Global Generative AI in Accounting Market, By Deployment Model (On-Premises Deployment, Cloud Deployment), By Technology (Machine Learning, Natural Language Processing, and Other ), By Region and Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends, and Forecast 2023-2032

Report Overview

Global Generative AI in Accounting market size is expected to be worth around USD 9,098 million by 2032 from USD 211 million in 2022, growing at a CAGR of 47.1% during the forecast period from 2023 to 2032.

Generative AI has the potential to revolutionize the accounting industry by automating manual processes, improving data analysis and decision-making, & enhancing fraud detection and risk assessment. It encompasses various technologies, such as machine learning and deep learning, which enable the generation of new content, prediction, and analysis based on patterns in accounting data. The predictive capabilities of generative AI help in financial planning and forecasting. By analyzing historical data and market trends, AI models can generate accurate predictions and assist in budgeting, resource allocation, and investment planning.

The market generative AI in accounting is expected to grow as businesses increasingly recognize the benefits of implementing AI technologies to streamline financial operations and improve efficiency. Key factors contributing to market growth include the increasing volume of financial data, the need for real-time insights and accurate forecasting, & the demand for enhanced fraud detection and compliance.

Driving Factors

Automation and Efficiency

Generative AI enables the automation of repetitive and manual accounting tasks such as data entry, document processing, and report generation. This automation improves efficiency, reduces errors, and frees up valuable time for accountants to focus on more strategic and analytical work.

Data Analysis and Insights

with access to vast amounts of financial data, generative AI algorithms can analyze patterns, detect anomalies, and generate insights for financial forecasting, risk assessment, and decision-making. These capabilities empower accountants and finance professionals with accurate and timely information to drive business strategies.

Improved Audit Processes

Generative AI can enhance the audit process by automating data extraction, analyzing financial statements, and identifying discrepancies or potential risks. This streamlines the audits, reduces manual effort, and improves the accuracy and thoroughness of audits.

Restraining Factors

Data Privacy and Security Concerns

Generative AI relies on access to sensitive financial data. Ensuring the privacy and security of this data is crucial. Organizations must address concerns related to data breaches, unauthorized access, and compliance with data protection regulations such as GDPR or HIPAA.

Ethical Considerations

The ethical implications of generative AI in accounting, such as bias in algorithms, responsible data usage, and transparency, must be carefully addressed. Organizations must ensure fairness, accountability, and transparency in AI systems to build trust and mitigate potential ethical concerns.

Limited Availability of Quality Data

Generative AI models require large quantities of high-quality data for effective training and accurate predictions. However, acquiring and organizing such data can be challenging in the accounting domain, particularly for small and medium-sized enterprises (SMEs) with limited data resources.

Lack of Skilled Workforce

Implementing generative AI technologies in accounting requires skilled professionals who understand AI concepts, data analytics, and accounting principles. The shortage of skilled personnel with expertise in both AI and accounting can hinder the effective adoption and utilization of generative AI in the industry.

COVID-19 Impact Analysis

The COVID-19 pandemic has positively and negatively impacted the global generative AI market in accounting.

The pandemic has accelerated the need for automation in accounting processes. As businesses faced remote work arrangements and operational disruptions, there was a greater emphasis on automating tasks such as data entry, document processing, and financial analysis, which generative AI can facilitate. The economic uncertainties and financial challenges caused by the pandemic highlighted the importance of robust risk management.

Generative AI can assist in identifying potential risks, detecting anomalies, and improving fraud detection, helping organizations mitigate financial risks and ensure compliance. The pandemic-induced economic downturn led to budget constraints for many organizations. As a result, some businesses had to scale back or postpone investments in new technologies, including generative AI solutions, due to financial constraints.

By Deployment Model Analysis

The Cloud-based Dominated Deployment Model Segment in Generative AI in Accounting Market.

Based on the deployment model, the cloud-based segment is currently dominating the Generative AI in the accounting market by deployment model. Cloud-based solutions offer the ability to scale resources up or down based on demand, allowing for the efficient processing of large datasets and complex models. Cloud-based deployment involves utilizing computing resources and storage infrastructure provided by a third-party cloud service provider.

