Introduction
Organizations are implementing artificial intelligence (AI) to a significant extent in their finance operations, according to new research from KPMG International. The benefits of AI are extensive and include improved data and decision-making, faster insights and reporting, reduced costs, and increased operational effectiveness. Additionally, the ROI is compelling.
The KPMG report shows that organizations are extracting the most value from machine learning, deep learning, and generative AI, despite investing in a diverse array of AI technologies. The ROI from these technologies is either meeting or exceeding expectations.
Published in the KPMG global AI in finance report, the research covered 2,900 organizations across 23 countries, building on earlier this year’s study of 1,800 organizations in 10 countries. We developed a maturity framework to categorize respondents’ AI preparedness into three groups: KPMG has identified a cohort of Leaders who are more advanced and mature in their deployment of AI. Leaders comprise twenty-four percent of organizations, while fifty-eight percent are middle-ground Implementers and eighteen percent are Beginners. Additionally, KPMG has created an AI maturity benchmarking instrument to assist organizations in evaluating their advancements in the AI transformation process.
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The Impact of Artificial Intelligence on Return on Investment within Financial Operations
More than seven out of ten organizations (71 percent) employ AI to some extent in their financial operations. Currently, 41 percent of these organizations utilize AI moderately or significantly, with projections indicating an increase to 83 percent in the next three years.
The dissemination of AI has been evident in the six months since the initial surge of research. The percentage of organizations in the original 10 countries that were using traditional AI in their finance operations to a moderate or large degree has increased to 45 percent, compared to 40 percent in April 2024.
However, the utilization of Gen AI has also expanded. The proportion of organizations without intention of utilizing Gen AI has decreased from 6 percent to a mere 1 percent. Gen AI has emerged as a critical focus and a top priority for the future, with 95% of leaders and 39% of others anticipating its selective or widespread adoption in financial reporting within the next three years. Additionally, despite significant disparities, KPMG’s research emphasizes the level of active exploration and utilization of AI in countries worldwide. While companies in the United States, Germany, and Japan have made significant advancements in AI use, other major economies such as Italy and Spain are lagging behind. The same dichotomy is evident in emerging markets, with China and India leading the way in AI usage while Saudi Arabia and African countries are further behind.
Since the initial wave of research, there has been a degree of parity among industries and sectors as organizations have intensified their efforts. Financial services leads the majority of sectors, accounting for 29%, while healthcare trails at 16%. Companies that generate over $10 billion in revenue are more advanced (41 percent of these organizations are considered leaders). Companies are increasingly utilizing AI in all aspects of corporate finance. The most prevalent application of AI is financial reporting, with nearly two-thirds of organizations piloting or utilizing it for financial planning, accounting, and reporting. Nevertheless, other sectors are adopting the same approach: presently, nearly half of organizations are conducting pilots or employing AI for risk and treasury management. This can lead to improved debt management, cash-flow forecasting, fraud detection, credit risk assessment, and scenario analysis in the treasury and risk management functions.
Nevertheless, tax management is marginally behind. Approximately half of the companies are in the planning stage, but less than one-third are currently piloting or utilizing AI in this sector. This use may be even further behind schedule because of things like the complexity of tax laws, a lack of up-to-date data, heavy-duty legacy systems, and the fact that many tax-related decisions are still made by hand. Leaders are demonstrating the way, with over three times as many leaders (87 percent) as others (27 percent) utilizing AI in finance to a moderate or large extent. Leaders are advancing rapidly and have developed an average of six AI use cases, nearly double the number of others. The most prevalent applications of Gen AI are research and data analysis (85%), fraud detection and prevention (81%), predictive analysis and planning (78%), and the composition of documents and other content (75%).
Industry Comments
David Rowlands, Global Head of AI, KPMG International, said: “Our research confirms it – AI is truly a global phenomenon that is being adopted by finance teams across markets and sectors. The benefits it can bring, and the return on investment it can deliver, make it a key strategic focus. The journey is only going to accelerate as new capabilities come on stream. Businesses need to act if they are to stay competitive. The same applies to auditors – which is why we ourselves are investing significantly in AI capabilities to transform the quality, effectiveness and insights of the audit.”
David Rowlands, commented: “It’s hard to think of another business capability where reported levels of return are so high. There are barriers and challenges to overcome, which is why businesses need to proceed with robust governance in place and a clear focus on the outcomes they’re looking to achieve – but the potential benefits are multiplying as we get further into a new era powered by AI.”
FAQ’s
1: What is the current adoption rate of AI in financial operations?
According to KPMG, 71% of organizations use AI in financial operations, with 41% employing it moderately or significantly. Projections suggest this figure will rise to 83% in three years, reflecting AI’s transformative potential in financial reporting, planning, and risk management, driven by technological advancements and increased organizational readiness.
2: Which AI technologies deliver the most value in finance?
Machine learning, deep learning, and generative AI are top performers in delivering ROI. These technologies enhance financial processes through predictive analytics, fraud prevention, and automated reporting. Generative AI, in particular, is gaining traction, with leaders prioritizing its integration into financial reporting and decision-making for strategic advantage.
3: What challenges do organizations face in AI adoption?
Key obstacles include data security vulnerabilities (57%), limited AI expertise (53%), high implementation costs (45%), and inconsistent data collection (48%). Advanced organizations overcome these challenges with robust governance, dedicated AI teams, and external expertise, enabling smoother integration and higher ROI from AI applications.
4: How are industry leaders excelling in AI adoption?
Leaders allocate 13% of IT budgets to AI, establish dedicated AI teams, and implement advanced governance measures. They pilot diverse AI use cases, from fraud detection to predictive planning, and achieve significant ROI by aligning AI strategies with business goals and leveraging both internal and external AI resources effectively.
Conclusion
KPMG’s findings underscore AI’s pivotal role in reshaping financial operations globally. While challenges persist, leaders demonstrate that strategic investments, governance, and resource allocation drive exceptional ROI. As AI adoption accelerates, organizations must prioritize innovation and robust governance to stay competitive, leveraging AI’s transformative power to redefine efficiency, accuracy, and decision-making in finance.
Investment—Leaders are allocating nearly twice as much of their IT expenditures to enterprise-wide AI activities as their peers (13 percent versus 7 percent).
Resourcing – Leaders are establishing their own internal AI resources, such as the organization’s central AI team, a central team within finance, and, in many instances, distinct AI resources within each finance department. Additionally, nearly half of the respondents employ external AI resources, including technology outsourcing companies or consultants.
Governance and assurance – Leaders have implemented additional measures to enhance AI governance. Third-party controls assurance over AI processes and controls is obtained by over half of leaders, which is more than double the number of other leaders. They frequently seek the assistance of their auditors in this regard, and they anticipate that their auditors will be employing sophisticated AI tools in their audit work and engaging in discussions with them regarding AI.
Consequently, executives are more effectively overcoming the obstacles to AI adoption that all organizations face. Data security vulnerabilities (57 percent), limited AI skills and knowledge (53 percent), costs (45 percent), and the ability to collect consistent data (48 percent) are common obstacles that all companies face. However, leaders are more adept at overcoming these obstacles as a result of the measures they have implemented. Their main problems get more complicated, like figuring out how to combine AI solutions with tools they already have and getting past any staff resistance that might still be there.
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