封面
市场调查报告书
商品编码
1721380

AI代理商市场 (~2035年):代理商系统类型·应用领域·代理商所扮演的角色类型·技术类型·产品类型·企业规模·主要各地区的产业趋势与全球预测

AI Agents Market till 2035: Distribution by Type of Agent System, Areas of Application, by Type of Agent Role, by Type of Technology, by Type of Product by Company Size, and Key Geographical Regions : Industry Trends and Global Forecasts

出版日期: | 出版商: Roots Analysis | 英文 168 Pages | 商品交期: 2-10个工作天内

价格
简介目录

预计到 2035 年,全球 AI 代理市场规模将从目前的 52.9 亿美元增长至 2,168 亿美元,预测期内的复合年增长率为 40.15%。

AI Agents Market-IMG1

预计在预测期内,全球 AI 代理市场将保持健康成长,这得益于自动化技术的应用日益普及,以提高营运效率,以及对个人化客户体验的需求日益增长。

AI代理商的市场机会:各市场区隔

代理商各系统类型

  • 多代理商
  • 单一代理商

应用各领域

  • 顾客服务&虚拟助手
  • 医疗保健

按代理商所扮演的角色

  • 代码生成
  • 顾客服务
  • 行销
  • 生产率提高&个人助手
  • 销售

各技术类型

  • Deep学习
  • 机器学习

各产品类型

  • 自製代理商
  • 即时展开代理商

不同企业规模

  • 自製代理商
  • 即时展开代理商

各地区

  • 北美
  • 美国
  • 加拿大
  • 墨西哥
  • 其他的北美各国
  • 欧洲
  • 奥地利
  • 比利时
  • 丹麦
  • 法国
  • 德国
  • 爱尔兰
  • 义大利
  • 荷兰
  • 挪威
  • 俄罗斯
  • 西班牙
  • 瑞典
  • 瑞士
  • 英国
  • 其他欧洲各国
  • 亚洲
  • 中国
  • 印度
  • 日本
  • 新加坡
  • 韩国
  • 其他亚洲各国
  • 南美
  • 巴西
  • 智利
  • 哥伦比亚
  • 委内瑞拉
  • 其他的南美各国
  • 中东·北非
  • 埃及
  • 伊朗
  • 伊拉克
  • 以色列
  • 科威特
  • 沙乌地阿拉伯
  • UAE
  • 其他的中东·北非各国
  • 全球其他地区
  • 澳洲
  • 纽西兰
  • 其他的国家

人工智慧代理市场:成长与趋势

尤其是自然语言处理 (NLP) 应用的重大进步,使人工智慧代理能够更好地理解和生成人类语言,从而实现与使用者的高阶互动。因此,越来越多的企业采用人工智慧驱动的自动化来提高营运效率,而人工智慧代理正成为客户服务、医疗保健和金融等多个领域的重要工具。

此外,对高度个人化体验的需求日益增长,以及将AI代理整合到业务流程中,也推动了AI代理市场的成长。企业正在采用AI代理来优化营运、降低成本,并透过个人化服务提升客户参与度。

针对特定产业设计的专业虚拟助理的兴起也为市场成长提供了机会。这些代理可以为法律和医疗等领域的特定需求提供专业服务。

本报告提供全球AI代理商的市场调查、彙整市场概要,背景,市场影响因素的分析,市场规模的转变·预测,各种区分·各地区的详细分析,竞争情形,主要企业简介等资讯。

目录

章节I:报告概要

第1章 序文

第2章 调查手法

第3章 市场动态

第4章 宏观经济指标

章节II:定性的洞察

第5章 摘要整理

第6章 简介

第7章 法规情势

章节III:市场概要

第8章 主要企业的总括的资料库

第9章 竞争情形

第10章 閒置频段分析

第11章 竞争分析

第12章 AI代理商市场上Start-Ups生态系统

章节IV: 企业简介

第13章 企业简介

  • 章概要
  • Alibaba Group
  • Amazon Web Services
  • Apple
  • Avaamo
  • Baidu
  • Google
  • Hewlett Packard
  • IBM
  • IPsoft
  • Meta
  • Microsoft
  • NVIDIA
  • Nuance Communications
  • Oracle
  • Salesforce
  • SAP SE
  • SoundHound

