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市场调查报告书
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1737130

全球会计人工智慧市场规模（按组件、部署类型、组织规模、应用、区域范围和预测）

Global Artificial Intelligence for Accounting Market Size By Component, By Deployment Mode, By Organization Size, By Application, By Geographic Scope And Forecast
出版日期: | 出版商: Verified Market Research | 英文 202 Pages | 商品交期: 2-3个工作天内

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简介目录

会计人工智慧市场规模及预测

2024 年会计人工智慧市场规模为 30.1506 亿美元，预计到 2032 年将达到 451.0762 亿美元，2026 年至 2032 年的复合年增长率为 46.98%。

人工智慧 (AI) 会计应用已被公认为一项颠覆性技术，它能够提供自动化、增强功能和数据主导的洞察，从而革新传统的会计实践。在财务管理领域，人工智慧透过自动化重复性任务、改善决策流程和实现预测分析，推动模式转移。先进的演算法和机器学习方法使会计专业人员能够从海量资料集中获取相关洞察，发现规律，并以无与伦比的准确性和效率识别错误。

人工智慧还能帮助自动化典型的会计业务，例如发票处理、费用分类和余额管理。机器人流程自动化 (RPA) 与人工智慧演算法相结合，可以自动化重复的基于规则的流程，负责人核算专注于财务分析、策略规划和客户咨询服务等更高价值的活动。透过自动化繁琐的流程，人工智慧会计解决方案可以提高生产力、节省营运成本、减少错误，并提升效率和准确性。

未来，人工智慧在会计领域的应用将带来巨大的潜力，它将彻底改变财务流程，提高效率，并为企业提供新的洞见。会计专业人士可透过运用人工智慧自动化、预测分析、诈欺侦测、数据分析和虚拟助理等技术，提升决策能力、业务效率和客户价值。随着人工智慧技术的进步和成熟，预计它将在改变会计和财务的未来方面发挥更大的作用。

会计人工智慧的市场动态

影响全球会计人工智慧市场的关键市场动态：

主要市场驱动因素：

人工智慧的未来应用：会计领域拥有巨大的潜力，可以彻底改变财务流程，提高效率，并为企业提供新的洞察。会计专业人士可透过采用人工智慧自动化、预测分析、诈骗侦测、数据分析和虚拟助理等技术，提升决策能力、业务效率和客户价值。随着人工智慧技术的进步和成熟，预计它们将在改变会计和金融的未来方面发挥更大的作用。

监管合规：这包括 GAAP、IFRS 和税收法规，这些法规要求公司提供准确、及时的财务揭露。人工智慧技术透过自动化合规性检查、确保数据准确性以及识别可能导致违规处罚的潜在错误或差异，在促进监管合规方面发挥关键作用。

日益复杂的财务数据：由于数据的指数级增长和复杂性，传统的会计流程面临巨大的挑战。随着企业在全球扩张，进行复杂的交易，并使其财务数据多样化，以获得有用的见解并保持合规性。人工智慧驱动的分析解决方案提供了处理各种资料来源、格式和结构所需的可扩充性、灵活性和专注度，使会计专业人员能够发现可能影响财务绩效和风险管理的隐藏模式、趋势和违规行为。

主要挑战

数据品质和可访问性：在会计领域运用人工智慧的主要障碍之一是确保数据品质和可访问性。人工智慧系统严重依赖资料输入进行训练、学习和预测。然而，会计资料通常以多种格式、来源和完整性层级存在，这引发了人们对资料完整性和可靠性的担忧。使用资料撷取和自动资料资料提取等被动资料收集方法可能难以取得和处理非结构化或不完整的资料集。此外，维护资料隐私和法规遵循增加了新的复杂性，需要强大的资讯管理结构和安全措施。

道德与监管合规：将人工智慧应用于会计的另一个重大障碍是道德考量，尤其是隐私、偏见和监管合规。被动资料收集策略可能会无意中传播过去资料集中发现的缺陷，从而导致人工智慧决策流程中出现不公平或歧视性的结果。此外，敏感财务资料的使用引发了人们对资料隐私和安全的担忧，并需要遵守《一般资料保护规范》（GDPR）、《加州消费者隐私法案》（CCPA）和《萨班斯-奥克斯利法案》等严格的法律规范。

