AI adoption across Finance functions achieves standout levels of ROI with usage only set to increase
- 57 percent of leaders say ROI is exceeding their expectations, compared to 29 percent of others.
- Financial reporting is the most common usage area – but this is widening out to include treasury management, risk management and tax
- Nearly three-quarters of leaders have developed principles and guidelines on the responsible use of AI
New research from KPMG International reveals the dramatic extent to which artificial intelligence (AI) is being deployed in organizations’ finance operations – with compelling levels of ROI and a wide range of benefits including better data and decisions, faster insights and reporting, lower costs, and greater operational effectiveness.
The KPMG report reveals that although investments are being made across a wide range of AI technologies, organizations are extracting the most value from machine learning, deep learning, and generative AI and report the ROI from these technologies is either meeting or exceeding expectations.
The research, published in the KPMG global AI in finance report, covered 2,900 organizations across 23 countries and built upon research conducted earlier this year across 1,800 organizations in 10 countries. A maturity framework was created to assess respondents into three AI-readiness groups: KPMG identifies a cohort of Leaders who are more advanced and more mature in their deployment of AI. A quarter (24 percent) of organizations qualify as Leaders, while 58 percent are middle ground Implementers, and 18 percent are Beginners. KPMG has also developed an AI maturity benchmarking toolopens in a new tab designed to help organizations assess their progress in the AI transformation journey.
AI deployment grows, Gen AI a key future priority
Over seven in ten (71 percent) organizations are using AI to some degree in their financial operations. Currently, 41 percent of them are using AI to a moderate or large degree – and this is predicted to rise to 83 percent over the next three years.
In just six months since the first wave of research, the spread of AI is already visible. Whereas in April 2024, 40 percent of organizations in the original 10 countries were using traditional AI in their finance operations to a moderate or large degree, this has increased to 45 percent.
The use of Gen AI has also grown. The percentage of companies with no intention to use Gen AI has fallen from 6 percent to just 1 percent now. Gen AI has become a key focus and a top priority for the future, with 95 percent of leaders and 39 percent of others expecting to selectively or widely adopt it within financial reporting in the next three years.
Adoption globally
KPMG’s research also underlines the extent to which AI is being utilized and actively explored in countries around the world, albeit with some wide variations. While companies in the US, Germany and Japan are well ahead in AI usage, other major economies, such as Italy and Spain, are behind. The same dichotomy is evident in emerging markets, with China and India ahead in AI usage, and Saudi Arabia and the African countries further behind.
By industries and sectors, there has been something of an equalization since the first wave of research as organizations have increased their efforts – most sectors have a similar percentage of leaders, although financial services heads the pack (29 percent) while healthcare is lagging behind (16 percent). Companies with larger revenue sizes tend to be more advanced (41 percent of companies with revenue over $10bn are leaders).
AI usage opening out across finance
Companies are turning to AI in every area of corporate finance. Financial reporting is the most widespread usage area, with nearly two-thirds of companies piloting or using AI for reporting, accounting and financial planning. But other areas are following suit: nearly half of companies are now piloting or using AI for treasury and risk management. This can generate better debt management, cash-flow forecasting, fraud detection, credit risk assessment, and scenario analysis in the treasury and risk management functions.
Tax management, however, sits slightly further behind. Less than one-third of companies piloting or using AI in this area, although about half are in the planning stage. Usage here may be further behind for a variety of reasons, including the complexity of tax regulations, a lack of up-to-date data, onerous legacy systems, and the reliance on human judgment for many tax-related decisions.
Leaders moving ahead
Leaders are showing the way, with more than three times as many leaders (87 percent) as others (27 percent) using AI in finance to a moderate or large degree. Leaders are moving fast and have on average developed six use cases for AI, almost double the number amongst others. Top areas for usage are research and data analysis (85 percent), fraud detection and prevention (81 percent), predictive analysis and planning (78 percent), and using Gen AI for composing documents and other content (75 percent).
Leaders are achieving success through a combination of factors:
- Investment – Leaders are spending nearly twice as much as others in enterprise-wide AI activities as a proportion of IT budgets (13 percent vs 7 percent).
- Resourcing – Leaders are building up their own internal AI resources including the organization’s central AI team, a central team within finance itself and, in many cases, separate AI resources within each department of finance. Nearly half also make use of external AI resources, such as technology outsourcing companies or consultants.
- Governance and assurance – Leaders have taken more actions to bolster AI governance. Over half of leaders gain third-party controls assurance over AI processes and controls, more than twice as many as others. They often turn to their auditors to do this – and expect their auditors to be using advanced AI tools themselves in their audit work and communicating with them about AI.
As a result, leaders are surmounting the barriers to AI adoption (which confront all organizations) more successfully. Common barriers that all companies encounter include data security vulnerabilities (57 percent), limited AI skills and knowledge (53 percent), gathering consistent data (48 percent) and costs (45 percent) – but leaders are better able to navigate these through the steps they have taken. Their chief barriers become more advanced ones, such as integrating AI solutions with existing tools and overcoming any residual staff resistance.
Reaping the benefits and achieving ROI
As the use of AI in finance grows, the dividends multiply. When starting out, finance teams report two to three benefits. By the time they are leaders, that number is seven.
Just as the benefits from AI can rise with its usage, so does the potential return on investment. As a result, a remarkable 57 percent of leaders say ROI is not just meeting but exceeding their expectations. Even amongst less advanced adopters, nearly one third (29 percent) report the same.