第5章 市场趋势

第14章 大趋势分析

第15章 未满足需求的分析

第16章 专利分析

第17章 最近的趋势

第6章 市场机会分析

第18章 全球AI代理商市场

第19章 代理商各系统类型的市场机会

第20章 应用各领域的市场机会

第21章 代理商所扮演的角色类别的市场机会

第22章 各技术的市场机会

第23章 各产品类型的市场机会

第24章 北美AI代理商的市场机会

第25章 欧洲的AI代理商的市场机会

第26章 亚洲的AI代理商的市场机会

第27章 中东·北非的AI代理商的市场机会

第28章 南美的AI代理商的市场机会

第29章 全球其他地区的AI代理商的市场机会

第30章 市场集中分析:各主要企业分布

第31章 邻近市场分析

第7章 策略工具

第32章 主要成功策略

第33章 波特的五力分析

第34章 SWOT分析

第35章 价值链分析

第36章 ROOTS的策略性建议

章节VIII:其他的垄断的洞察

第37章 来自1次调查的洞察

第38章 总论

章节IX:附录

第39章 表格形式资料

第40章 企业·团体一览

第41章 客制化的机会

第42章 ROOTS的订阅服务

第43章 着者详细内容

简介目录
Product Code: RAICT300157

GLOBAL AI AGENTS MARKET: OVERVIEW

As per Roots Analysis, the global AI agents market size is estimated to grow from USD 5.29 billion in the current year to USD 216.8 billion by 2035, at a CAGR of 40.15% during the forecast period, till 2035.

AI Agents Market - IMG1

Driven by the growing adoption of automation to increase the operational efficiency of the companies, along with rising demand for personalized customer experiences, the global AI agents market is expected to grow at a healthy pace during the forecast period.

The opportunity for AI agents market has been distributed across the following segments:

Type of Agent System

  • Multi Agent
  • Single Agent

Areas of Application

  • Customer Service & Virtual Assistants
  • Healthcare

Type of Agent Role

  • Code Generation
  • Customer Service
  • Marketing
  • Productivity & Personal Assistants
  • Sales

Type of Technology

  • Deep Learning
  • Machine Learning

Type of Product

  • Build Your Own Agents
  • Ready to Deploy Agents

Company Size

  • Build Your Own Agents
  • Ready to Deploy Agents

Geographical Regions

  • North America
  • US
  • Canada
  • Mexico
  • Other North American countries
  • Europe
  • Austria
  • Belgium
  • Denmark
  • France
  • Germany
  • Ireland
  • Italy
  • Netherlands
  • Norway
  • Russia
  • Spain
  • Sweden
  • Switzerland
  • UK
  • Other European countries
  • Asia
  • China
  • India
  • Japan
  • Singapore
  • South Korea
  • Other Asian countries
  • Latin America
  • Brazil
  • Chile
  • Colombia
  • Venezuela
  • Other Latin American countries
  • Middle East and North Africa
  • Egypt
  • Iran
  • Iraq
  • Israel
  • Kuwait
  • Saudi Arabia
  • UAE
  • Other MENA countries
  • Rest of the World
  • Australia
  • New Zealand
  • Other countries

AI AGENTS MARKET: GROWTH AND TRENDS

Artificial intelligence (AI) agents are software entities that operate autonomously or semi-autonomously to carry out certain tasks or roles in a digital setting. They utilize AI techniques like machine learning, natural language processing, and decision-making algorithms to function independently or alongside other agents and systems. Notably, the AI agents market is witnessing growth, owing to the significant improvements in natural language processing (NLP) applications, which enhance the capability of AI agents to comprehend and generate human language, facilitating more advanced interactions with users. As organizations increasingly adopt AI-driven automation to boost their operational efficiency, AI agents are becoming vital tools across multiple sectors, including customer service, healthcare, and finance.

Futhermore, it is important to note that the growth of the market is also driven by the increasing need for highly personalized experience and the integration of AI agents into business processes. Companies are choosing to implement AI agents to optimize operations, lower costs, and improve customer engagement through tailored interactions.