人机协作与技能差距：人类专家与人工智慧系统之间的有效协作对于成功将人工智慧融入会计至关重要。然而，这需要克服技能差距、变革管理和员工准备等问题。人员流失、失控以及对人工智慧工具和技术的不熟悉等问题都可能导致企业积极抵制采用人工智慧主导的技术。解决这些问题需要积极主动地提升会计专业人员的技能，培养持续学习和适应的文化，并为人工智慧的整合创造协作的思维模式。

主要趋势

自动化日常任务：会计自动化旨在透过简化常见流程来提高业务效率。人工智慧软体解决方案正在改变资料输入、交易分类、对帐和财务报告等业务。这些系统使用机器学习演算法和自然语言处理 (NLP) 来评估大量财务数据，提取所需信息，并以极快的速度和准确性执行重复性任务。

进阶数据分析：会计领域的人工智慧正在革新数据分析，使企业能够从财务数据中获得关键洞察。人工智慧分析解决方案利用演算法发现大量资料集中的模式、趋势和差异，从而更好地洞察财务绩效、风险因素和业务动态。这些技术可以执行进阶分析，例如预测建模、识别异常、分析情绪和预测趋势，使会计师和财务专业人士能够做出更自信、更准确的数据主导决策。

加强网路安全措施：随着财务数据和交易数位化，会计师事务所和组织必须优先考虑网路安全。人工智慧透过主动识别和减少潜在的网路攻击和漏洞，在提升网路安全方面发挥关键作用。基于人工智慧的网路安全解决方案使用机器学习演算法来分析网路流量、检测可疑活动并即时回应安全漏洞。这些技术可以侦测出网路攻击的模式，预测即将发生的风险，并自动更新防御措施以应对不断发展的网路威胁。

目录

第一章 全球会计人工智慧市场介绍

  • 市场概览
  • 研究范围
  • 先决条件

第二章执行摘要

  • 资料探勘
  • 二次调查
  • 初步调查
  • 专家建议
  • 品质检查
  • 最终审核
  • 数据三角测量
  • 自下而上的方法
  • 自上而下的方法
  • 调查流程
  • 资料来源

第三章：已验证的市场研究调查方法

  • 概述
  • 绝对的商机
  • 市场吸引力
  • 未来市场机会

第四章 会计人工智慧的全球市场展望

  • 概述
  • 市场动态
    • 驱动程式
    • 限制因素
    • 机会
  • 波特五力模型
  • 价值链分析

第五章会计人工智慧市场组成部分

  • 解决方案
  • 服务

第六章全球会计人工智慧市场（按应用）

  • 概述
  • 自动记帐
  • 发票分类和核准
  • 诈欺与风险管理
  • 其他的

第七章全球会计人工智慧市场（按部署类型）

  • 概述
  • 在云端
  • 本地

第八章全球会计人工智慧市场（按组织规模）

  • 概述
  • 小型企业
  • 大公司

第九章全球会计人工智慧市场（按地区）

  • 概述
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 义大利
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 其他亚太地区
  • 拉丁美洲
    • 巴西
    • 阿根廷
    • 其他拉丁美洲
  • 中东和非洲
    • 阿拉伯聯合大公国
    • 沙乌地阿拉伯
    • 南非
    • 其他中东和非洲地区

第十章全球会计人工智慧市场竞争格局

  • 概述
  • 各公司市场排名
  • 主要发展策略
  • 公司地理分布
  • 公司产业足迹
  • ACE矩阵

第十一章 公司简介

  • Xero Limited
  • Intuit Inc.
  • Sage Group
  • SAP SE
  • Epicor Software Corporation
  • OSP
  • UiPath
  • Kore.AI
  • Appzen
  • Yaypay

第十二章 重大进展

  • 产品发布/开发
  • 合併与收购
  • 业务扩展
  • 伙伴关係与合作

第十三章 附录

  • 相关调查
简介目录
Product Code: 52149

Artificial Intelligence For Accounting Market Size And Forecast

Artificial Intelligence for Accounting Market size was valued at USD 3015.06 Million in 2024 and is projected to reach USD 45107.62 Million by 2032, growing at a CAGR of 46.98% from 2026 to 2032.

Artificial intelligence (AI) for accounting has become known as a game-changing technology, automating, enhancing, and providing data-driven insights to alter traditional accounting methods. In the field of financial management, AI promotes a paradigm shift by automating repetitive jobs, improving decision-making processes, and enabling predictive analytics. Advanced algorithms and machine learning approaches enable accounting professionals to extract relevant insights from enormous data sets, discover patterns, and identify errors with unmatched precision and efficiency.

