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市場調查報告書
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2068777

人工智慧驅動的學術輔導市場預測至2034年：按組件、部署模式、輔導類型、應用、最終用戶和地區分類的全球分析

AI-Powered Academic Mentoring Market Forecasts to 2034 - Global Analysis By Component (Software and Services), Deployment Mode, Mentoring Type, 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個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧驅動的學術教學市場預計將在 2026 年達到 50 億美元，並在預測期內以 16.5% 的複合年成長率成長，到 2034 年達到 170 億美元。

人工智慧驅動的學術教學是指利用人工智慧演算法為學習者提供個人化教學、一對一輔導和學術支援的智慧系統。這些平台運用自然語言處理、機器學習和自適應學習技術來分析學生的學習數據，並提供客製化的回饋。這項技術包括虛擬輔導助理、用於早期療育的預測分析以及自動化的課程推薦。人工智慧驅動的學術教學面向中小學生、高等教育學習者以及希望透過數據驅動的教學路徑提昇技能的專業人士。

個別化學習的需求

隨著個人化學習路徑的日益普及，對人工智慧驅動的學術輔導解決方案的需求也顯著成長。教育機構逐漸意識到，千篇一律的教學方法無法滿足不同學習風格和進度的需求。人工智慧輔導平台透過分析大量資料集來最佳化內容交付，並創造自適應學習體驗，從而提升學生的學習動力和學習成績。大學和中小學正大力投資這些技術，以降低輟學率並提高學業成績。人工智慧驅動的擴充性，使教育機構能夠在不相應增加教師人數的情況下，為更多學生提供支援。

資料隱私問題

收集和分析海量學生資料引發了嚴重的隱私和安全問題，限制了市場擴張。教育機構在實施人工智慧輔導系統時，必須應對複雜的法律規範，包括《家庭教育權利和隱私法案》（FERPA）和《一般資料保護規範》（GDPR）。家長和學生對演算法分析以及敏感學業記錄可能被濫用表示擔憂。實施強力的網路安全措施和合規協議需要大量的額外成本。解決這些問題需要透明的資料管治政策，這可能會延緩實施進度。

終身學習的拓展

持續技能發展和終身學習的加速轉型，為人工智慧驅動的學術輔導平台創造了廣泛的機會。在職人士越來越需要靈活、隨選的教育支持，以在快速變化的勞動力市場中保持競爭力。企業學習與發展計畫正在引入人工智慧輔導，以高效提升員工技能。微證書和專業資格的普及推動了對智慧指導系統的需求。教育科技提供者與企業之間的夥伴關係，正在傳統學術環境之外創造永續的收入來源。

對人類教育的承諾

教育環境中對人際互動的強烈偏好對人工智慧輔導的廣泛應用構成了重大威脅。許多學習者和教育者珍惜人類導師所提供的同理心、直覺和細緻的理解。人們對人工智慧能否滿足複雜的社會情感學習需求持懷疑態度，這限制了其市場滲透。教師工會和教職員擔心失業，由此產生的抵制也構成了製度性障礙。此外，人們普遍認為人工智慧輔導只是一種削減成本的手段，而非對教育的改進，這也阻礙了其被接受。

新型冠狀病毒（COVID-19）的影響：

隨著全球教育機構轉向遠距學習模式，新冠疫情從根本上加速了人工智慧驅動的學術輔導的普及應用。儘管疫情初期造成了實施進度的暫時延誤，但這場危機也凸顯了在線學習中為學生提供個人化支持方面存在的巨大缺口。疫情過後，混合式學習模式已成為常態，推動了對智慧輔導平台的持續投入。如今，教育機構正優先考慮建構一個能夠適應不同教學模式、具有彈性且技術驅動的支援系統。

在預測期內，服務業預計將佔據最大的市場佔有率。

在預測期內，服務領域預計將佔據最大的市場佔有率。這是因為人工智慧輔導平台的實施、培訓和持續維護都需要全面的支援。教育機構需要大量的專業服務來將這些系統與其現有的學習管理基礎設施整合。諮詢服務有助於客製化人工智慧演算法，以適應每個機構的課程和教學方法。由於機器學習模型的實施十分複雜，因此專家技術支援和持續最佳化至關重要。服務供應商透過基於訂閱的支援合約和系統升級獲得持續的收入。

在預測期內，基於雲端的細分市場預計將呈現最高的複合年成長率。

在預測期內，雲端細分市場預計將呈現最高的成長率，這主要得益於雲端學術輔導平台模式的擴充性、易用性和成本效益。雲端基礎設施能夠與現有的教育科技生態系統無縫整合，同時降低資本支出需求。雲端解決方案的柔軟性支援遠端和混合式學習環境，而這些環境已成為後疫情時代的標準。各種規模的教育機構無需投資大規模IT基礎設施，即可利用企業級AI輔導功能。