Moreover, the rise of specialized virtual assistants designed for specific industries offers opportunities for growth, as these agents can meet tailored needs within sectors such as legal and healthcare.

AI AGENTS MARKET: KEY SEGMENTS

Market Share by Type of Agent System

Based on the type of agent system, the global AI agents market is segmented into multi-agents and single agents. According to our estimates, currently, single agents segment captures the majority share of the market. This can be attributed to the easier and quicker implementation of single-agent systems compared to their multi-agent counterparts. Organizations can readily deploy these systems without requiring extensive customization, making them an ideal choice for companies aiming to enhance their efficiency quickly. Additionally, the costs related to the development and deployment of single-agent systems are generally lower when compared to multi-agent systems. However, multi-agents segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Areas of Application

Based on the areas of application, the AI agents market is segmented into customer service & virtual assistants, and healthcare. According to our estimates, currently, customer service and virtual assistants segment captures the majority share of the market. This can be attributed to the rising use of AI agents by companies to automate tasks in customer service, which leads to enhanced efficiency and lower operational costs. Moreover, AI agents can manage a large number of customer interactions at the same time, allowing companies to scale their customer service capabilities without the requirement of hiring additional staff. However, healthcare segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Farming Environment

Based on the type of farming environment, the AI agents market is segmented into indoor and outdoor. According to our estimates, currently, outdoor segment captures the majority share of the market. This can be attributed to the demand for automation in labor-intensive agricultural tasks. The growth in technology and economic efficiency is promoting the use of robots, such as agricultural drones and autonomous tractors. However, indoor segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Agent Role

Based on the type of agent role, the AI agents market is segmented into code generation, customer service, marketing, productivity & personal assistants, and sales. According to our estimates, currently, code generation segment captures the majority share of the market. This can be attributed to the rising use of coding agents, as they simplify the coding process, enhance productivity, and shorten time to market. These AI-powered agents can automatically generate code, troubleshoot issues, and propose enhancements, allowing developers to focus on more complex and creative tasks.

Market Share by Type of Technology

Based on the type of technology, the AI agents market is segmented into deep learning and machine learning. According to our estimates, currently, machine learning segment captures the majority share of the market. This can be attributed to the ability of machine learning algorithms to process large volumes of data and rapidly make informed decisions. This not only boosts automation but also enhances overall operational efficiency across multiple sectors. However, deep learning segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Product

Based on the type of product, the AI agents market is segmented into build your own agents, ready to deploy agents. According to our estimates, currently, ready to deploy agents segment captures the majority share of the market. This can be attributed to the pre-built agents' capability to be set up swiftly, enabling businesses to start reaping the benefits of AI technologies right away. However, build your own agents segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Company Size

Based on the company size, the AI agents market is segmented into large, and small and medium enterprises. According to our estimates, currently, large enterprise segment captures the majority share of the market. However, small and medium enterprise segments are anticipated to grow at a higher CAGR during the forecast period. This growth is attributed to their flexibility, innovation, focus on specialized markets, and their capacity to adjust to evolving customer preferences and market dynamics.

Market Share by Geographical Regions

Based on the geographical regions, the AI agents market is segmented into North America, Europe, Asia, Latin America, Middle East and North Africa, and Rest of the World. According to our estimates, currently, North America captures the majority share of the market, owing to the region's extensive use of AI agents for managing routine questions, addressing problems, and providing tailored support.

Example Players in AI Agents Market

  • Alibaba Group
  • Amazon Web Services
  • Apple
  • Avaamo
  • Baidu
  • Google
  • Hewlett Packard
  • IBM
  • IPsoft
  • Meta
  • Microsoft
  • NVIDIA
  • Nuance Communications
  • Oracle
  • Salesforce
  • SAP SE
  • SoundHound