AI also helps to automate typical accounting operations including invoice processing, expense classification, and balance. Robotic process automation (RPA) paired with AI algorithms automates repetitive rule-based processes allowing accountants to focus on higher-value activities like financial analysis, strategic planning, and client advisory services. By automating boring procedures, AI-powered accounting solutions boost productivity, save operating expenses, and reduce errors, resulting in increased efficiency and accuracy.

The future use of artificial intelligence in accounting has tremendous potential for revolutionizing financial processes, increasing efficiency, and providing new insights to firms. Accounting professionals can increase their decision-making abilities, operational efficiency, and client value by embracing AI-powered automation, predictive analytics, fraud detection, data analytics, and virtual assistants. As AI technologies advance and mature, they are projected to play a larger role in changing the future of accounting and finance.

Artificial Intelligence For Accounting Market Dynamics

The key market dynamics that are shaping the global artificial intelligence for accounting market include:

Key Market Drivers:

The Future Use of Artificial Intelligence: The accounting has tremendous potential for revolutionizing financial processes, increasing efficiency, and providing new insights to firms. Accounting professionals can increase their decision-making abilities, operational efficiency, and client value by embracing AI-powered automation, predictive analytics, fraud detection, data analytics, and virtual assistants. As AI technologies advance and mature they are projected to play a larger role in changing the future of accounting and finance.

Regulatory Compliance: It includes GAAP, IFRS, and tax regulations, requiring businesses to provide accurate and timely financial disclosures. AI technologies play an important role in facilitating regulatory compliance by automating compliance checks, assuring data accuracy, and identifying potential errors or differences that could result in noncompliance penalties.

Increasing Financial Data Complexity: Traditional accounting processes face substantial problems due to exponential growth in data volume and complexity. As firms expand globally diversify operations, conduct complicated transactions, and diversify financial data to extract useful insights and maintain regulatory compliance. AI-powered analytics solutions provide the scalability, flexibility, and alertness required to handle a wide range of data sources, formats, and structures, allowing accounting professionals to find hidden patterns, trends, and irregularities that may impact financial performance or risk management.

Key Challenges:

Data Quality and Accessibility: One of the key obstacles in using AI for accounting is guaranteeing data quality and accessibility. AI systems rely largely on data inputs to train, learn, and predict. However, accounting data frequently exists in diverse formats, sources, and levels of completeness raising concerns about data integrity and trustworthiness. Unstructured or incomplete data sets can be challenging to obtain and handle using passive data collecting methods such as data scraping and automated data extraction. In addition, maintaining data privacy and regulatory compliance adds a new layer of complexity needing strong information management structures and security measures.

Ethical and Regulatory Compliance: Another key obstacle to the application of AI in accounting is ethical considerations specifically privacy, bias, and regulatory compliance. Passive data-gathering strategies may unintentionally propagate flaws found in past data sets resulting in unfair or discriminatory outcomes in AI-powered decision-making processes. In addition, the usage of sensitive financial data creates concerns about data privacy, and security requiring compliance with stringent regulatory frameworks such as GDPR, CCPA, and the Sarbanes-Oxley Act.

Human-AI Collaboration and Skills Gap: The successful incorporation of AI into accounting procedures is dependent on effective collaboration between human experts and AI systems. However, this entails overcoming problems like as skill gaps, change management, and worker preparation. Concerns about job displacement, loss of control, or unfamiliarity with AI tools and methodology can all contribute to inactive resistance to embracing AI-driven technology. Addressing these problems demands proactive actions to upskill accounting experts develop a culture of constant learning and adaptability, and create a collaborative mindset for AI integration.

Key Trends:

Automation of Routine Tasks: Accounting automation aims to improve operational efficiency by streamlining common procedures. Artificial intelligence-powered software solutions are transforming operations including data entry, transaction categorization, conciliation, and financial reporting. These systems use machine learning algorithms and natural language processing (NLP) to evaluate large volumes of financial data, extract essential information, and perform repetitive operations with exceptional speed and accuracy.

Advanced Data Analytics: AI in accounting has revolutionized data analytics allowing firms to gain important insights from financial data. AI-powered analytics solutions use algorithms to find patterns, trends, and differences in enormous data sets providing better insight into financial performance, risk factors, and business dynamics. These technologies may do advanced analyses such as predictive modeling, abnormality identification, analysis of sentiment, and forecasting of trends giving accountants and financial professionals the ability to make more confident and precise data-driven judgments

Enhanced Cybersecurity Measures: As financial data and transactions become more digital, accounting firms and organizations must prioritize cybersecurity. AI is playing an important role in improving cybersecurity by proactively recognizing and reducing potential cyber-attacks and weaknesses. AI-enabled cybersecurity solutions use machine learning algorithms to analyze network traffic, detect suspicious activity, and respond to security breaches in real-time. These technologies can detect patterns indicative of cyber-attacks, predict upcoming risks, and automatically update defenses to combat developing cyber threats.

