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市场调查报告书
商品编码
1725075

2032 年智慧学习市场预测：按组件、学习类型、部署模式、技术、最终用户和地区进行的全球分析

Smart Learning Market Forecasts to 2032 - Global Analysis By Component (Hardware, Software and Services), Learning Type, Deployment Mode, Technology, 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个工作天内

价格

根据 Stratistics MRC 预测，全球智慧学习市场规模预计在 2025 年达到 1,012 亿美元，到 2032 年将达到 4,565 亿美元，复合年增长率为 24%。

「智慧学习」是指结合尖端科技驱动的教育策略，结合数位工具、资源和平台来提高学生的学习成果。它使用数据分析、互动式学习材料和人工智慧为每个学生提供灵活、个人化的学习路线。智慧学习允许即时回馈、团队合作和存取广泛的资源，从而促进更动态和有趣的学习环境。这种方法让学生可以按照自己的步调学习，培养批判性思维并确保更好的可及性，使教育更有效、更有效率，并能根据每个学生的个人要求和偏好进行客製化。

混合式学习模式

混合学习模式将传统的面对面教育与数位工具结合，提供灵活、个人化的体验，从而改变智慧学习市场。这些模型透过人工智慧和数据分析实现即时互动、提高参与度并提高效率。终身学习和技能提升的需求不断增长，推动着市场成长，混合式学习因其成本效益和广泛的能力而被教育机构和企业部门采用。

抵制人工智慧整合

许多教育机构和教育工作者不愿采用人工智慧的主要原因是对技术缺乏信任以及担心失业。这种抵制减缓了个人化学习策略的采用，而这种策略可以提高学生的参与度和表现。如果没有人工智慧，教育机构将失去可以改善课程设计和学习成果的数据主导洞察力。高昂的前期成本和对资料隐私的担忧进一步引发了反对。因此，智慧学习技术的全部潜力尚未在许多教育环境中实现。

扩大地方教育

随着农村地区网路连结性的改善，智慧教室和数位学习技术将变得更加普及。教育科技的使用受到政府计画和地方教育经费的推动。对于瞄准服务不足地区的教育科技公司来说，这意味着更大的消费群。此外，使用人工智慧内容和虚拟教室的智慧学习可以帮助解决农村地区的教师短缺问题。总体而言，农村教育的扩展将创造新的市场并加速教育的数位转型。

技术依赖

如果偏远地区或欠发达地区的学生无法使用设备或互联网，他们可能会被排除在外，因为他们过于依赖科技。经常发生的硬体和软体故障可能会阻碍学习并降低学习的品质和一致性。此外，平台的频繁变化和发展需要持续的培训，这既昂贵又耗时。对一些消费者来说，对网路安全和资料保护的担忧可能会阻碍他们充分利用智慧学习产品的潜力。最后，过多的萤幕时间和过少的面对面学习会影响学生的社交和认知发展。

COVID-19的影响

新冠疫情显着加速了智慧学习市场的成长。随着学校和大学转向线上和混合学习，对数位教育工具、平台和技术的需求激增。全球对虚拟教室、数位学习解决方案和互动教育内容的需求日益增加。这种转变凸显了智慧学习解决方案的重要性，并推动了对人工智慧、AR/VR 和云端基础的平台等技术的投资。随着远距教育越来越融入传统教育体系，预计市场将持续成长。

预计硬体部分将成为预测期内最大的部分

由于硬体在为数位教育提供基本基础设施方面发挥重要作用，预计在预测期内硬体部分将占据最大的市场占有率。智慧投影机、iPad、AR/ VR头戴装置、互动式白板等是一些可以提高学生课堂参与度和互动性的设备。可携式设备的日益普及使得远距学习和客製化学习体验成为可能。对教育机构数位基础设施升级的投资不断增加，推动了对尖端硬体解决方案的需求。此外，人工智慧和物联网在教育设备中的应用正在推动硬体领域的市场扩张。

