致推薦不準確，並降低人們對人工智慧系統的信任。監管機構正在加強監督，以確保公平性和透明度。如果公司未能解決偏見問題，將面臨聲譽受損的風險。這項威脅凸顯了在教育領域採用符合倫理的人工智慧實踐的重要性。

新冠疫情的影響：

新冠疫情對人工智慧驅動的個人化學習市場產生了複雜的影響。遠距學習的激增提高了對數位化平台的需求。教育機構加快了採用人工智慧工具來管理虛擬教室和評估。然而，預算限制和數位落差在某些地區減緩了人工智慧工具的普及。疫情凸顯了建構具有韌性、技術主導的教育系統的重要性。總體而言，儘管新冠疫情帶來了短期挑戰，但它增強了個人化學習的長期發展動能。

在預測期內，軟體平台細分市場預計將佔據最大的市場佔有率。

軟體平台領域預計將在預測期內佔據最大的市場佔有率，因為它為提供個人化學習體驗提供了核心基礎設施。這些平台整合了人工智慧演算法、內容庫和分析工具，以支援自適應學習。教育機構依靠這些平台來實現擴充性和效率。雲端解決方案的持續創新正在推動其普及應用。企業培訓計畫也優先考慮使用軟體平台進行人才培養。

預計在預測期內，企業培訓領域將呈現最高的複合年成長率。

在預測期內，由於動態職場環境中對個人化技能發展的需求不斷成長，企業培訓領域預計將呈現最高的成長率。人工智慧驅動的學習工具能夠實現與員工角色和職涯發展路徑相符的客製化培訓計畫。即時回饋可以提高生產力並加速學習成果。企業正在投資個人化平台，以提高員工的適應能力。人工智慧公司與企業培訓提供者之間的合作正在推動創新。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其成熟的教育科技公司以及大學和企業較高的採用率。美國處於主導地位，主要企業都在投資人工智慧驅動的學習平台。對個人化教育的強勁需求鞏固了該地區的領先地位。政府主導的數位化學習措施進一步加速了其普及。教育機構與Start-Ups之間的合作正在推動個人化解決方案的創新。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於快速的數位化進程、不斷擴展的教育生態系統以及對人工智慧技術投資的增加。中國、印度和韓國等國家正在部署大規模的個人化學習計畫。區域內Start-Ups正攜創新解決方案進入市場。對線上教育和企業培訓日益成長的需求正在推動其普及。政府主導的數位轉型支援計畫也進一步促進了成長。

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    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 波特五力分析
    • 供應商的議價能力
    • 買方的議價能力
    • 替代品的威脅
    • 新進入者的威脅
    • 競爭公司之間的競爭
  • 主要企業市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧驅動的個人化學習市場：按解決方案分類

  • 自適應學習平台
  • 智慧輔導系統
  • 內容建議系統
  • 評估和分析工具
  • 學習管理系統
  • 其他解決方案

第6章：全球人工智慧驅動的個人化學習市場：按組件分類

  • 軟體平台
  • 人工智慧演算法
  • 數據分析工具
  • 雲端基礎設施
  • 內容庫
  • 其他規則

第7章：全球人工智慧驅動的個人化學習市場：按部署模式分類

  • 現場
  • 基於雲端的

第8章：全球人工智慧驅動的個人化學習市場：按技術分類

  • 機器學習
  • 自然語言處理
  • 預測分析
  • 建議引擎
  • 學習分析
  • 其他技術

第9章：全球人工智慧驅動的個人化學習市場：按最終用戶分類

  • K-12教育
  • 高等教育
  • 企業培訓
  • 教育科技平台
  • 政府和機構
  • 其他最終用戶

第10章：全球人工智慧驅動的個人化學習市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第11章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第12章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第13章：公司簡介

  • Coursera
  • Udemy
  • Khan Academy
  • Duolingo
  • Byju's
  • Google Classroom
  • Microsoft Education
  • IBM SkillsBuild
  • Pearson plc
  • Blackboard Inc.
  • Instructure（Canvas）
  • edX
  • Quizlet
  • Squirrel AI
  • DreamBox Learning
Product Code: SMRC35212

According to Stratistics MRC, the Global AI-Powered Personalized Learning Market is accounted for $95.82 billion in 2026 and is expected to reach $373.33 billion by 2034 growing at a CAGR of 18.5% during the forecast period. AI-Powered Personalized Learning refers to educational systems that use artificial intelligence to tailor learning experiences based on individual student needs, preferences, and performance. These systems analyze data such as learning pace, strengths, and weaknesses to deliver customized content, assessments, and feedback. By adapting in real time, they improve student engagement, retention, and outcomes. AI-driven platforms support teachers by automating administrative tasks and providing insights into student progress. Growing adoption of digital education and demand for individualized learning experiences are driving this market.

Market Dynamics:

Driver:

Demand for customized learning experiences

Learners increasingly expect tailored content that adapts to their pace, preferences, and skill levels. AI algorithms enable dynamic curriculum adjustments, ensuring improved engagement and outcomes. Educational institutions and corporate training providers are adopting personalized platforms to enhance efficiency. The shift toward learner-centric models further amplifies this demand. As personalization becomes a priority, AI-driven solutions continue to fuel market growth.