Global Artificial Intelligence for Accounting Market Regional Analysis

Here is a more detailed regional analysis of the global artificial intelligence for accounting market:

North America:

AI technology integration helps firms perform a variety of services including fraud detection, bankruptcy prediction, and cash flow forecasting. As a result, accountants may assist consumers in proactively responding to financial issues by adjusting their spending before the situation worsens. Furthermore, it broadens the scope of predictive consulting beyond traditional financial planning and allows for the integration of other critical business areas.

In addition, the majority of market vendors are in the United States giving the region a competitive edge in innovation. The US government encourages the adoption of novel technologies such as artificial intelligence, machine learning, and natural language processing which provides several chances for market participants to enhance their market share in the sector. The US Department of Labor classified accountant and auditor employment as among the most newly created and it expects the industry to grow at a 10% annual rate from 2016 to 2026. The preference of accountants for AI increases the market's growth.

North America is a major market for AI and machine learning technologies with the United States playing a key role in driving regional demand. Due to its leadership in AI and machine learning technologies, the country is expected to dominate the global market over the projection period.

Asia Pacific:

In Asia, the market for artificial intelligence in accounting is rapidly expanding. This is due to the growing desire for automation and cost-effectiveness in the accounting industry. Businesses are using AI-based solutions to improve their accounting operations and decrease manual labor costs. The number of startups and venture capital investments in the AI accounting field is also on the rise in Asia.

This is due to the abundance of skilled talent and a big client base. In addition, the region is home to some of the world's most prominent technological businesses which are significantly investing in AI-based solutions. The Asian region is also seeing an increase in the number of AI-based accounting solutions being created.

Global Artificial Intelligence for Accounting Market: Segmentation Analysis

The Global Artificial Intelligence for Accounting Market is segmented based on Component, Deployment Mode, Organization Size, Application, and Geography.

Artificial Intelligence for Accounting Market, By Component

  • Solutions
  • Services

Based on the Components, the market is divided into Solutions and Services. The services segment is projected to hold the largest share of the market throughout the projected period. The advantage can be due to the growing demand for specialized knowledge and support services for adopting, managing, and optimizing AI systems in accounting. As businesses value the importance of specialized advice and continuous assistance, the services segment is likely to develop slowly, enhancing its market position.

Artificial Intelligence for Accounting Market, By Deployment Mode

  • On-Cloud
  • On-Premises

Based on Deployment Mode, the market is divided into On-Cloud and On-Premises. The On-Premises segment holds the largest worldwide market share and is expected to increase significantly during the forecast period. However, the On-Cloud sector is predicted to develop at the fastest CAGR over the forecast period. Cloud-based AI solutions facilitate real-time collaboration and decision-making by providing remote access to accounting data and AI-powered tools from any location with an internet connection.

Artificial Intelligence for Accounting Market, By Organization Size

  • Small and Medium Enterprise
  • Large Enterprise

Based on Organization Size, the market is segmented into Small and Medium Enterprises and Large Enterprises. The large enterprise segment has the largest worldwide market share and is expected to expand at a considerable CAGR over the forecast period. However, the small and medium enterprise segment is predicted to increase at the fastest CAGR over the forecast period.

Artificial Intelligence for Accounting Market, By Application

  • Automated Bookkeeping
  • Invoice Classification and Approvals
  • Fraud and Risk Management
  • Reporting

Based on Application, the market is segmented into Automated Bookkeeping, Invoice Classification and Approvals, Fraud and Risk Management, and Reporting. The automated bookkeeping segment accounted for the biggest market share and is expected to increase at a considerable CAGR. AI-powered automated accounting reduces the likelihood of human error in manual data entry and processing resulting in more accurate financial records.

Artificial Intelligence For Accounting Market, By Geography

  • North America
  • Europe
  • Asia Pacific
  • Rest of the World

Based on Geography, the global Artificial Intelligence for the accounting market is classified into North America, Europe, Asia Pacific, and the Rest of the world. North America accounts for the largest market share in artificial intelligence for the accounting market. AI technology integration helps companies perform a variety of services including fraud detection, bankruptcy prediction, and cash flow forecasting. Therefore, accountants may assist consumers in proactively responding to financial issues by adjusting their spending before the situation worsens. Furthermore, it expands the scope of predicting counseling beyond traditional financial planning and allows for the integration of other critical business areas.