AI AGENTS MARKET: RESEARCH COVERAGE

The report on the AI agents market features insights on various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of the AI agents market, focusing on key market segments, including [A] type of agent system, [B] areas of application, [C] type of agent role, [D] type of technology, [E] type of product, [F] company size, [G] geographical regions.
  • Competitive Landscape: A comprehensive analysis of the companies engaged in the AI agents market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters, [D] ownership structure.
  • Company Profiles: Elaborate profiles of prominent players engaged in the AI agents market, providing details on [A] location of headquarters, [B]company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] AI agents portfolio, [J] moat analysis, [K] recent developments, and an informed future outlook.
  • Megatrends: An evaluation of ongoing megatrends in AI agents industry.
  • Patent Analysis: An insightful analysis of patents filed / granted in the AI agents domain, based on relevant parameters, including [A] type of patent, [B] patent publication year, [C] patent age and [D] leading players.
  • Recent Developments: An overview of the recent developments made in the AI agents market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
  • Porter's Five Forces Analysis: An analysis of five competitive forces prevailing in the AI agents market, including threats of new entrants, bargaining power of buyers, bargaining power of suppliers, threats of substitute products and rivalry among existing competitors.
  • SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.

KEY QUESTIONS ANSWERED IN THIS REPORT

  • How many companies are currently engaged in this market?
  • How are AI agents used in customer service?
  • How are privacy concerns handled in AI agents?
  • What factors are likely to influence the evolution of this market?
  • What is the current and future market size?
  • What is the CAGR of this market?
  • Which agent role is growing the most?
  • How is the current and future market opportunity likely to be distributed across key market segments?

REASONS TO BUY THIS REPORT

  • The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
  • Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
  • The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.

ADDITIONAL BENEFITS

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  • 10% Free Content Customization
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TABLE OF CONTENTS

SECTION I: REPORT OVERVIEW

1. PREFACE

  • 1.1. Introduction
  • 1.2. Market Share Insights
  • 1.3. Key Market Insights
  • 1.4. Report Coverage
  • 1.5. Key Questions Answered
  • 1.6. Chapter Outlines

2. RESEARCH METHODOLOGY

  • 2.1. Chapter Overview
  • 2.2. Research Assumptions
  • 2.3. Database Building
    • 2.3.1. Data Collection
    • 2.3.2. Data Validation
    • 2.3.3. Data Analysis
  • 2.4. Project Methodology
    • 2.4.1. Secondary Research
      • 2.4.1.1. Annual Reports
      • 2.4.1.2. Academic Research Papers
      • 2.4.1.3. Company Websites
      • 2.4.1.4. Investor Presentations
      • 2.4.1.5. Regulatory Filings
      • 2.4.1.6. White Papers
      • 2.4.1.7. Industry Publications
      • 2.4.1.8. Conferences and Seminars
      • 2.4.1.9. Government Portals
      • 2.4.1.10. Media and Press Releases
      • 2.4.1.11. Newsletters
      • 2.4.1.12. Industry Databases
      • 2.4.1.13. Roots Proprietary Databases
      • 2.4.1.14. Paid Databases and Sources
      • 2.4.1.15. Social Media Portals
      • 2.4.1.16. Other Secondary Sources
    • 2.4.2. Primary Research
      • 2.4.2.1. Introduction
      • 2.4.2.2. Types
        • 2.4.2.2.1. Qualitative
        • 2.4.2.2.2. Quantitative
      • 2.4.2.3. Advantages
      • 2.4.2.4. Techniques
        • 2.4.2.4.1. Interviews
        • 2.4.2.4.2. Surveys
        • 2.4.2.4.3. Focus Groups
        • 2.4.2.4.4. Observational Research
        • 2.4.2.4.5. Social Media Interactions
      • 2.4.2.5. Stakeholders
        • 2.4.2.5.1. Company Executives (CXOs)
        • 2.4.2.5.2. Board of Directors
        • 2.4.2.5.3. Company Presidents and Vice Presidents
        • 2.4.2.5.4. Key Opinion Leaders
        • 2.4.2.5.5. Research and Development Heads
        • 2.4.2.5.6. Technical Experts
        • 2.4.2.5.7. Subject Matter Experts
        • 2.4.2.5.8. Scientists
        • 2.4.2.5.9. Doctors and Other Healthcare Providers
      • 2.4.2.6. Ethics and Integrity
        • 2.4.2.6.1. Research Ethics
        • 2.4.2.6.2. Data Integrity
    • 2.4.3. Analytical Tools and Databases