Restraint:

High development and implementation costs

Building AI-powered learning platforms requires advanced infrastructure, skilled expertise, and significant investment. Smaller institutions and organizations often struggle to afford these solutions. Ongoing maintenance and updates add further expense. Cost barriers limit adoption, particularly in emerging markets. Despite strong demand, affordability remains a challenge for widespread deployment.

Opportunity:

Adaptive learning and real-time feedback

AI systems can analyze learner performance instantly and adjust content accordingly. This enhances engagement, reduces dropout rates, and improves knowledge retention. Enterprises are adopting adaptive platforms to optimize workforce training. Partnerships between edtech firms and AI developers are accelerating innovation. As demand for continuous learning grows, adaptive solutions are expected to expand rapidly.

Threat:

Bias in AI-driven learning algorithms

Algorithms trained on limited datasets may reinforce inequalities or misrepresent learner needs. This can lead to inaccurate recommendations and reduced trust in AI systems. Regulatory scrutiny is increasing to ensure fairness and transparency. Enterprises risk reputational damage if bias is not addressed. This threat underscores the importance of ethical AI practices in education.

Covid-19 Impact:

The COVID-19 pandemic had a mixed impact on the AI-powered personalized learning market. Remote learning surged, boosting demand for digital platforms. Institutions accelerated adoption of AI-driven tools to manage virtual classrooms and assessments. However, budget constraints and digital divides slowed adoption in some regions. The pandemic highlighted the importance of resilient, technology-driven education systems. Overall, COVID-19 created short-term challenges but reinforced long-term momentum for personalized learning.

The software platforms segment is expected to be the largest during the forecast period

The software platforms segment is expected to account for the largest market share during the forecast period as they provide the core infrastructure for delivering personalized learning experiences. Platforms integrate AI algorithms, content libraries, and analytics tools to support adaptive learning. Educational institutions rely on these platforms for scalability and efficiency. Continuous innovation in cloud-based solutions strengthens adoption. Corporate training programs also prioritize software platforms for workforce development.

The corporate training segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the corporate training segment is predicted to witness the highest growth rate due to increasing demand for personalized skill development in dynamic work environments. AI-powered learning tools enable tailored training programs that align with employee roles and career paths. Real-time feedback enhances productivity and accelerates learning outcomes. Enterprises are investing in personalized platforms to improve workforce agility. Partnerships between AI firms and corporate training providers are driving innovation.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share owing to established edtech firms, and high adoption across universities and corporations. The U.S. leads with major players investing in AI-powered learning platforms. Robust demand for personalized education strengthens regional leadership. Government-backed initiatives in digital learning further accelerate adoption. Partnerships between institutions and startups drive innovation in personalized solutions.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR driven by rapid digitalization, expanding education ecosystems, and rising investments in AI technologies. Countries such as China, India, and South Korea are deploying large-scale personalized learning projects. Regional startups are entering the market with innovative solutions. Expanding demand for online education and corporate training fuels adoption. Government-backed programs supporting digital transformation further strengthen growth.

Key players in the market

Some of the key players in AI-Powered Personalized Learning Market include Coursera, Udemy, Khan Academy, Duolingo, Byju's, Google Classroom, Microsoft Education, IBM SkillsBuild, Pearson plc, Blackboard Inc., Instructure (Canvas), edX, Quizlet, Squirrel AI and DreamBox Learning.

Key Developments:

In March 2026, Quizlet launched as a native app in ChatGPT, enabling students to transform AI conversations into flashcards and active study materials without leaving their workflow.

In July 2025, Instructure announced a global partnership with OpenAI to embed LLM technology into Canvas LMS, enabling educators to design AI-powered learning activities and students to have dynamic educational conversations.

Solutions Covered:

  • Adaptive Learning Platforms
  • Intelligent Tutoring Systems
  • Content Recommendation Systems
  • Assessment & Analytics Tools
  • Learning Management Systems
  • Other Solutions

Components Covered:

  • Software Platforms
  • AI Algorithms
  • Data Analytics Tools
  • Cloud Infrastructure
  • Content Libraries
  • Other Components

Deployment Modes Covered:

  • On-Premise
  • Cloud-Based

Technologies Covered:

  • Machine Learning
  • Natural Language Processing
  • Predictive Analytics
  • Recommendation Engines
  • Learning Analytics
  • Other Technologies

End Users Covered:

  • K-12 Education
  • Higher Education
  • Corporate Training
  • EdTech Platforms
  • Government & Institutions
  • Other End Users

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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, 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-Powered Personalized Learning Market, By Solution

  • 5.1 Adaptive Learning Platforms
  • 5.2 Intelligent Tutoring Systems
  • 5.3 Content Recommendation Systems
  • 5.4 Assessment & Analytics Tools
  • 5.5 Learning Management Systems
  • 5.6 Other Solutions