On-premises deployment involves installing and running the generative AI system within an organization's own infrastructure. Organizations have complete control over their data as it is stored and processed within their own infrastructure. With on-premises deployment, internet connectivity is not dependent, resulting in potentially lower latency and faster processing times.

By Technology Analysis

The Machine Learning Segment Accounted for the Largest Share of Generative AI In Accounting Market in 2022.

Based on technology, machine learning is currently dominating the Generative AI in the accounting market by technology. Machine learning techniques have found widespread adoption and success in various accounting tasks. ML algorithms, including both traditional and advanced techniques, are widely used in generative AI for accounting. ML algorithms can analyze large volumes of financial data to identify patterns, make predictions, and automate various accounting processes.

NLP is another important technology in generative AI for accounting. It enables computers to understand and process human language, which is crucial for tasks such as automated data extraction from financial documents, sentiment analysis of financial reports, & generation of financial narratives.

By Application Analysis

Generative AI can be employed to automate data entry tasks by extracting information from documents, invoices, receipts, and other sources. It can help reduce manual data entry errors and improve overall efficiency in handling large volumes of financial data. In Financial Forecasting and Analysis include, Generative AI algorithms can analyze historical financial data to generate forecasts, identify patterns, and assist in financial planning. These models can help businesses make informed decisions by predicting future trends, estimating revenue and expenses, and evaluating potential risks and opportunities.

Generative AI can assist in ensuring compliance with accounting regulations and streamlining the audit process. Analyzing financial data can identify anomalies, flag potential risks, and assist auditors in detecting fraudulent activities or errors. Decision Support and Optimization, such as Generative AI models, can provide decision support by analyzing various financial scenarios and suggesting optimal strategies. This application can help in areas such as investment portfolio optimization, cost management, and resource allocation.

By End-User Analysis

Large Enterprises are Dominated in End-Users Segment in Generative AI in Accounting Market.

Large enterprises typically have more extensive financial operations and complex accounting processes, which could make them more inclined to explore and adopt generative AI solutions. They often have the resources and infrastructure to implement and integrate generative AI technologies into their accounting systems. Small and medium enterprises (SMEs) may also find value in utilizing generative AI in accounting.

While they may have less complex accounting processes compared to large enterprises, generative AI can still provide benefits such as automating data entry, improving accuracy, and enhancing financial analysis and decision-making. Accounting firms, including the Big Four and smaller accounting practices, can leverage generative AI to enhance their services and improve efficiency. Generative AI can automate tasks, streamline auditing processes, and provide advanced financial analysis capabilities.

Key Market Segments

Based on Deployment Model

• Cloud Deployment
• On-Premises Deployment

Based on Technology

• Deep Learning Technology
• Natural Language Processing Technology
• Machine Learning Technology
• Other Technologies

Based on Application

• Data Entry and Processing
• Fraud Detection and Risk Assessment
• Financial Forecasting and Analysis
• Compliance and Audit Support
• Decision Support and Optimization
• Other Applications

Based on End-User

• Large Enterprises
• Small and Medium Enterprises
• Accounting Firms
• Other End-Users

Growth Opportunity

Generative AI has the potential to bring significant advancements and opportunities to the field of accounting. Here are some growth opportunities for generative AI in accounting:

Automating Routine Tasks: Generative AI can automate repetitive and mundane tasks in accounting, such as data entry, transaction matching, and report generation. By leveraging AI algorithms, these tasks can be performed faster, more accurately, & with reduced manual effort. This allows accountants to focus on more strategic & value-added activities.

Fraud Detection and Risk Management: Generative AI can enhance accounting fraud detection and risk management. AI algorithms can analyze large volumes of financial data and identify anomalies, patterns, or trends indicating fraudulent activities or potential risks. This helps accountants detect and prevent fraud early and make informed decisions to mitigate risks.

