查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1880525

人工智慧驅動的個人化學習系統市場預測至2032年：按組件、學習類型、存取模式、部署模式、應用、最終用戶和地區分類的全球分析

AI-Driven Personalized Learning Systems Market Forecasts to 2032 - Global Analysis By Component (Platform and Services), Learning Type, Access Mode, Deployment Mode, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的一項研究，全球人工智慧驅動的個人化學習系統市場預計到 2025 年將達到 71.9 億美元，到 2032 年將達到 203.2 億美元，在預測期內的複合年成長率為 16%。

人工智慧驅動的個人化學習系統是一種教育平台，它利用人工智慧技術來最佳化學習體驗，使其與每個學習者的需求、偏好和學習表現相匹配。透過分析學習進度、評估結果和參與度等數據，這些系統能夠動態調整學習內容、推薦學習資源並提供即時回饋。其主要功能包括智慧輔導、自適應評估和個人化學習路徑，從而最佳化技能習得和維持。這些系統適用於K-12教育、高等教育、企業培訓和終身學習等各種環境中的學習者。透過提高參與度、改善學習成果並實現可擴展的個人化，人工智慧驅動的系統正在將傳統教育轉變為更有效率、以學習者為中心的學習體驗。

個別化學習的需求

學習者期望獲得根據自身學習目標和認知特點量身定做的內容、循序漸進的學習進度和回饋。平台利用人工智慧引擎、基於規則的邏輯和行為分析技術，即時調整教學內容。與學習管理系統 (LMS)、行動應用和遊戲化模組的整合，能夠提升學習者的參與度和留存率。教育機構、雇主和教育科技Start-Ups都在尋求擴充性、全面且以結果為導向的解決方案。這些趨勢正在推動人工智慧驅動的個人化學習系統的應用。

資料隱私和安全問題

自適應系統會收集敏感的學習者數據，包括表現生物識別和行為模式，因此需要強大的加密和使用者同意通訊協定。企業在滿足《家庭教育權利和隱私法案》(FERPA)、 《一般資料保護規則》(GDPR) 和區域合規要求的同時，還要保持個人化，這面臨著許多挑戰。缺乏透明度、演算法偏差和第三方存取權限進一步加劇了實施的複雜性。供應商必須投資於符合倫理的人工智慧、隱私儀表板和安全的雲端架構，以降低風險。這些限制持續阻礙著合規驅動型學習環境中平台的成熟度。

擴大遠距和混合式教育

教育機構和雇主正在拓展其數位化項目，以涵蓋分散的學習者並提高靈活性。平台支援模組化內容、動態評估和個人化學習路徑，並可在行動和桌面介面上運作。與虛擬教室、認證系統和分析儀表板的整合提高了學習的連續性和有效性。在正規教育、勞動力發展和終身學習領域，對擴充性、高彈性和以學習者為中心的基礎設施的需求日益成長。這些趨勢正在推動混合式和遠距學習、人工智慧驅動的個人化學習系統的發展。

高昂的實施和整合成本

自適應系統需要對內容標籤、後端整合和教師培訓進行投資，這減緩了其普及速度。企業難以將傳統基礎設施與雲端原生引擎和互通性標準相容。缺乏內部專業知識和變更管理進一步加劇了擴展性和效能方面的挑戰。供應商必須提供模組化定價、部署支援和低程式碼介面，以提高可訪問性。在預算敏感且抵制變革的教育產業，這些限制持續限制平台績效。

新冠疫情的影響：

疫情加速了數位化學習的普及，同時也暴露了個人化、互動性和學習者支持方面的不足。封鎖措施擾亂了課堂教學，並增加了對支援遠距離診斷和自主學習的自適應平台的需求。教育機構部署了人工智慧引擎，以指導不同學習群體的補習、強化和能力提升。公立和私立教育系統在雲端遷移、內容數位化和分析方面的投資激增。政策制定者和消費者越來越關注學習損失、公平性和數位化教學方法。這些變化強化了對自適應和彈性學習基礎設施的長期投資。

預計在預測期內，影片學習領域將佔據最大的市場佔有率。

在預測期內，由於其便利性、互動性和與自適應引擎的兼容性，影片學習預計將佔據最大的市場佔有率。平台利用互動式影片、分支邏輯和內建評估來實現個人化教學和進度追蹤。與行動應用、學習管理系統 (LMS) 和內容庫的整合擴大了覆蓋範圍並增強了學習者的自主控制權。 K-12、高等教育和專業培訓領域對視覺身臨其境型和自主學習模式的需求日益成長。供應商提供模組化影片堆疊、人工智慧標籤和分析儀表板以輔助實施。這些功能正在鞏固影片學習在人工智慧驅動的個人化學習系統中的主導地位。