3. MARKET DYNAMICS

  • 3.1. Forecast Methodology
    • 3.1.1. Top-Down Approach
    • 3.1.2. Bottom-Up Approach
    • 3.1.3. Hybrid Approach
  • 3.2. Market Assessment Framework
    • 3.2.1. Total Addressable Market (TAM)
    • 3.2.2. Serviceable Addressable Market (SAM)
    • 3.2.3. Serviceable Obtainable Market (SOM)
    • 3.2.4. Currently Acquired Market (CAM)
  • 3.3. Forecasting Tools and Techniques
    • 3.3.1. Qualitative Forecasting
    • 3.3.2. Correlation
    • 3.3.3. Regression
    • 3.3.4. Time Series Analysis
    • 3.3.5. Extrapolation
    • 3.3.6. Convergence
    • 3.3.7. Forecast Error Analysis
    • 3.3.8. Data Visualization
    • 3.3.9. Scenario Planning
    • 3.3.10. Sensitivity Analysis
  • 3.4. Key Considerations
    • 3.4.1. Demographics
    • 3.4.2. Market Access
    • 3.4.3. Reimbursement Scenarios
    • 3.4.4. Industry Consolidation
  • 3.5. Robust Quality Control
  • 3.6. Key Market Segmentations
  • 3.7. Limitations

4. MACRO-ECONOMIC INDICATORS

  • 4.1. Chapter Overview
  • 4.2. Market Dynamics
    • 4.2.1. Time Period
      • 4.2.1.1. Historical Trends
      • 4.2.1.2. Current and Forecasted Estimates
    • 4.2.2. Currency Coverage
      • 4.2.2.1. Overview of Major Currencies Affecting the Market
      • 4.2.2.2. Impact of Currency Fluctuations on the Industry
    • 4.2.3. Foreign Exchange Impact
      • 4.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
      • 4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
    • 4.2.4. Recession
      • 4.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
      • 4.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
    • 4.2.5. Inflation
      • 4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
      • 4.2.5.2. Potential Impact of Inflation on the Market Evolution
    • 4.2.6. Interest Rates
      • 4.2.6.1. Overview of Interest Rates and Their Impact on the Market
      • 4.2.6.2. Strategies for Managing Interest Rate Risk
    • 4.2.7. Commodity Flow Analysis
      • 4.2.7.1. Type of Commodity
      • 4.2.7.2. Origins and Destinations
      • 4.2.7.3. Values and Weights
      • 4.2.7.4. Modes of Transportation
    • 4.2.8. Global Trade Dynamics
      • 4.2.8.1. Import Scenario
      • 4.2.8.2. Export Scenario
    • 4.2.9. War Impact Analysis
      • 4.2.9.1. Russian-Ukraine War
      • 4.2.9.2. Israel-Hamas War
    • 4.2.10. COVID Impact / Related Factors
      • 4.2.10.1. Global Economic Impact
      • 4.2.10.2. Industry-specific Impact
      • 4.2.10.3. Government Response and Stimulus Measures
      • 4.2.10.4. Future Outlook and Adaptation Strategies
    • 4.2.11. Other Indicators
      • 4.2.11.1. Fiscal Policy
      • 4.2.11.2. Consumer Spending
      • 4.2.11.3. Gross Domestic Product (GDP)
      • 4.2.11.4. Employment
      • 4.2.11.5. Taxes
      • 4.2.11.6. R&D Innovation
      • 4.2.11.7. Stock Market Performance
      • 4.2.11.8. Supply Chain
      • 4.2.11.9. Cross-Border Dynamics

SECTION II: QUALITATIVE INSIGHTS

5. EXECUTIVE SUMMARY

6. INTRODUCTION

  • 6.1. Chapter Overview
  • 6.2. Overview of AI Agents Market
    • 6.2.1. Type of Agent System
    • 6.2.2. Areas of Application
    • 6.2.3. Type of Agent Role
    • 6.2.4. Type of Product
  • 6.3. Future Perspective

