The significant rise of artificial intelligence (AI) within finance operations across organizations showcases substantial levels of return on investment (ROI) and numerous operational benefits. According to recent research conducted by KPMG International, the widespread deployment of AI technologies, including machine learning, deep learning, and generative AI, is transforming finance functions. These advancements are enhancing data quality, decision-making, speed of insights and reporting, cost management, and overall operational effectiveness.
The Current State of AI Adoption in Finance
AI Adoption Maturity Levels
KPMG’s global AI in finance report, which surveyed 2,900 organizations across 23 countries, categorizes AI adoption into three maturity groups: Leaders, Implementers, and Beginners. Leaders, representing 24% of respondents, exhibit the highest degree of AI adoption and capability. Implementers constitute 58%, while Beginners make up the remaining 18%. The study also reveals that 71% of organizations now use AI in some capacity within their financial operations, with 41% using AI to a moderate or large extent. This statistic is expected to increase to 83% over the next three years, illustrating a significant upward trend for AI integration in finance.
Generative AI in Financial Reporting
AI technologies, particularly generative AI, are becoming prioritized within financial reporting. The research shows a significant decline in the percentage of companies not intending to use generative AI, dropping from 6% to 1%. The projection is that 95% of organizational leaders and 39% of other respondents plan to adopt generative AI selectively or widely within the next three years. This shift indicates a growing confidence in AI’s ability to streamline and enhance reporting processes, ultimately leading to more efficient and accurate financial operations.
Global Variances in AI Utilization
Leading and Lagging Countries
Globally, the utilization of AI in finance reflects notable variances among countries. The United States, Germany, and Japan are ahead in AI usage, whereas countries like Italy and Spain lag. A similar trend is observed in emerging markets, with China and India leading, and Saudi Arabia and various African countries being behind. These differences can be attributed to varying levels of technological infrastructure, economic development, and commitment from leadership. Nonetheless, the global trend suggests an increasing adoption of AI, with advanced economies paving the way for others to follow.
The Role of CFOs and Finance Functions
Adam Scriven, Head of Finance Transformation at KPMG China, emphasizes the necessity for Chief Financial Officers (CFOs) and finance functions to build AI capabilities as essential in the digital era. According to Scriven, AI should be viewed as an enabling capability rather than merely a technological product. KPMG is actively assisting clients in setting up the right data and systems frameworks to maximize AI’s power. Through collaborative efforts, KPMG co-creates AI solutions with clients, enhancing their journey and capability in AI adoption. This approach ensures that AI integration is not only effective but also aligned with the strategic goals of each organization.
AI’s Impact on Financial Reporting and Planning
Revolutionizing Financial Reporting
Alan Yau of KPMG China indicates how AI is revolutionizing financial reporting, bringing higher accuracy, efficiency, and real-time insights. AI, as a mega-trend, provides predictive analytics and data-driven decisions. This necessitates organizations to continuously upskill their workforce to foster innovation and maintain a competitive market edge. The transformation in financial reporting is evident as more companies adopt AI tools that enhance the ability to analyze vast amounts of data swiftly, thereby offering better insights and facilitating more informed decision-making processes.
Applications in Financial Reporting and Planning
AI is being applied across various finance areas, with financial reporting being the most prevalent use case. Nearly two-thirds of organizations are employing AI for financial reporting, accounting, and financial planning. Treasury and risk management see AI use by nearly half of the organizations surveyed, aiding in better debt management, cash-flow forecasting, fraud detection, credit risk assessment, and scenario analysis. However, tax management lags behind, with less than one-third of organizations currently piloting or using AI, though about half are planning implementations. This disparity highlights the uneven adoption of AI across different areas of finance, suggesting room for broader AI applications in the sector.
Leaders vs. Other Organizations in AI Adoption
Progress and Use Cases
Leaders in AI adoption exhibit pronounced progress; 87% of them use AI in finance compared to just 27% of other organizations. Leaders typically develop six AI use cases, almost double that of other adopters. Main AI applications among these leaders include research and data analysis (85%), fraud detection and prevention (81%), predictive analysis and planning (78%), and using generative AI for composing documents and other content (75%). These leaders demonstrate significant advancements in leveraging AI to optimize their financial operations, setting a benchmark for other organizations striving to catch up.
Overcoming Barriers to AI Adoption
Despite common barriers to AI adoption like data security vulnerabilities (57%), limited AI skills and knowledge (53%), and consistent data gathering (48%), leaders are better equipped to navigate these challenges. They face more advanced barriers such as integrating AI solutions with existing tools and overcoming employee resistance to new technologies. These advanced challenges indicate that AI leaders have moved beyond initial obstacles and are now focusing on more complex aspects of AI integration. Their experience in overcoming these barriers serves as a valuable reference for organizations at earlier stages of AI adoption.
ROI and Operational Benefits of AI in Finance
Benefits and ROI for Initial Users vs. Mature Leaders
The advantages and ROI of AI in finance grow as adoption intensifies. Initial AI users report two to three benefits, while mature leaders report up to seven. Remarkably, 57% of AI leaders state their ROI is not just meeting but exceeding expectations, compared to nearly one-third (29%) of less advanced users reporting the same results. These benefits and significantly higher ROI illustrate the value of investing in AI capabilities, with mature leaders enjoying more extensive operational advantages and financial returns.
The Importance of Robust AI Governance
The notable surge of artificial intelligence (AI) in finance operations within organizations is showing significant returns on investment (ROI) and offering a plethora of operational benefits. A recent study by KPMG International highlights how widespread implementation of AI technologies, like machine learning, deep learning, and generative AI, is revolutionizing finance functions. These technological advancements are improving data quality, refining decision-making, accelerating insights and reporting, and enhancing cost management. Overall, they are boosting operational effectiveness across the finance industry.
AI is not only automating routine tasks but also enabling more accurate forecasting and risk management. This shift allows finance professionals to focus on strategic activities rather than mundane, manual processes. Furthermore, AI-driven predictive analytics is providing deeper insights, enabling better forecasting and more informed decisions. As organizations continue to integrate AI into their finance operations, they are witnessing improved accuracy and efficiency, ultimately leading to better financial performance and competitive advantage.