预计在预测期内，企业部门的复合年增长率最高。

由于对员工技能提升和持续培训的需求，预计企业部门将在预测期内实现最高成长率。企业越来越多地使用智慧学习工具来提高员工的生产力和灵活性。人工智慧学习材料和云端基础的学习平台可以帮助简化企业培训计画。远距工作的趋势正在推动对适应性强、技术先进的学习解决方案的需求。因此，企业在智慧学习技术上的支出不断增加，影响着市场的成长。

占比最大的地区：

由于网路普及率不断提高、智慧型手机普及率不断提高以及政府对数位教育的投资不断增加，预计亚太地区将在预测期内占据最大的市场占有率。中国、印度、日本和韩国等国家处于领先地位，采用人工智慧主导的学习平台、虚拟教室和个人化教育工具。学生和专业人士对灵活、互动且易于存取的学习解决方案的需求正在急剧增长。这种蓬勃发展的成长反映了该地区致力于利用先进技术改造传统教育的决心。

复合年增长率最高的地区：

受技术进步、互联网广泛应用以及个性化教育需求不断增长的推动，北美地区预计将在预测期内呈现最高的复合年增长率。随着人工智慧、AR/VR 和云端基础的平台的整合，教育机构和企业培训中心正在将传统学习转变为动态的互动体验。该地区强大的数位基础设施，加上政府在数位学习的倡议和投资，正在进一步加速电子学习的采用。主要企业专注于创新，以提高不同学习者群体的可及性、参与度和成果。

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目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 研究范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 限制因素
  • 机会
  • 威胁
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买家的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

第五章 全球智慧学习市场（按组件）

  • 硬体
    • 互动式白板
    • 平板电脑和行动装置
    • 智慧白板
    • VR头戴装置
    • 投影仪
  • 软体
    • 学习管理系统（LMS）
    • 企业资源规划（ERP）
    • 自适应学习平台
    • 评级系统
  • 服务
    • 託管服务
    • 专业服务

第六章 全球智慧学习市场（依学习类型）

  • 同步学习
  • 非同步学习
  • 混合式学习
  • 协作学习
  • 其他学习类型

第七章 全球智慧学习市场（依部署模式）

  • 本地
  • 云端基础

8. 全球智能学习市场（按技术）

  • 人工智慧（AI）
  • 扩增实境（AR）/虚拟实境（VR）
  • 机器学习（ML）
  • 物联网 (IoT)
  • 区块链
  • 巨量资料分析
  • 其他技术

第九章 全球智慧学习市场（按最终用户）

  • 学术的
  • 公司
  • 政府
  • 其他最终用户

第十章 全球智慧学习市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十二章 公司概况

  • IBM Corporation
  • Microsoft Corporation
  • Google
  • Apple Inc.
  • Pearson Education
  • Samsung Electronics
  • NVIDIA Corporation
  • Lenovo Group Limited
  • Cisco Systems, Inc.
  • Blackboard Inc.
  • D2L
  • McGraw-Hill Education
  • Knewton
  • Houghton Mifflin Harcourt
  • Coursera
  • Udemy
  • Quizlet
  • Vernier Software & Technology
Product Code: SMRC29381

According to Stratistics MRC, the Global Smart Learning Market is accounted for $101.2 billion in 2025 and is expected to reach $456.5 billion by 2032 growing at a CAGR of 24% during the forecast period. The term "smart learning" is a cutting-edge, technologically orientated teaching strategy that incorporates digital tools, resources, and platforms to improve student learning. It uses data analytics, interactive material, and artificial intelligence to give students individualised, flexible learning routes. Real-time feedback, teamwork, and access to a variety of resources are made possible by smart learning, which promotes a more dynamic and interesting learning environment. This approach makes education more effective, efficient, and customised to each student's requirements and preferences by enabling them to learn at their own pace, fostering critical thinking, and guaranteeing better accessibility.