6 Global AI-Powered Personalized Learning Market, By Component

  • 6.1 Software Platforms
  • 6.2 AI Algorithms
  • 6.3 Data Analytics Tools
  • 6.4 Cloud Infrastructure
  • 6.5 Content Libraries
  • 6.6 Other Components

7 Global AI-Powered Personalized Learning Market, By Deployment Mode

  • 7.1 On-Premise
  • 7.2 Cloud-Based

8 Global AI-Powered Personalized Learning Market, By Technology

  • 8.1 Machine Learning
  • 8.2 Natural Language Processing
  • 8.3 Predictive Analytics
  • 8.4 Recommendation Engines
  • 8.5 Learning Analytics
  • 8.6 Other Technologies

9 Global AI-Powered Personalized Learning Market, By End User

  • 9.1 K-12 Education
  • 9.2 Higher Education
  • 9.3 Corporate Training
  • 9.4 EdTech Platforms
  • 9.5 Government & Institutions
  • 9.6 Other End Users

10 Global AI-Powered Personalized Learning 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 Udemy
  • 13.3 Khan Academy
  • 13.4 Duolingo
  • 13.5 Byju's
  • 13.6 Google Classroom
  • 13.7 Microsoft Education
  • 13.8 IBM SkillsBuild
  • 13.9 Pearson plc
  • 13.10 Blackboard Inc.
  • 13.11 Instructure (Canvas)
  • 13.12 edX
  • 13.13 Quizlet
  • 13.14 Squirrel AI
  • 13.15 DreamBox Learning

List of Tables

  • Table 1 Global AI-Powered Personalized Learning Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Powered Personalized Learning Market, By Solution (2023-2034) ($MN)
  • Table 3 Global AI-Powered Personalized Learning Market, By Adaptive Learning Platforms (2023-2034) ($MN)
  • Table 4 Global AI-Powered Personalized Learning Market, By Intelligent Tutoring Systems (2023-2034) ($MN)
  • Table 5 Global AI-Powered Personalized Learning Market, By Content Recommendation Systems (2023-2034) ($MN)
  • Table 6 Global AI-Powered Personalized Learning Market, By Assessment & Analytics Tools (2023-2034) ($MN)
  • Table 7 Global AI-Powered Personalized Learning Market, By Learning Management Systems (2023-2034) ($MN)
  • Table 8 Global AI-Powered Personalized Learning Market, By Other Solutions (2023-2034) ($MN)
  • Table 9 Global AI-Powered Personalized Learning Market, By Component (2023-2034) ($MN)
  • Table 10 Global AI-Powered Personalized Learning Market, By Software Platforms (2023-2034) ($MN)
  • Table 11 Global AI-Powered Personalized Learning Market, By AI Algorithms (2023-2034) ($MN)
  • Table 12 Global AI-Powered Personalized Learning Market, By Data Analytics Tools (2023-2034) ($MN)
  • Table 13 Global AI-Powered Personalized Learning Market, By Cloud Infrastructure (2023-2034) ($MN)
  • Table 14 Global AI-Powered Personalized Learning Market, By Content Libraries (2023-2034) ($MN)
  • Table 15 Global AI-Powered Personalized Learning Market, By Other Components (2023-2034) ($MN)
  • Table 16 Global AI-Powered Personalized Learning Market, By Deployment Mode (2023-2034) ($MN)
  • Table 17 Global AI-Powered Personalized Learning Market, By On-Premise (2023-2034) ($MN)
  • Table 18 Global AI-Powered Personalized Learning Market, By Cloud-Based (2023-2034) ($MN)
  • Table 19 Global AI-Powered Personalized Learning Market, By Technology (2023-2034) ($MN)
  • Table 20 Global AI-Powered Personalized Learning Market, By Machine Learning (2023-2034) ($MN)
  • Table 21 Global AI-Powered Personalized Learning Market, By Natural Language Processing (2023-2034) ($MN)
  • Table 22 Global AI-Powered Personalized Learning Market, By Predictive Analytics (2023-2034) ($MN)
  • Table 23 Global AI-Powered Personalized Learning Market, By Recommendation Engines (2023-2034) ($MN)
  • Table 24 Global AI-Powered Personalized Learning Market, By Learning Analytics (2023-2034) ($MN)
  • Table 25 Global AI-Powered Personalized Learning Market, By Other Technologies (2023-2034) ($MN)
  • Table 26 Global AI-Powered Personalized Learning Market, By End User (2023-2034) ($MN)
  • Table 27 Global AI-Powered Personalized Learning Market, By K-12 Education (2023-2034) ($MN)
  • Table 28 Global AI-Powered Personalized Learning Market, By Higher Education (2023-2034) ($MN)
  • Table 29 Global AI-Powered Personalized Learning Market, By Corporate Training (2023-2034) ($MN)
  • Table 30 Global AI-Powered Personalized Learning Market, By EdTech Platforms (2023-2034) ($MN)
  • Table 31 Global AI-Powered Personalized Learning Market, By Government & Institutions (2023-2034) ($MN)
  • Table 32 Global AI-Powered Personalized Learning Market, By Other End Users (2023-2034) ($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.