Key Players

  • The Global Artificial Intelligence For Accounting study report will provide valuable insight with an emphasis on the global market. The major players in the market are Xero Limited, Intuit, Inc., Sage Group, SAP SE, Epicor Software Corporation.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

  • Artificial Intelligence for Accounting Market Recent Developments
  • Artificial Intelligence for Accounting Market Recent Developments
  • In April 2023, Intuit, Inc. introduced Email Content Generator (beta), which employed GPT AI technology to allow customers to create marketing email messages based on industry, marketing intent, and brand voice. Mailchimp's latest release of AI-powered capabilities including Email Content Generator, is the next stage in the company's ambition to transform email marketing for small and medium-sized organizations.
  • In April 2023, PwC US invested USD 1 billion over the next three years to improve the work of its tax accountants, auditors, and consultants for clients by leveraging artificial intelligence. This project, which involves collaboration with Microsoft Corp., aims to decrease busywork so that employees may focus on tasks that require expert eyes.

TABLE OF CONTENTS

1 INTRODUCTION OF THE GLOBAL ARTIFICIAL INTELLIGENCE FOR ACCOUNTING MARKET

  • 1.1 Overview of the Market
  • 1.2 Scope of Report
  • 1.3 Assumptions

2 EXECUTIVE SUMMARY

  • 2.1 Data mining
  • 2.2 Secondary research
  • 2.3 Primary research
  • 2.4 Subject matter expert advice
  • 2.5 Quality check
  • 2.6 Final review
  • 2.7 Data triangulation
  • 2.8 Bottom-up approach
  • 2.9 Top-down approach
  • 2.10 Research flow
  • 2.11 Data sources

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

  • 3.1 Overview
  • 3.2 Absolute $ Opportunity
  • 3.3 Market attractiveness
  • 3.4 Future Market Opportunities

4 GLOBAL ARTIFICIAL INTELLIGENCE FOR ACCOUNTING MARKET OUTLOOK

  • 4.1 Overview
  • 4.2 Market Dynamics
    • 4.2.1 Drivers
    • 4.2.2 Restraints
    • 4.2.3 Opportunities
  • 4.3 Porter's Five Force Model
  • 4.4 Value Chain Analysis

5 Artificial Intelligence for Accounting Market, By Component

  • 5.1 Solutions
  • 5.2 Services

6 GLOBAL ARTIFICIAL INTELLIGENCE FOR ACCOUNTING MARKET, BY APPLICATION

  • 6.1 Overview
  • 6.2 Automated Bookkeeping
  • 6.3 Invoice Classification and Approvals
  • 6.4 Fraud and Risk Management
  • 6.5 Others

7 GLOBAL ARTIFICIAL INTELLIGENCE FOR ACCOUNTING MARKET, BY DEPLOYMENT MODE

  • 7.1 Overview
  • 7.2 On-Cloud
  • 7.3 On-Premises

8 GLOBAL ARTIFICIAL INTELLIGENCE FOR ACCOUNTING MARKET, BY ORGANIZATION SIZE

  • 8.1 Overview
  • 8.2 Small and Medium Enterprise
  • 8.3 Large Enterprise

9 GLOBAL ARTIFICIAL INTELLIGENCE FOR ACCOUNTING MARKET, BY GEOGRAPHY

  • 9.1 Overview
  • 9.2 North America
    • 9.2.1 The U.S.
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 The U.K.
    • 9.3.3 France
    • 9.3.4 Italy
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 Japan
    • 9.4.3 India
    • 9.4.4 Rest of Asia Pacific
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Argentina
    • 9.5.3 Rest of LATAM
  • 9.6 Middle East and Africa
    • 9.6.1 UAE
    • 9.6.2 Saudi Arabia
    • 9.6.3 South Africa
    • 9.6.4 Rest of the Middle East and Africa

10 GLOBAL ARTIFICIAL INTELLIGENCE FOR ACCOUNTING MARKET COMPETITIVE LANDSCAPE

  • 10.1 Overview
  • 10.2 Company Market Ranking
  • 10.3 Key Development Strategies
  • 10.4 Company Regional Footprint
  • 10.5 Company Industry Footprint
  • 10.6 ACE Matrix