Market Dynamics:

Driver:

Hybrid learning models

Hybrid learning models are transforming the smart learning market by combining traditional in-person education with digital tools, offering a flexible, personalized experience. These models enable real-time interaction, enhance engagement, and boost efficiency through AI and data analytics. The growing demand for lifelong learning and upskilling drives market growth, and hybrid learning is being adopted by educational institutions and corporate sectors for its cost-effectiveness and wide-reaching capabilities.

Restraint:

Resistance to AI integration

A lack of faith in technology and concerns about job displacement are the main reasons why many educational institutions and educators are reluctant to embrace AI. The adoption of individualised learning strategies that improve student engagement and results is slowed down by this resistance. Institutions lose out on data-driven insights that could enhance curriculum design and learning effectiveness in the absence of AI. The opposition is further fuelled by high upfront expenses and worries about data privacy. Because of this, in many educational contexts, the full potential of smart learning technology is yet unrealised.

Opportunity:

Rural education expansion

Smart classrooms and e-learning technologies become more widely available as internet connectivity improves in rural regions. The use of educational technology is fuelled by government programs and funding for rural education. For edtech companies that target underserved locations, this results in an expanding consumer base. Using AI-powered content and virtual instruction, smart learning also aids in addressing the teacher shortage in rural areas. All things considered, expanding education in rural areas creates new markets and speeds up the digital transformation of education.

Threat:

Technological dependence

Students in isolated or undeveloped regions with little access to devices or the internet may be excluded if they rely too heavily on technology. Regular hardware or software malfunctions might interfere with learning and lower its quality and consistency. Furthermore, ongoing training is necessary due to platforms' frequent changes and evolution, which can be expensive and time-consuming. Some consumers are discouraged from utilising smart learning products to their full potential due to concerns about cybersecurity and data protection. Finally, too much screen time and little in-person engagement can affect students' social and cognitive development.

Covid-19 Impact

The COVID-19 pandemic significantly accelerated the growth of the smart learning market. With schools and universities shifting to online and hybrid learning, demand for digital education tools, platforms, and technologies surged. The need for virtual classrooms, e-learning solutions, and interactive educational content increased globally. This shift highlighted the importance of smart learning solutions, boosting investments in technologies like AI, AR/VR, and cloud-based platforms. The market is expected to continue growing as remote learning becomes more integrated into traditional education systems.

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

The hardware segment is expected to account for the largest market share during the forecast period by providing the essential infrastructure for digital education. Smart projectors, iPads, AR/VR headsets, and interactive whiteboards are some of the gadgets that improve student participation and interaction in the classroom. Remote and customised learning experiences are made possible by the increasing use of portable devices. The need for cutting-edge hardware solutions is increased by rising investments in educational institutions to upgrade their digital infrastructure. Furthermore, learning gadgets' incorporation of AI and IoT is propelling the market's hardware segment's expansion.

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

Over the forecast period, the corporate segment is predicted to witness the highest growth rate, due to the demand for upskilling and continuous employee training. Smart learning tools are being used by businesses more and more to increase worker productivity and flexibility. AI-powered material and cloud-based learning platforms facilitate the simplification of corporate training initiatives. Trends towards remote work have increased need for adaptable, technologically advanced learning solutions. As a result, business expenditures on intelligent learning technologies keep rising, influencing market growth.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share due to rising internet penetration, growing smartphone adoption, and increasing government investments in digital education. Countries like China, India, Japan, and South Korea are at the forefront, embracing AI-driven learning platforms, virtual classrooms, and personalized education tools. The demand for flexible, interactive, and accessible learning solutions is surging among students and professionals alike. This dynamic growth reflects the region's commitment to transforming traditional education through advanced technologies.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, driven by advancements in technology, widespread internet penetration, and increasing demand for personalized education. With the integration of AI, AR/VR, and cloud-based platforms, educational institutions and corporate training centers are transforming traditional learning into dynamic, interactive experiences. The region's strong digital infrastructure, coupled with government initiatives and investments in e-learning, is further accelerating adoption. Key players are focusing on innovation to enhance accessibility, engagement, and outcomes across diverse learner segments.