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，這主要得益於美國和加拿大對先進教育技術的早期應用以及對教育科技基礎設施的大量投資。包括微軟、Alphabet 和亞馬遜在內的領先科技公司正在推動人工智慧驅動的學習解決方案的創新。政府支持教育數位轉型的措施正在加速這一進程。頂尖大學和研究機構的存在，也催生了對尖端指導平台的強勁需求。創業投資對教育科技新創企業的投入，正在推動一個充滿活力的創新生態系統的發展。

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，這主要得益於中國、印度和東南亞國家在教育科技領域的巨額投資。政府的數位教育舉措和不斷提高的網路普及率，為人工智慧驅動的輔導模式的推廣應用創造了有利環境。該地區龐大的學生群體和不斷壯大的中產階級，對個人化學習解決方案的需求也日益成長。本地科技公司正與國際供應商合作，打造符合當地文化習慣的輔導平台。快速的都市化和高等教育入學人數的不斷增加，也進一步推動了市場成長。

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    • 對主要公司進行SWOT分析（最多3家公司）
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    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

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
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧驅動的學術輔導市場：按組件分類

  • 軟體
  • 服務

第6章：全球人工智慧驅動的學術輔導市場：按部署模式分類

  • 基於雲端的
  • 現場
  • 混合

第7章：全球由人工智慧驅動的學術輔導市場：按輔導類型分類

  • 學業表現指導
  • 職業指導和諮詢
  • 研究和論文指導
  • 技能差距輔導
  • 社會情緒學習輔導
  • 考試準備輔導

第8章：全球由人工智慧驅動的學術輔導市場：按應用領域分類

  • K-12教育
  • 高等教育
  • 專業認證項目
  • 企業學習與人力資源發展
  • 考試準備

第9章：全球人工智慧驅動的學術輔導市場：按最終用戶分類

  • 教育機構
  • 教育科技公司
  • 個別學習者
  • 政府機構和非營利組織
  • 公司

第10章：全球由人工智慧驅動的學術輔導市場：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

  • Microsoft Corporation
  • Alphabet Inc.
  • Amazon.com, Inc.
  • IBM Corporation
  • Oracle Corporation
  • Adobe Inc.
  • Pearson plc
  • Chegg, Inc.
  • Duolingo, Inc.
  • Coursera, Inc.
  • Udemy, Inc.
  • 2U, Inc.
  • PowerSchool Holdings, Inc.
  • Instructure Holdings, Inc.
  • Blackboard Inc.
  • Stride, Inc.
  • Carnegie Learning, Inc.
Product Code: SMRC37089

According to Stratistics MRC, the Global AI-Powered Academic Mentoring Market is accounted for $5.0 billion in 2026 and is expected to reach $17.0 billion by 2034 growing at a CAGR of 16.5% during the forecast period. AI-powered academic mentoring refers to intelligent systems that provide personalized guidance, tutoring, and academic support to learners through artificial intelligence algorithms. These platforms utilize natural language processing, machine learning, and adaptive learning technologies to analyze student performance data and deliver customized feedback. The technology encompasses virtual tutoring assistants, predictive analytics for early intervention, and automated curriculum recommendations. AI-powered academic mentoring serves K-12 students, higher education learners, and professionals seeking skill development through data-driven instructional pathways.

Market Dynamics:

Driver:

Personalized learning demand

The growing emphasis on individualized education pathways is driving substantial demand for AI-powered academic mentoring solutions. Educational institutions increasingly recognize that one-size-fits-all approaches fail to address diverse learning styles and paces. AI mentoring platforms analyze vast datasets to tailor content delivery, creating adaptive experiences that improve student engagement and outcomes. Universities and schools invest heavily in these technologies to reduce dropout rates and enhance academic performance. The scalability of AI-driven personalization enables institutions to support larger student populations without proportional increases in faculty staffing.

Restraint:

Data privacy concerns

The collection and analysis of extensive student data raises significant privacy and security concerns that constrain market expansion. Educational institutions must navigate complex regulatory frameworks, including FERPA and GDPR, while implementing AI mentoring systems. Parents and students express apprehension about algorithmic profiling and potential misuse of sensitive academic records. The cost of implementing robust cybersecurity measures and compliance protocols adds substantial overhead. These concerns necessitate transparent data governance policies that can slow adoption timelines.

Opportunity:

Lifelong learning expansion

The accelerating shift toward continuous skill development and lifelong learning creates expansive opportunities for AI-powered academic mentoring platforms. Working professionals increasingly seek flexible, on-demand educational support to remain competitive in rapidly evolving job markets. Corporate learning and development programs integrate AI mentoring to upskill employees efficiently. The proliferation of micro-credentials and professional certifications drives demand for intelligent guidance systems. Partnerships between EdTech providers and enterprises create sustainable revenue streams beyond traditional academic settings.