預計在預測期內，技能發展和認證領域將以最高的複合年成長率成長。

預計在預測期內，技能發展和認證領域將實現最高成長率，因為該平台正拓展至員工技能提升、認證和績效追蹤等領域。學習者透過自適應學習路徑獲得與工作相關的技能，並努力取得符合業界標準的微證書。該平台支援企業培訓和職業培訓項目中的能力映射、個人化評估和數位徽章。與人力資源系統、學習管理系統平台和職業服務機構的整合提升了平台的價值和學員留存率。雇主、自由工作者和成人學習者對擴充性、檢驗且與成果掛鉤的學習需求日益成長。這些趨勢正在推動以技能為中心、人工智慧驅動的個人化學習系統和服務的發展。

佔比最大的地區：

由於教育科技的成熟、機構投資以及監管機構對人工智慧驅動的個人化學習系統的承諾，預計北美地區將在預測期內佔據最大的市場佔有率。各公司正在學校、大學和企業內部培訓中部署平台，以提高個人化程度、學生留存率和學習成果。對人工智慧引擎、雲端基礎設施和數位教學法的投資為創新和擴充性提供了支持。主要供應商、研究機構和政策框架的存在正在推動該生態系統的深化和廣泛應用。各公司正在調整其適應性策略，使其與第一類教育補助金（Title I）的要求、勞動力發展和終身學習目標保持一致。這些因素正在推動北美在人工智慧驅動的個人化學習系統的商業化和管治處於主導地位。

年複合成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於該地區各國經濟對教育的需求不斷成長、行動網路普及率不斷提高以及數位轉型日益融合。印度、中國、印尼和越南等國家正在各個教育階段（包括K-12、高等教育和職業培訓）擴展其平台。政府支持計畫正在促進都市區地區的教育科技孵化、數位素養提升和遠距學習基礎建設。本地供應商正在提供行動優先、多語言且具有文化適應性的解決方案，以滿足不同學習者的需求。正規和非正規教育系統對擴充性、全面且個人化的學習基礎設施的需求日益成長。

免費客製化服務：

購買此報告的客戶可以選擇以下免費自訂選項之一：

  • 公司概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 主要參與者（最多3家公司）的SWOT分析
  • 區域細分
    • 根據客戶要求，提供主要國家的市場規模估算與預測，以及複合年成長率（註：可行性需確認）。
  • 競爭基準化分析
    • 根據主要參與者的產品系列、地理覆蓋範圍和策略聯盟基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 原始研究資料
    • 二手研究資料
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章 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
  • 競爭對手之間的競爭

5. 全球人工智慧驅動的個人化學習系統市場（按組件分類）

  • 介紹
  • 平台
  • 服務
    • 實施與整合
    • 支援與維護
    • 諮詢

6. 全球人工智慧驅動的個人化學習系統市場（按學習類型分類）

  • 介紹
  • 基於視訊的學習
  • 以文本為基礎的學習
  • 基於音訊的學習
  • 混合/多模態學習
  • 其他學習類型

7. 全球人工智慧驅動的個人化學習系統市場（按訪問模式分類）

  • 介紹
  • 桌面
  • 藥片
  • 智慧型手機
  • VR/AR設備
  • 其他接取方式

8. 全球人工智慧驅動的個人化學習系統市場（按部署模式分類）

  • 介紹
  • 雲端基礎的
  • 本地部署

9. 全球人工智慧驅動的個人化學習系統市場（按應用分類）

  • 介紹
  • 技能發展與認證
  • 基於課程的學習
  • 企業培訓與合規
  • 考試準備與評估
  • 其他用途

第10章 由全球人工智慧驅動的個人化學習系統市場（依最終用戶分類）

  • 介紹
  • 高等教育機構
  • 公司
  • 政府和國防部
  • 職業技術培訓中心
  • 其他最終用戶

第11章 由全球人工智慧驅動的個人化學習系統市場（按地區分類）

  • 介紹
  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲國家
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與併購
  • 新產品上市
  • 業務拓展
  • 其他關鍵策略

第13章：企業概況

  • 360Learning
  • Adaptemy
  • CogBooks
  • Disprz
  • edyoucated
  • OttoLearn
  • Paradiso Solutions
  • Pearson plc
  • Realizeit
  • Smart Sparrow
  • DreamBox Learning Inc.
  • Knewton Inc.
  • McGraw Hill LLC
  • Area9 Lyceum ApS
  • Squirrel AI Learning Inc.
Product Code: SMRC32502