7. REGULATORY SCENARIO

SECTION III: MARKET OVERVIEW

8. COMPREHENSIVE DATABASE OF LEADING PLAYERS

9. COMPETITIVE LANDSCAPE

  • 9.1. Chapter Overview
  • 9.2. AI Agents: Overall Market Landscape
    • 9.2.1. Analysis by Year of Establishment
    • 9.2.2. Analysis by Company Size
    • 9.2.3. Analysis by Location of Headquarters
    • 9.2.4. Analysis by Ownership Structure

10. WHITE SPACE ANALYSIS

11. COMPETITIVE COMPETITIVENESS ANALYSIS

12. STARTUP ECOSYSTEM IN THE AI AGENTS MARKET

  • 12.1. AI Agents Market: Market Landscape of Startups
    • 12.1.1. Analysis by Year of Establishment
    • 12.1.2. Analysis by Company Size
    • 12.1.3. Analysis by Company Size and Year of Establishment
    • 12.1.4. Analysis by Location of Headquarters
    • 12.1.5. Analysis by Company Size and Location of Headquarters
    • 12.1.6. Analysis by Ownership Structure
  • 12.2. Key Findings

SECTION IV: COMPANY PROFILES

13. COMPANY PROFILES

  • 13.1. Chapter Overview
  • 13.2. Alibaba Group*
    • 13.2.1. Company Overview
    • 13.2.2. Company Mission
    • 13.2.3. Company Footprint
    • 13.2.4. Management Team
    • 13.2.5. Contact Details
    • 13.2.6. Financial Performance
    • 13.2.7. Operating Business Segments
    • 13.2.8. Service / Product Portfolio (project specific)
    • 13.2.9. MOAT Analysis
    • 13.2.10. Recent Developments and Future Outlook
  • 13.3. Amazon Web Services
  • 13.4. Apple
  • 13.5. Avaamo
  • 13.6. Baidu
  • 13.7. Google
  • 13.8. Hewlett Packard
  • 13.9. IBM
  • 13.10. IPsoft
  • 13.11. Meta
  • 13.12. Microsoft
  • 13.13. NVIDIA
  • 13.14. Nuance Communications
  • 13.15. Oracle
  • 13.16. Salesforce
  • 13.17. SAP SE
  • 13.18. SoundHound

SECTION V: MARKET TRENDS

14. MEGA TRENDS ANALYSIS

15. UNMEET NEED ANALYSIS

16. PATENT ANALYSIS

17. RECENT DEVELOPMENTS

  • 17.1. Chapter Overview
  • 17.2. Recent Funding
  • 17.3. Recent Partnerships
  • 17.4. Other Recent Initiatives

SECTION VI: MARKET OPPORTUNITY ANALYSIS

18. GLOBAL AI AGENTS MARKET

  • 18.1. Chapter Overview
  • 18.2. Key Assumptions and Methodology
  • 18.3. Trends Disruption Impacting Market
  • 18.4. Demand Side Trends
  • 18.5. Supply Side Trends
  • 18.6. Global AI Agents Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.7. Multivariate Scenario Analysis
    • 18.7.1. Conservative Scenario
    • 18.7.2. Optimistic Scenario
  • 18.8. Investment Feasibility Index
  • 18.9. Key Market Segmentations

19. MARKET OPPORTUNITIES BASED ON TYPE OF AGENT SYSTEM

  • 19.1. Chapter Overview
  • 19.2. Key Assumptions and Methodology
  • 19.3. Revenue Shift Analysis
  • 19.4. Market Movement Analysis
  • 19.5. Penetration-Growth (P-G) Matrix
  • 19.6. AI Agents Market for Multi-agent: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.7. AI Agents Market for Single agent: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.8. Data Triangulation and Validation
    • 19.8.1. Secondary Sources
    • 19.8.2. Primary Sources
    • 19.8.3. Statistical Modeling

20. MARKET OPPORTUNITIES BASED ON AREAS OF APPLICATION

  • 20.1. Chapter Overview
  • 20.2. Key Assumptions and Methodology
  • 20.3. Revenue Shift Analysis
  • 20.4. Market Movement Analysis
  • 20.5. Penetration-Growth (P-G) Matrix
  • 20.6. AI Agents Market for Customer Service & Virtual Assistants: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.7. AI Agents Market for Healthcare: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.8. Data Triangulation and Validation
    • 20.8.1. Secondary Sources
    • 20.8.2. Primary Sources
    • 20.8.3. Statistical Modeling