Threat:

Human tutor preference

The persistent preference for human interaction in educational settings poses a significant threat to widespread AI mentoring adoption. Many learners and educators value the empathy, intuition, and nuanced understanding that human mentors provide. Skepticism regarding AI's ability to address complex socio-emotional learning needs limits market penetration. Resistance from teaching unions and faculty concerned about job displacement creates institutional barriers. The perception that AI mentoring represents a cost-cutting measure rather than educational enhancement undermines acceptance.

Covid-19 Impact:

The COVID-19 pandemic fundamentally accelerated the adoption of AI-powered academic mentoring as educational institutions worldwide transitioned to remote learning models. Initial disruptions caused temporary setbacks in implementation timelines, yet the crisis revealed critical gaps in personalized student support during virtual instruction. Post-pandemic, hybrid learning models have become permanent fixtures, driving sustained investment in intelligent mentoring platforms. Educational institutions now prioritize resilient, technology-enabled support systems that can function across diverse delivery modalities.

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

The services segment is expected to account for the largest market share during the forecast period, due to the comprehensive need for implementation support, training, and ongoing maintenance of AI mentoring platforms. Educational institutions require extensive professional services to integrate these systems with existing learning management infrastructure. Consulting services help customize AI algorithms to specific institutional curricula and pedagogical approaches. The complexity of deploying machine learning models necessitates specialized technical support and continuous optimization. Service providers generate recurring revenue through subscription-based support contracts and system upgrades.

The cloud-based segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud-based segment is predicted to witness the highest growth rate, driven by the scalability, accessibility, and cost-effectiveness of cloud deployment models for academic mentoring platforms. Cloud infrastructure enables seamless integration with existing educational technology ecosystems while reducing capital expenditure requirements. The flexibility of cloud-based solutions supports remote and hybrid learning environments that have become standard post-pandemic. Educational institutions of all sizes can access enterprise-grade AI mentoring capabilities without extensive IT infrastructure investments.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to early adoption of advanced educational technologies and substantial investment in EdTech infrastructure across the United States and Canada. Major technology companies, including Microsoft, Alphabet, and Amazon, drive innovation in AI-powered learning solutions. Government initiatives supporting digital transformation in education accelerate deployment timelines. The presence of leading universities and research institutions creates a strong demand for cutting-edge mentoring platforms. Venture capital funding for EdTech startups sustains a vibrant innovation ecosystem.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by massive investments in educational technology across China, India, and Southeast Asian nations. Government digital education initiatives and increasing internet penetration create fertile ground for AI mentoring adoption. The region's large student population and growing middle class generate substantial demand for personalized learning solutions. Local technology companies partner with international providers to deliver culturally adapted mentoring platforms. Rapid urbanization and expanding higher education enrollment further catalyze market growth.

Key players in the market

Some of the key players in AI-Powered Academic Mentoring Market include Microsoft Corporation, Alphabet Inc., Amazon.com, Inc., IBM Corporation, Oracle Corporation, Adobe Inc., Pearson plc, Chegg, Inc., Duolingo, Inc., Coursera, Inc., Udemy, Inc., 2U, Inc., PowerSchool Holdings, Inc., Instructure Holdings, Inc., Blackboard Inc., Stride, Inc., and Carnegie Learning, Inc..

Key Developments:

In May 2026, Microsoft Corporation launched an enhanced AI tutoring engine integrated with Teams for Education, enabling real-time personalized feedback for K-12 students across partner school districts.

In April 2026, Pearson plc partnered with leading universities to deploy adaptive mentoring platforms that leverage generative AI for automated essay feedback and curriculum recommendations.

In February 2026, Duolingo, Inc. expanded its AI tutoring capabilities with conversational practice modules powered by large language models for immersive language learning experiences.

Components Covered:

  • Software
  • Services

Deployment Modes Covered:

  • Cloud-Based
  • On-Premises
  • Hybrid

Mentoring Types Covered:

  • Academic Performance Mentoring
  • Career Guidance and Counseling
  • Research and Thesis Mentoring
  • Skill Gap Mentoring
  • Social-Emotional Learning Mentoring
  • Exam Preparation Mentoring

Applications Covered:

  • K-12 Education
  • Higher Education
  • Professional Certification Programs
  • Corporate Learning and Development
  • Test Preparation

End Users Covered:

  • Educational Institutions
  • EdTech Companies
  • Individual Learners
  • Government and Non-Profit Organizations
  • Corporate Enterprises

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 Academic Mentoring Market, By Component