Key players in the market

Some of the key players profiled in the Smart Learning Market include IBM Corporation, Microsoft Corporation, Google, Apple Inc., Pearson Education, Samsung Electronics, NVIDIA Corporation, Lenovo Group Limited, Cisco Systems, Inc., Blackboard Inc., D2L, McGraw-Hill Education, Knewton, Houghton Mifflin Harcourt, Coursera, Udemy, Vernier Software & Technology and Quizlet.

Key Developments:

In February 2025, IBM completed the acquisition of HashiCorp, a move aimed at bolstering its capabilities in managing hybrid cloud environments and enhancing its generative AI portfolio, especially the watsonx suite. This acquisition is expected to contribute to IBM's revenue growth and expand its market footprint.

In February 2024, IBM and Wipro expanded their partnership to launch the Wipro Enterprise AI-Ready Platform, leveraging IBM's watsonx AI and data platform. This platform aims to accelerate enterprise adoption of generative AI by providing customized AI environments, integrating tools, large language models, streamlined processes, and robust governance.

Components Covered:

  • Hardware
  • Software
  • Services

Learning Types Covered:

  • Synchronous Learning
  • Asynchronous Learning
  • Blended Learning
  • Collaborative Learning
  • Other Learning Types

Deployment Modes Covered:

  • On-Premise
  • Cloud-Based

Technologies Covered:

  • Artificial Intelligence (AI)
  • Augmented Reality (AR) / Virtual Reality (VR)
  • Machine Learning (ML)
  • Internet of Things (IoT)
  • Blockchain
  • Big Data Analytics
  • Other Technologies

End Users Covered:

  • Academic
  • Corporate
  • Government
  • 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 End User Analysis
  • 3.7 Emerging Markets
  • 3.8 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 Smart Learning Market, By Component

  • 5.1 Introduction
  • 5.2 Hardware
    • 5.2.1 Interactive Whiteboards
    • 5.2.2 Tablets & Mobile Devices
    • 5.2.3 Smartboards
    • 5.2.4 VR Headsets
    • 5.2.5 Projectors
  • 5.3 Software
    • 5.3.1 Learning Management Systems (LMS)
    • 5.3.2 Enterprise Resource Planning (ERP)
    • 5.3.3 Adaptive Learning Platforms
    • 5.3.4 Assessment Systems
  • 5.4 Services
    • 5.4.1 Managed Services
    • 5.4.2 Professional Services

6 Global Smart Learning Market, By Learning Type

  • 6.1 Introduction
  • 6.2 Synchronous Learning
  • 6.3 Asynchronous Learning
  • 6.4 Blended Learning
  • 6.5 Collaborative Learning
  • 6.6 Other Learning Types

7 Global Smart Learning Market, By Deployment Mode

  • 7.1 Introduction
  • 7.2 On-Premise
  • 7.3 Cloud-Based

8 Global Smart Learning Market, By Technology

  • 8.1 Introduction
  • 8.2 Artificial Intelligence (AI)
  • 8.3 Augmented Reality (AR) / Virtual Reality (VR)
  • 8.4 Machine Learning (ML)
  • 8.5 Internet of Things (IoT)
  • 8.6 Blockchain
  • 8.7 Big Data Analytics
  • 8.8 Other Technologies

9 Global Smart Learning Market, By End User

  • 9.1 Introduction
  • 9.2 Academic
  • 9.3 Corporate
  • 9.4 Government
  • 9.5 Other End Users

10 Global Smart Learning Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 IBM Corporation
  • 12.2 Microsoft Corporation
  • 12.3 Google
  • 12.4 Apple Inc.
  • 12.5 Pearson Education
  • 12.6 Samsung Electronics
  • 12.7 NVIDIA Corporation
  • 12.8 Lenovo Group Limited
  • 12.9 Cisco Systems, Inc.
  • 12.10 Blackboard Inc.
  • 12.11 D2L
  • 12.12 McGraw-Hill Education
  • 12.13 Knewton
  • 12.14 Houghton Mifflin Harcourt
  • 12.15 Coursera
  • 12.16 Udemy
  • 12.17 Quizlet
  • 12.18 Vernier Software & Technology