21. MARKET OPPORTUNITIES BASED ON TYPES OF AGENT ROLE

  • 21.1. Chapter Overview
  • 21.2. Key Assumptions and Methodology
  • 21.3. Revenue Shift Analysis
  • 21.4. Market Movement Analysis
  • 21.5. Penetration-Growth (P-G) Matrix
  • 21.6. AI Agents Market for Code Generation: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.7. AI Agents Market for Customer Service: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.8. AI Agents Market for Marketing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.9. AI Agents Market for Productivity & Personal Assistants: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.10. AI Agents Market for Sales: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.11. Data Triangulation and Validation
    • 21.11.1. Secondary Sources
    • 21.11.2. Primary Sources
    • 21.11.3. Statistical Modeling

22. MARKET OPPORTUNITIES BASED ON TYPE OF TECHNOLOGY

  • 22.1. Chapter Overview
  • 22.2. Key Assumptions and Methodology
  • 22.3. Revenue Shift Analysis
  • 22.4. Market Movement Analysis
  • 22.5. Penetration-Growth (P-G) Matrix
  • 22.6. AI Agents Market for Deep Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.7. AI Agents Market for Machine Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.8. Data Triangulation and Validation
    • 22.8.1. Secondary Sources
    • 22.8.2. Primary Sources
    • 22.8.3. Statistical Modeling

23. MARKET OPPORTUNITIES BASED ON TYPE OF PRODUCT

  • 23.1. Chapter Overview
  • 23.2. Key Assumptions and Methodology
  • 23.3. Revenue Shift Analysis
  • 23.4. Market Movement Analysis
  • 23.5. Penetration-Growth (P-G) Matrix
  • 23.6. AI Agents Market for Build Your Own Agents: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.7. AI Agents Market for Ready to Deploy Agents: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.8. Data Triangulation and Validation
    • 23.8.1. Secondary Sources
    • 23.8.2. Primary Sources
    • 23.8.3. Statistical Modeling

24. MARKET OPPORTUNITIES FOR AI AGENTS IN NORTH AMERICA

  • 24.1. Chapter Overview
  • 24.2. Key Assumptions and Methodology
  • 24.3. Revenue Shift Analysis
  • 24.4. Market Movement Analysis
  • 24.5. Penetration-Growth (P-G) Matrix
  • 24.6. AI Agents Market in North America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.1. AI Agents Market in the US: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.2. AI Agents Market in Canada: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.3. AI Agents Market in Mexico: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.4. AI Agents Market in Other North American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 24.7. Data Triangulation and Validation

25. MARKET OPPORTUNITIES FOR AI AGENTS IN EUROPE

  • 25.1. Chapter Overview
  • 25.2. Key Assumptions and Methodology
  • 25.3. Revenue Shift Analysis
  • 25.4. Market Movement Analysis
  • 25.5. Penetration-Growth (P-G) Matrix
  • 25.6. AI Agents Market in Europe: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.1. AI Agents Market in Austria: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.2. AI Agents Market in Belgium: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.3. AI Agents Market in Denmark: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.4. AI Agents Market in France: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.5. AI Agents Market in Germany: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.6. AI Agents Market in Ireland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.7. AI Agents Market in Italy: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.8. AI Agents Market in Netherlands: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.9. AI Agents Market in Norway: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.10. AI Agents Market in Russia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.11. AI Agents Market in Spain: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.12. AI Agents Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.13. AI Agents Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.14. AI Agents Market in Switzerland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.15. AI Agents Market in the UK: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.16. AI Agents Market in Other European Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 25.7. Data Triangulation and Validation

26. MARKET OPPORTUNITIES FOR AI AGENTS IN ASIA

  • 26.1. Chapter Overview
  • 26.2. Key Assumptions and Methodology
  • 26.3. Revenue Shift Analysis
  • 26.4. Market Movement Analysis
  • 26.5. Penetration-Growth (P-G) Matrix
  • 26.6. AI Agents Market in Asia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.1. AI Agents Market in China: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.2. AI Agents Market in India: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.3. AI Agents Market in Japan: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.4. AI Agents Market in Singapore: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.5. AI Agents Market in South Korea: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.6. AI Agents Market in Other Asian Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 26.7. Data Triangulation and Validation

