세계의 AI 에이전트 시장(-2035년) : 에이전트 시스템 유형, 응용 분야, 에이전트의 역할 유형, 기술 유형, 제품 유형, 기업 규모, 주요 지역별 산업 동향과 예측

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

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한글목차

세계 AI 에이전트 시장 규모는 현재 52억 9,000만 달러에서 예측 기간 동안 CAGR 40.15%로 2035년까지 2,168억 달러로 성장할 것으로 예측됩니다.

세계 AI 에이전트 시장은 업무 효율성 향상을 위한 자동화 도입과 개인화된 고객 경험에 대한 수요 증가로 인해 예측 기간 동안 건강한 속도로 성장할 것으로 예측됩니다.

AI 에이전트 시장 기회: 부문별

에이전트 시스템 유형별

• 멀티 에이전트
• 싱글 에이전트

응용 분야별

• 고객 서비스 및 가상 비서
• 헬스케어

에이전트 역할별

• 코드 생성
• 고객 서비스
• 마케팅
• 생산성 향상 & 개인 비서
• 세일즈

기술 유형별

• 딥러닝
• 머신러닝

제품 유형별

• 자체 제작 에이전트
• 즉시 배포 에이전트

기업 규모별

• 자체 제작 에이전트
• 즉시 배포 에이전트

지역별

• 북미
• 미국
• 캐나다
• 멕시코
• 기타 북미 국가
• 유럽
• 오스트리아
• 벨기에
• 덴마크
• 프랑스
• 독일
• 아일랜드
• 이탈리아
• 네덜란드
• 노르웨이
• 러시아
• 스페인
• 스웨덴
• 스위스
• 영국
• 기타 유럽 국가
• 아시아
• 중국
• 인도
• 일본
• 싱가포르
• 한국
• 기타 아시아 국가
• 라틴아메리카
• 브라질
• 칠레
• 콜롬비아
• 베네수엘라
• 기타 라틴아메리카 국가
• 중동 및 북아프리카
• 이집트
• 이란
• 이라크
• 이스라엘
• 쿠웨이트
• 사우디아라비아
• 아랍에미리트(UAE)
• 기타 중동 및 북아프리카 국가
• 세계 기타 지역
• 호주
• 뉴질랜드
• 기타 국가

AI 에이전트 시장 : 성장과 동향

특히 자연어 처리(NLP) 용도의 눈부신 발전으로 AI 에이전트는 인간의 언어를 이해하고 생성할 수 있는 능력이 향상되어 사용자와 고도의 상호작용이 가능해졌습니다. 이에 따라 AI 기반 자동화를 도입하여 업무 효율성을 높이려는 기업이 증가하고 있으며, AI 에이전트는 고객 서비스, 의료, 금융 등 다양한 분야에서 필수적인 도구로 자리 잡고 있습니다.

또한, AI 에이전트 시장의 성장은 고도로 개인화된 경험에 대한 수요 증가와 AI 에이전트를 업무 프로세스에 통합하는 추세에 따라 더욱 가속화되고 있습니다. 기업들은 업무 최적화, 비용 절감, 개인화된 고객 응대를 통한 고객 참여도 향상을 위해 AI 에이전트를 도입하고 있습니다.

또한, 특정 산업을 위해 설계된 전문 가상 비서의 등장도 시장 성장의 기회를 제공합니다. 이러한 에이전트는 법률, 의료 등 각 분야의 필요에 따라 전문적으로 대응할 수 있습니다.

세계의 AI 에이전트(AI Agent) 시장을 조사했으며, 시장 개요와 배경, 시장 영향요인 분석, 시장 규모 추이 및 예측, 각종 부문별/지역별 상세 분석, 경쟁 구도, 주요 기업 개요 등의 정보를 정리하여 전해드립니다.

목차

섹션 I : 보고서 개요

제1장 서문

제2장 조사 방법

제3장 시장 역학

제4장 거시경제 지표

섹션 II : 정성적 통찰

제5장 주요 요약

제6장 서론

제7장 규제 시나리오

섹션 III : 시장 개요

제8장 주요 기업 종합적 데이터베이스

제9장 경쟁 구도

제10장 화이트 스페이스 분석

제11장 경쟁 분석

제12장 AI 에이전트 시장 스타트업 에코시스템

섹션 IV : 기업 개요

제13장 기업 개요

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

제5장 시장 동향

제14장 메가트렌드 분석

제15장 미충족 요구 분석

제16장 특허 분석

제17장 최근 동향

제6장 시장 기회 분석

제18장 세계의 AI 에이전트 시장

제19장 에이전트 시스템 유형별 시장 기회

제20장 응용 분야별 시장 기회

제21장 에이전트의 역할 유형별 시장 기회

제22장 기술별 시장 기회

제23장 제품 유형별 시장 기회

제24장 북미의 AI 에이전트 시장 기회

제25장 유럽의 AI 에이전트 시장 기회

제26장 아시아의 AI 에이전트 시장 기회

제27장 중동 및 북아프리카의 AI 에이전트 시장 기회

제28장 라틴아메리카의 AI 에이전트 시장 기회

제29장 세계 기타 지역의 AI 에이전트 시장 기회

제30장 시장 집중 분석 : 주요 기업별 분포

제31장 인접 시장 분석

제7장 전략 툴

제32장 주요 성공 전략

제33장 Porter의 Five Forces 분석

제34장 SWOT 분석

제35장 밸류체인 분석

제36장 ROOTS 전략적 제안

섹션 VIII : 기타 독점적 통찰

제37장 1차 조사로부터 통찰

제38장 결론

섹션 IX : 부록

제39장 표 형식 데이터

제40장 기업 및 단체 리스트

제41장 커스터마이즈 기회

제42장 ROOTS 구독 서비스

제43장 저자 상세

LSH

영문 목차

영문목차

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.

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

• Complimentary Excel Data Packs for all Analytical Modules in the Report
• 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

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