According to Stratistics MRC, the Global AI-Driven Personalized Learning Systems Market is accounted for $7.19 billion in 2025 and is expected to reach $20.32 billion by 2032 growing at a CAGR of 16% during the forecast period. AI-Driven Personalized Learning Systems are educational platforms that leverage artificial intelligence to tailor learning experiences to individual learners' needs, preferences, and performance. By analyzing data such as learning pace, assessment results, and engagement patterns, these systems dynamically adapt content, recommend resources, and provide real-time feedback. Features often include intelligent tutoring, adaptive assessments, and personalized learning pathways that optimize skill acquisition and retention. They support diverse learners across K-12, higher education, corporate training, and lifelong learning environments. By enhancing engagement, improving outcomes, and enabling scalable personalization, AI-driven systems are transforming traditional education into more efficient, learner-centric experiences.

Market Dynamics:

Driver:

Demand for personalized learning

Learners seek tailored content pacing and feedback based on performance goals and cognitive profiles. Platforms use AI engines rule-based logic and behavioral analytics to adapt instruction in real time. Integration with LMS systems mobile apps and gamified modules enhances engagement and retention. Demand for scalable inclusive and outcome-driven solutions is rising across institutions employers and edtech startups. These dynamics are propelling deployment across AI-driven personalized learning systems.

Restraint:

Data privacy & security concerns

Adaptive systems collect sensitive learner data including performance biometrics and behavioral patterns which require robust encryption and consent protocols. Enterprises face challenges in meeting FERPA GDPR and regional compliance mandates while maintaining personalization. Lack of transparency algorithmic bias and third-party access further complicate adoption. Vendors must invest in ethical AI privacy dashboards and secure cloud architecture to reduce risk. These constraints continue to hinder platform maturity across compliance-sensitive learning environments.

Opportunity:

Growth of remote & hybrid education

Institutions and employers are scaling digital programs to reach distributed learners and improve flexibility. Platforms support modular content dynamic assessments and personalized pathways across mobile and desktop interfaces. Integration with virtual classrooms credentialing systems and analytics dashboards enhances continuity and impact. Demand for scalable resilient and learner-centric infrastructure is rising across formal education workforce development and lifelong learning. These trends are fostering growth across hybrid and remote-enabled AI-driven personalized learning systems.

Threat:

High implementation & integration costs

Adaptive systems require investment in content tagging backend integration and faculty training which delays deployment. Enterprises face challenges in aligning legacy infrastructure with cloud-native engines and interoperability standards. Lack of internal expertise and change management further complicates scaling and performance. Vendors must offer modular pricing onboarding support and low-code interfaces to improve accessibility. These limitations continue to restrict platform performance across budget-sensitive and transformation-resistant education segments.

Covid-19 Impact:

The pandemic accelerated digital learning adoption while exposing gaps in personalization engagement and learner support. Lockdowns disrupted classroom instruction and increased demand for adaptive platforms that support remote diagnostics and individualized pacing. Institutions deployed AI-powered engines to guide remediation enrichment and mastery across diverse learner cohorts. Investment in cloud migration content digitization and analytics surged across public and private education systems. Public awareness of learning loss equity and digital pedagogy increased across policy and consumer circles. These shifts are reinforcing long-term investment in adaptive and resilient learning infrastructure.

The video-based learning segment is expected to be the largest during the forecast period

The video-based learning segment is expected to account for the largest market share during the forecast period due to its accessibility engagement and compatibility with adaptive engines. Platforms use interactive videos branching logic and embedded assessments to personalize instruction and track progress. Integration with mobile apps LMS systems and content libraries enhances reach and learner control. Demand for visual immersive and self-paced formats is rising across K-12 higher education and professional training. Vendors offer modular video stacks AI tagging and analytics dashboards to support deployment. These capabilities are boosting segment dominance across video-enabled AI-driven personalized learning systems.