List of Tables

  • Table 1 Global Smart Learning Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Smart Learning Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global Smart Learning Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 4 Global Smart Learning Market Outlook, By Interactive Whiteboards (2024-2032) ($MN)
  • Table 5 Global Smart Learning Market Outlook, By Tablets & Mobile Devices (2024-2032) ($MN)
  • Table 6 Global Smart Learning Market Outlook, By Smartboards (2024-2032) ($MN)
  • Table 7 Global Smart Learning Market Outlook, By VR Headsets (2024-2032) ($MN)
  • Table 8 Global Smart Learning Market Outlook, By Projectors (2024-2032) ($MN)
  • Table 9 Global Smart Learning Market Outlook, By Software (2024-2032) ($MN)
  • Table 10 Global Smart Learning Market Outlook, By Learning Management Systems (LMS) (2024-2032) ($MN)
  • Table 11 Global Smart Learning Market Outlook, By Enterprise Resource Planning (ERP) (2024-2032) ($MN)
  • Table 12 Global Smart Learning Market Outlook, By Adaptive Learning Platforms (2024-2032) ($MN)
  • Table 13 Global Smart Learning Market Outlook, By Assessment Systems (2024-2032) ($MN)
  • Table 14 Global Smart Learning Market Outlook, By Services (2024-2032) ($MN)
  • Table 15 Global Smart Learning Market Outlook, By Managed Services (2024-2032) ($MN)
  • Table 16 Global Smart Learning Market Outlook, By Professional Services (2024-2032) ($MN)
  • Table 17 Global Smart Learning Market Outlook, By Learning Type (2024-2032) ($MN)
  • Table 18 Global Smart Learning Market Outlook, By Synchronous Learning (2024-2032) ($MN)
  • Table 19 Global Smart Learning Market Outlook, By Asynchronous Learning (2024-2032) ($MN)
  • Table 20 Global Smart Learning Market Outlook, By Blended Learning (2024-2032) ($MN)
  • Table 21 Global Smart Learning Market Outlook, By Collaborative Learning (2024-2032) ($MN)
  • Table 22 Global Smart Learning Market Outlook, By Other Learning Types (2024-2032) ($MN)
  • Table 23 Global Smart Learning Market Outlook, By Deployment Mode (2024-2032) ($MN)
  • Table 24 Global Smart Learning Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 25 Global Smart Learning Market Outlook, By Cloud-Based (2024-2032) ($MN)
  • Table 26 Global Smart Learning Market Outlook, By Technology (2024-2032) ($MN)
  • Table 27 Global Smart Learning Market Outlook, By Artificial Intelligence (AI) (2024-2032) ($MN)
  • Table 28 Global Smart Learning Market Outlook, By Augmented Reality (AR) / Virtual Reality (VR) (2024-2032) ($MN)
  • Table 29 Global Smart Learning Market Outlook, By Machine Learning (ML) (2024-2032) ($MN)
  • Table 30 Global Smart Learning Market Outlook, By Internet of Things (IoT) (2024-2032) ($MN)
  • Table 31 Global Smart Learning Market Outlook, By Blockchain (2024-2032) ($MN)
  • Table 32 Global Smart Learning Market Outlook, By Big Data Analytics (2024-2032) ($MN)
  • Table 33 Global Smart Learning Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 34 Global Smart Learning Market Outlook, By End User (2024-2032) ($MN)
  • Table 35 Global Smart Learning Market Outlook, By Academic (2024-2032) ($MN)
  • Table 36 Global Smart Learning Market Outlook, By Corporate (2024-2032) ($MN)
  • Table 37 Global Smart Learning Market Outlook, By Government (2024-2032) ($MN)
  • Table 38 Global Smart Learning Market Outlook, By Other End Users (2024-2032) ($MN)

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