  • 5.1 Software
  • 5.2 Services

6 Global AI-Powered Academic Mentoring Market, By Deployment Mode

  • 6.1 Cloud-Based
  • 6.2 On-Premises
  • 6.3 Hybrid

7 Global AI-Powered Academic Mentoring Market, By Mentoring Type

  • 7.1 Academic Performance Mentoring
  • 7.2 Career Guidance and Counseling
  • 7.3 Research and Thesis Mentoring
  • 7.4 Skill Gap Mentoring
  • 7.5 Social-Emotional Learning Mentoring
  • 7.6 Exam Preparation Mentoring

8 Global AI-Powered Academic Mentoring Market, By Application

  • 8.1 K-12 Education
  • 8.2 Higher Education
  • 8.3 Professional Certification Programs
  • 8.4 Corporate Learning and Development
  • 8.5 Test Preparation

9 Global AI-Powered Academic Mentoring Market, By End User

  • 9.1 Educational Institutions
  • 9.2 EdTech Companies
  • 9.3 Individual Learners
  • 9.4 Government and Non-Profit Organizations
  • 9.5 Corporate Enterprises

10 Global AI-Powered Academic Mentoring 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 Microsoft Corporation
  • 13.2 Alphabet Inc.
  • 13.3 Amazon.com, Inc.
  • 13.4 IBM Corporation
  • 13.5 Oracle Corporation
  • 13.6 Adobe Inc.
  • 13.7 Pearson plc
  • 13.8 Chegg, Inc.
  • 13.9 Duolingo, Inc.
  • 13.10 Coursera, Inc.
  • 13.11 Udemy, Inc.
  • 13.12 2U, Inc.
  • 13.13 PowerSchool Holdings, Inc.
  • 13.14 Instructure Holdings, Inc.
  • 13.15 Blackboard Inc.
  • 13.16 Stride, Inc.
  • 13.17 Carnegie Learning, Inc.

List of Tables

  • Table 1 Global AI-Powered Academic Mentoring Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Powered Academic Mentoring Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI-Powered Academic Mentoring Market Outlook, By Software (2023-2034) ($MN)
  • Table 4 Global AI-Powered Academic Mentoring Market Outlook, By Services (2023-2034) ($MN)
  • Table 5 Global AI-Powered Academic Mentoring Market Outlook, By Deployment Mode (2023-2034) ($MN)
  • Table 6 Global AI-Powered Academic Mentoring Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 7 Global AI-Powered Academic Mentoring Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 8 Global AI-Powered Academic Mentoring Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 9 Global AI-Powered Academic Mentoring Market Outlook, By Mentoring Type (2023-2034) ($MN)
  • Table 10 Global AI-Powered Academic Mentoring Market Outlook, By Academic Performance Mentoring (2023-2034) ($MN)
  • Table 11 Global AI-Powered Academic Mentoring Market Outlook, By Career Guidance and Counseling (2023-2034) ($MN)
  • Table 12 Global AI-Powered Academic Mentoring Market Outlook, By Research and Thesis Mentoring (2023-2034) ($MN)
  • Table 13 Global AI-Powered Academic Mentoring Market Outlook, By Skill Gap Mentoring (2023-2034) ($MN)
  • Table 14 Global AI-Powered Academic Mentoring Market Outlook, By Social-Emotional Learning Mentoring (2023-2034) ($MN)
  • Table 15 Global AI-Powered Academic Mentoring Market Outlook, By Exam Preparation Mentoring (2023-2034) ($MN)
  • Table 16 Global AI-Powered Academic Mentoring Market Outlook, By Application (2023-2034) ($MN)
  • Table 17 Global AI-Powered Academic Mentoring Market Outlook, By K-12 Education (2023-2034) ($MN)
  • Table 18 Global AI-Powered Academic Mentoring Market Outlook, By Higher Education (2023-2034) ($MN)
  • Table 19 Global AI-Powered Academic Mentoring Market Outlook, By Professional Certification Programs (2023-2034) ($MN)
  • Table 20 Global AI-Powered Academic Mentoring Market Outlook, By Corporate Learning and Development (2023-2034) ($MN)
  • Table 21 Global AI-Powered Academic Mentoring Market Outlook, By Test Preparation (2023-2034) ($MN)
  • Table 22 Global AI-Powered Academic Mentoring Market Outlook, By End User (2023-2034) ($MN)
  • Table 23 Global AI-Powered Academic Mentoring Market Outlook, By Educational Institutions (2023-2034) ($MN)
  • Table 24 Global AI-Powered Academic Mentoring Market Outlook, By EdTech Companies (2023-2034) ($MN)
  • Table 25 Global AI-Powered Academic Mentoring Market Outlook, By Individual Learners (2023-2034) ($MN)
  • Table 26 Global AI-Powered Academic Mentoring Market Outlook, By Government and Non-Profit Organizations (2023-2034) ($MN)
  • Table 27 Global AI-Powered Academic Mentoring Market Outlook, By Corporate Enterprises (2023-2034) ($MN)

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