The skill development & certification segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the skill development & certification segment is predicted to witness the highest growth rate as platforms expand across workforce reskilling credentialing and performance tracking. Learners pursue adaptive pathways to acquire job-relevant skills and earn microcredentials aligned with industry standards. Platforms support competency mapping personalized assessments and digital badges across enterprise and vocational programs. Integration with HR systems LMS platforms and career services enhances value and continuity. Demand for scalable verified and outcome-linked learning is rising across employers freelancers and adult learners. These dynamics are accelerating growth across skill-focused AI-driven personalized learning systems and services.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its edtech maturity institutional investment and regulatory engagement across AI-driven personalized learning systems. Enterprises deploy platforms across schools universities and corporate training to improve personalization retention and outcomes. Investment in AI engines cloud infrastructure and digital pedagogy supports innovation and scalability. Presence of leading vendors research institutions and policy frameworks drives ecosystem depth and adoption. Firms align adaptive strategies with Title I mandates workforce development and lifelong learning goals. These factors are propelling North America's leadership in AI-driven personalized learning systems commercialization and governance.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR as education demand mobile penetration and digital transformation converge across regional economies. Countries like India China Indonesia and Vietnam scale platforms across K-12 higher education and vocational training. Government-backed programs support edtech incubation digital literacy and remote learning infrastructure across urban and rural zones. Local providers offer mobile-first multilingual and culturally adapted solutions tailored to diverse learner profiles. Demand for scalable inclusive and personalized learning infrastructure is rising across formal and informal education systems.

Key players in the market

Some of the key players in AI-Driven Personalized Learning Systems Market include 360Learning, Adaptemy, CogBooks, Disprz, edyoucated, OttoLearn, Paradiso Solutions, Pearson plc, Realizeit, Smart Sparrow, DreamBox Learning Inc., Knewton Inc., McGraw Hill LLC, Area9 Lyceum ApS and Squirrel AI Learning Inc.

Key Developments:

In April 2025, Adaptemy launched an upgraded Curriculum Mapping Engine, enabling granular alignment between student performance and national learning outcomes. The tool offers automatic content suggestions, real-time feedback loops, and teacher dashboards for differentiated instruction.

In October 2023, 360Learning acquired eLamp, a French AI-powered skills management platform, to strengthen its AI-driven personalized learning systems capabilities. The acquisition enabled 360Learning to map skill gaps more precisely and deliver personalized upskilling paths using AI.

Components Covered:

  • Platform
  • Services

Learning Types Covered:

  • Video-Based Learning
  • Text-Based Learning
  • Voice-Based Learning
  • Hybrid/Multimodal Learning
  • Other Learning Types

Access Modes Covered:

  • Desktop
  • Tablets
  • Smartphones
  • VR/AR Devices
  • Other Access Modes

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises

Applications Covered:

  • Skill Development & Certification
  • Curriculum-Based Learning
  • Corporate Training & Compliance
  • Test Preparation & Assessment
  • Other Applications

End Users Covered:

  • Higher Education Institutions
  • Corporate Enterprises
  • Government & Defense
  • Vocational & Technical Training Centers
  • Other End Users

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 2024, 2025, 2026, 2028, and 2032
  • 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

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI-driven Personalized Learning Systems Market, By Component

  • 5.1 Introduction
  • 5.2 Platform
  • 5.3 Services
    • 5.3.1 Implementation & Integration
    • 5.3.2 Support & Maintenance
    • 5.3.3 Consulting

6 Global AI-driven Personalized Learning Systems Market, By Learning Type

  • 6.1 Introduction
  • 6.2 Video-Based Learning
  • 6.3 Text-Based Learning
  • 6.4 Voice-Based Learning
  • 6.5 Hybrid/Multimodal Learning
  • 6.6 Other Learning Types

7 Global AI-driven Personalized Learning Systems Market, By Access Mode

  • 7.1 Introduction
  • 7.2 Desktop
  • 7.3 Tablets
  • 7.4 Smartphones
  • 7.5 VR/AR Devices
  • 7.6 Other Access Modes

8 Global AI-driven Personalized Learning Systems Market, By Deployment Mode

  • 8.1 Introduction
  • 8.2 Cloud-Based
  • 8.3 On-Premises

9 Global AI-driven Personalized Learning Systems Market, By Application

  • 9.1 Introduction
  • 9.2 Skill Development & Certification
  • 9.3 Curriculum-Based Learning
  • 9.4 Corporate Training & Compliance
  • 9.5 Test Preparation & Assessment
  • 9.6 Other Applications

10 Global AI-driven Personalized Learning Systems Market, By End User

  • 10.1 Introduction
  • 10.2 igher Education Institutions
  • 10.3 Corporate Enterprises
  • 10.4 Government & Defense
  • 10.5 Vocational & Technical Training Centers
  • 10.6 Other End Users

11 Global AI-driven Personalized Learning Systems Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 360Learning
  • 13.2 Adaptemy
  • 13.3 CogBooks
  • 13.4 Disprz
  • 13.5 edyoucated
  • 13.6 OttoLearn
  • 13.7 Paradiso Solutions
  • 13.8 Pearson plc
  • 13.9 Realizeit
  • 13.10 Smart Sparrow
  • 13.11 DreamBox Learning Inc.
  • 13.12 Knewton Inc.
  • 13.13 McGraw Hill LLC
  • 13.14 Area9 Lyceum ApS
  • 13.15 Squirrel AI Learning Inc.