Latest Trends

Natural Language Processing: NLP techniques are being integrated into generative AI systems for accounting. This enables AI Algorithms to understand and process unstructured data, such as financial statements, contracts, and regulatory documents. NLP facilitates the automation of data extraction, contracts, and reporting, improving efficiency and accuracy in accounting processes.

Integrated Accounting Systems: Generative AI is integrated into accounting software and platforms to enhance functionalities. AI algorithms can automate data entry, categorize transactions, and generate financial reports, simplifying the accounting process and reducing manual effort. Integrated systems also facilitate seamless data flow between different accounting functions and applications.

Continuous Auditing and Monitoring: Generative AI enables continuous auditing and monitoring of financial data in real time. AI algorithms can analyze financial transactions, identify anomalies, and provide alerts for potential fraud or compliance issues. This trend enhances the efficiency and effectiveness of audit processes and reduces the reliance on manual sampling and periodic audits.

Regional Analysis

North America Accounted for the Largest Share of Generative AI in Accounting Market in 2022.

North America, particularly the United States, has been a hub for technological advancements in the accounting industry. Many regional accounting firms and organizations have embraced generative AI to automate routine tasks, improve data analysis, and enhance financial reporting accuracy. The presence of major technology companies and research institutions has driven innovation and research in generative AI applications for accounting.

European countries have also shown significant interest in adopting AI in accounting. Countries like the UK, Germany, France, & Netherlands have been actively exploring the use of AI technologies in financial management, auditing, & fraud detection. The European Union's General Data Protection Regulation has influenced the adoption of AI by imposing strict regulations on data privacy and security.

Key Regions

• North America
  • The US
  • Canada
  • Mexico
• Western Europe
  • Germany
  • France
  • The UK
  • Spain
  • Italy
  • Portugal
  • Ireland
  • Austria
  • Switzerland
  • Benelux
  • Nordic
  • Rest of Western Europe
• Eastern Europe
  • Russia
  • Poland
  • The Czech Republic
  • Greece
  • Rest of Eastern Europe
• APAC
  • China
  • Japan
  • South Korea
  • India
  • Australia & New Zealand
  • Indonesia
  • Malaysia
  • Philippines
  • Singapore
  • Thailand
  • Vietnam
  • Rest of APAC
• Latin America
  • Brazil
  • Colombia
  • Chile
  • Argentina
  • Costa Rica
  • Rest of Latin America
• Middle East & Africa
  • Algeria
  • Egypt
  • Israel
  • Kuwait
  • Nigeria
  • Saudi Arabia
  • South Africa
  • Turkey
  • United Arab Emirates
  • Rest of MEA

Market Share & Key Players Analysis

IBM has been a major player in the field of AI, including generative AI. They have developed various AI-powered solutions for accounting and finance, such as Watson, which has been applied to tasks like financial analysis, fraud detection, and risk assessment.

KPMG offers AI and data analytics solutions for accounting and financial management, helping organizations automate processes, improve accuracy, and gain valuable insights from their financial data.

Market Key Players

• IBM Corporation
• KPMG
• BlackLine, Inc
• SAP SE
• Workday, Inc.
• NVIDIA Corporation
• Intuit Inc.
• UiPath Inc.
• Hitachi
• Microsoft
• Deloitte Touche Tohmatsu Limited
• Other Key Players

Recent Development

• In June 2023, the business and technology subsidiary of the American Institute of CPAs (AICPA), announced its plans to deliver a series of initiatives designed to support accounting and finance professionals in building awareness and understanding of generative AI (GenAI) and its potential impact on the accounting profession.
• In 2022, Hitachi announced the development of a generative AI system that can automatically construct financial statements from raw data. The system is intended to save accountants time and enhance their precision.
• In 2023, SAP announced the acquisition of Converge, an accounting and finance-focused generative AI company. The acquisition is anticipated to assist SAP in expanding its generative AI capabilities and providing its clients with new financial data insights.
• In 2023, Microsoft launched AI for Finance, a package of generative AI tools to assist accountants automate activities, enhance accuracy, and obtain insights into their financial data.

 Report Scope