New research from KPMG International uncovers the extensive ways in which artificial intelligence (AI) is being integrated into organizations' finance operations. It showcases compelling returns on investment and a plethora of advantages such as enhanced data and decision-making, quicker insights and reporting, reduced costs, and improved operational effectiveness.

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AI Deployment Across Finance

Companies are leveraging AI in every facet of corporate finance. Financial reporting stands out as the most commonly used area, with nearly two-thirds of companies piloting or using AI for reporting, accounting, and financial planning. However, other areas are also catching up; nearly half of companies are now experimenting with AI in treasury and risk management. This enables better debt management, cash-flow forecasting, fraud detection, credit risk assessment, and scenario analysis. Tax management, though slightly behind, is also seeing increased adoption with about half of companies in the planning stage.

For instance, a large multinational corporation implemented AI in their financial reporting process. This led to a significant reduction in reporting time from days to just a few hours. The accuracy of the reports also improved, reducing the risk of errors and providing more reliable data for decision-making.

Another company used AI in treasury and risk management. By analyzing vast amounts of data in real-time, they were able to identify potential risks and take proactive measures to mitigate them. This not only saved them money but also enhanced their overall financial stability.

AI Maturity and Readiness

The KPMG report reveals that organizations are extracting the most value from machine learning, deep learning, and generative AI. A maturity framework was created to categorize respondents into three groups: Leaders, Implementers, and Beginners. A quarter (24 percent) of organizations are Leaders, 58 percent are Implementers, and 18 percent are Beginners.

Take a leading financial institution, for example. They have invested heavily in building their internal AI resources and have a dedicated central AI team within finance. This has allowed them to be at the forefront of AI adoption and extract maximum value from it.

In contrast, some smaller organizations are still in the early stages of AI implementation. They are focusing on building their AI skills and knowledge and gradually integrating AI into their operations.

AI Adoption Globally

AI is being utilized and explored globally, but there are significant variations. Companies in the US, Germany, and Japan are more advanced in AI usage, while Italy and Spain lag behind. In emerging markets, China and India are ahead, and Saudi Arabia and African countries are further behind.

For instance, a Chinese bank has been using AI extensively in their lending processes. By analyzing customer data and creditworthiness, they can make more accurate lending decisions and reduce the risk of defaults. This has helped them expand their business and gain a competitive edge.

In Africa, some companies are just starting to explore the potential of AI. They are investing in training their employees and building the necessary infrastructure to support AI implementation.

Leaders Leading the Way

Leaders are showing remarkable progress in using AI in finance. More than three times as many leaders (87 percent) as others (27 percent) are using AI to a moderate or large degree. They are achieving success through a combination of factors such as investment, resourcing, and governance.

One leading financial services firm has allocated a significant portion of its IT budget to enterprise-wide AI activities. They have also built up their internal AI resources and collaborate with external AI providers. This has enabled them to develop multiple use cases for AI and achieve significant business outcomes.

Another leader in the healthcare industry is using AI for predictive analysis and planning. By analyzing patient data and medical records, they can predict disease outbreaks and plan resource allocation more effectively, improving patient care and reducing costs.

Reaping the Benefits and Achieving ROI

As the use of AI in finance grows, the benefits multiply. Finance teams report two to three benefits when starting out, but as they become leaders, the number increases to seven. The potential return on investment also rises, with 57 percent of leaders saying it is exceeding their expectations, and nearly one-third (29 percent) of less advanced adopters reporting the same.

A manufacturing company that implemented AI in their production planning process saw a significant increase in production efficiency and a reduction in waste. This led to a substantial improvement in their bottom line and a higher return on investment.

A retail company used AI for customer segmentation and personalized marketing. This resulted in increased sales and customer satisfaction, demonstrating the tangible benefits of AI in finance.