27. MARKET OPPORTUNITIES FOR AI AGENTS IN MIDDLE EAST AND NORTH AFRICA (MENA)

  • 27.1. Chapter Overview
  • 27.2. Key Assumptions and Methodology
  • 27.3. Revenue Shift Analysis
  • 27.4. Market Movement Analysis
  • 27.5. Penetration-Growth (P-G) Matrix
  • 27.6. AI Agents Market in Middle East and North Africa (MENA): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.1. AI Agents Market in Egypt: Historical Trends (Since 2019) and Forecasted Estimates (Till 205)
    • 27.6.2. AI Agents Market in Iran: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.3. AI Agents Market in Iraq: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.4. AI Agents Market in Israel: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.5. AI Agents Market in Kuwait: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.6. AI Agents Market in Saudi Arabia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.7. AI Agents Market in United Arab Emirates (UAE): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.8. AI Agents Market in Other MENA Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 27.7. Data Triangulation and Validation

28. MARKET OPPORTUNITIES FOR AI AGENTS IN LATIN AMERICA

  • 28.1. Chapter Overview
  • 28.2. Key Assumptions and Methodology
  • 28.3. Revenue Shift Analysis
  • 28.4. Market Movement Analysis
  • 28.5. Penetration-Growth (P-G) Matrix
  • 28.6. AI Agents Market in Latin America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.1. AI Agents Market in Argentina: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.2. AI Agents Market in Brazil: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.3. AI Agents Market in Chile: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.4. AI Agents Market in Colombia Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.5. AI Agents Market in Venezuela: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.6. AI Agents Market in Other Latin American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 28.7. Data Triangulation and Validation

29. MARKET OPPORTUNITIES FOR AI AGENTS IN REST OF THE WORLD

  • 29.1. Chapter Overview
  • 29.2. Key Assumptions and Methodology
  • 29.3. Revenue Shift Analysis
  • 29.4. Market Movement Analysis
  • 29.5. Penetration-Growth (P-G) Matrix
  • 29.6. AI Agents Market in Rest of the World: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.1. AI Agents Market in Australia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.2. AI Agents Market in New Zealand: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.3. AI Agents Market in Other Countries
  • 29.7. Data Triangulation and Validation

30. MARKET CONCENTRATION ANALYSIS: DISTRIBUTION BY LEADING PLAYERS

  • 30.1. Leading Player 1
  • 30.2. Leading Player 2
  • 30.3. Leading Player 3
  • 30.4. Leading Player 4
  • 30.5. Leading Player 5
  • 30.6. Leading Player 6
  • 30.7. Leading Player 7
  • 30.8. Leading Player 8

31. ADJACENT MARKET ANALYSIS

SECTION VII: STRATEGIC TOOLS

32. KEY WINNING STRATEGIES

33. PORTER FIVE FORCES ANALYSIS

34. SWOT ANALYSIS

35. VALUE CHAIN ANALYSIS

36. ROOTS STRATEGIC RECOMMENDATIONS

  • 36.1. Chapter Overview
  • 36.2. Key Business-related Strategies
    • 36.2.1. Research & Development
    • 36.2.2. Product Manufacturing
    • 36.2.3. Commercialization / Go-to-Market
    • 36.2.4. Sales and Marketing
  • 36.3. Key Operations-related Strategies
    • 36.3.1. Risk Management
    • 36.3.2. Workforce
    • 36.3.3. Finance
    • 36.3.4. Others

SECTION VIII: OTHER EXCLUSIVE INSIGHTS

37. INSIGHTS FROM PRIMARY RESEARCH

38. REPORT CONCLUSION

SECTION IX: APPENDIX

39. TABULATED DATA

40. LIST OF COMPANIES AND ORGANIZATIONS

41. CUSTOMIZATION OPPORTUNITIES

42. ROOTS SUBSCRIPTION SERVICES

43. AUTHOR DETAILS