List of Tables

  • Table 1 Global AI-driven Personalized Learning Systems Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-driven Personalized Learning Systems Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI-driven Personalized Learning Systems Market Outlook, By Platform (2024-2032) ($MN)
  • Table 4 Global AI-driven Personalized Learning Systems Market Outlook, By Services (2024-2032) ($MN)
  • Table 5 Global AI-driven Personalized Learning Systems Market Outlook, By Implementation & Integration (2024-2032) ($MN)
  • Table 6 Global AI-driven Personalized Learning Systems Market Outlook, By Support & Maintenance (2024-2032) ($MN)
  • Table 7 Global AI-driven Personalized Learning Systems Market Outlook, By Consulting (2024-2032) ($MN)
  • Table 8 Global AI-driven Personalized Learning Systems Market Outlook, By Learning Type (2024-2032) ($MN)
  • Table 9 Global AI-driven Personalized Learning Systems Market Outlook, By Video-Based Learning (2024-2032) ($MN)
  • Table 10 Global AI-driven Personalized Learning Systems Market Outlook, By Text-Based Learning (2024-2032) ($MN)
  • Table 11 Global AI-driven Personalized Learning Systems Market Outlook, By Voice-Based Learning (2024-2032) ($MN)
  • Table 12 Global AI-driven Personalized Learning Systems Market Outlook, By Hybrid/Multimodal Learning (2024-2032) ($MN)
  • Table 13 Global AI-driven Personalized Learning Systems Market Outlook, By Other Learning Types (2024-2032) ($MN)
  • Table 14 Global AI-driven Personalized Learning Systems Market Outlook, By Access Mode (2024-2032) ($MN)
  • Table 15 Global AI-driven Personalized Learning Systems Market Outlook, By Desktop (2024-2032) ($MN)
  • Table 16 Global AI-driven Personalized Learning Systems Market Outlook, By Tablets (2024-2032) ($MN)
  • Table 17 Global AI-driven Personalized Learning Systems Market Outlook, By Smartphones (2024-2032) ($MN)
  • Table 18 Global AI-driven Personalized Learning Systems Market Outlook, By VR/AR Devices (2024-2032) ($MN)
  • Table 19 Global AI-driven Personalized Learning Systems Market Outlook, By Other Access Modes (2024-2032) ($MN)
  • Table 20 Global AI-driven Personalized Learning Systems Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 21 Global AI-driven Personalized Learning Systems Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 22 Global AI-driven Personalized Learning Systems Market Outlook, By On-Premises (2024-2032) ($MN)
  • Table 23 Global AI-driven Personalized Learning Systems Market Outlook, By Application (2024-2032) ($MN)
  • Table 24 Global AI-driven Personalized Learning Systems Market Outlook, By Skill Development & Certification (2024-2032) ($MN)
  • Table 25 Global AI-driven Personalized Learning Systems Market Outlook, By Curriculum-Based Learning (2024-2032) ($MN)
  • Table 26 Global AI-driven Personalized Learning Systems Market Outlook, By Corporate Training & Compliance (2024-2032) ($MN)
  • Table 27 Global AI-driven Personalized Learning Systems Market Outlook, By Test Preparation & Assessment (2024-2032) ($MN)
  • Table 28 Global AI-driven Personalized Learning Systems Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 29 Global AI-driven Personalized Learning Systems Market Outlook, By End User (2024-2032) ($MN)
  • Table 30 Global AI-driven Personalized Learning Systems Market Outlook, By Higher Education Institutions (2024-2032) ($MN)
  • Table 31 Global AI-driven Personalized Learning Systems Market Outlook, By Corporate Enterprises (2024-2032) ($MN)
  • Table 32 Global AI-driven Personalized Learning Systems Market Outlook, By Government & Defense (2024-2032) ($MN)
  • Table 33 Global AI-driven Personalized Learning Systems Market Outlook, By Vocational & Technical Training Centers (2024-2032) ($MN)
  • Table 34 Global AI-driven Personalized Learning Systems Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.