11 COMPANY PROFILES

  • 11.1 Xero Limited
    • 11.1.1 Company Overview
    • 11.1.2 Company Insights
    • 11.1.3 Business Breakdown
    • 11.1.4 Product Benchmarking
    • 11.1.5 Key Developments
    • 11.1.6 Winning Imperatives
    • 11.1.7 Current Focus & Strategies
    • 11.1.8 Threat from Competition
    • 11.1.9 SWOT Analysis
  • 11.2 Intuit Inc.
    • 11.2.1 Company Overview
    • 11.2.2 Company Insights
    • 11.2.3 Business Breakdown
    • 11.2.4 Product Benchmarking
    • 11.2.5 Key Developments
    • 11.2.6 Winning Imperatives
    • 11.2.7 Current Focus & Strategies
    • 11.2.8 Threat from Competition
    • 11.2.9 SWOT Analysis
  • 11.3 Sage Group
    • 11.3.1 Company Overview
    • 11.3.2 Company Insights
    • 11.3.3 Business Breakdown
    • 11.3.4 Product Benchmarking
    • 11.3.5 Key Developments
    • 11.3.6 Winning Imperatives
    • 11.3.7 Current Focus & Strategies
    • 11.3.8 Threat from Competition
    • 11.3.9 SWOT Analysis
  • 11.4 SAP SE
    • 11.4.1 Company Overview
    • 11.4.2 Company Insights
    • 11.4.3 Business Breakdown
    • 11.4.4 Product Benchmarking
    • 11.4.5 Key Developments
    • 11.4.6 Winning Imperatives
    • 11.4.7 Current Focus & Strategies
    • 11.4.8 Threat from Competition
    • 11.4.9 SWOT Analysis
  • 11.5 Epicor Software Corporation
    • 11.5.1 Company Overview
    • 11.5.2 Company Insights
    • 11.5.3 Business Breakdown
    • 11.5.4 Product Benchmarking
    • 11.5.5 Key Developments
    • 11.5.6 Winning Imperatives
    • 11.5.7 Current Focus & Strategies
    • 11.5.8 Threat from Competition
    • 11.5.9 SWOT Analysis
  • 11.6 OSP
    • 11.6.1 Company Overview
    • 11.6.2 Company Insights
    • 11.6.3 Business Breakdown
    • 11.6.4 Product Benchmarking
    • 11.6.5 Key Developments
    • 11.6.6 Winning Imperatives
    • 11.6.7 Current Focus & Strategies
    • 11.6.8 Threat from Competition
    • 11.6.9 SWOT Analysis
  • 11.7 UiPath
    • 11.7.1 Company Overview
    • 11.7.2 Company Insights
    • 11.7.3 Business Breakdown
    • 11.7.4 Product Benchmarking
    • 11.7.5 Key Developments
    • 11.7.6 Winning Imperatives
    • 11.7.7 Current Focus & Strategies
    • 11.7.8 Threat from Competition
    • 11.7.9 SWOT Analysis
  • 11.8 Kore.AI
    • 11.8.1 Company Overview
    • 11.8.2 Company Insights
    • 11.8.3 Business Breakdown
    • 11.8.4 Product Benchmarking
    • 11.8.5 Key Developments
    • 11.8.6 Winning Imperatives
    • 11.8.7 Current Focus & Strategies
    • 11.8.8 Threat from Competition
    • 11.8.9 SWOT Analysis
  • 11.9 Appzen
    • 11.9.1 Company Overview
    • 11.9.2 Company Insights
    • 11.9.3 Business Breakdown
    • 11.9.4 Product Benchmarking
    • 11.9.5 Key Developments
    • 11.9.6 Winning Imperatives
    • 11.9.7 Current Focus & Strategies
    • 11.9.8 Threat from Competition
    • 11.9.9 SWOT Analysis
  • 11.10 Yaypay
    • 11.10.1 Company Overview
    • 11.10.2 Company Insights
    • 11.10.3 Business Breakdown
    • 11.10.4 Product Benchmarking
    • 11.10.5 Key Developments
    • 11.10.6 Winning Imperatives
    • 11.10.7 Current Focus & Strategies
    • 11.10.8 Threat from Competition
    • 11.10.9 SWOT Analysis

12 KEY DEVELOPMENTS

  • 12.1 Product Launches/Developments
  • 12.2 Mergers and Acquisitions
  • 12.3 Business Expansions
  • 12.4 Partnerships and Collaborations

13 Appendix

  • 13.1 Related Research