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KPMG: AI Is Transforming Financial Reporting Globally, Near Universal Adoption Expected in 3 Years
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Artificial intelligence (AI) is already being widely adopted in companies’ financial reporting processes, with a majority of businesses piloting or using it, and this is set to grow to almost universal levels over the next three years, according to a global research from KPMG. At the same time, companies expect AI to be increasingly used by their auditors to drive more proactive and predictive audits.

KPMG’s research, titled “AI in Financial Reporting and Audit: Navigating the New Era,” surveyed 1,800 companies across six industries in ten major markets to understand how financial reporting executives feel AI adoption is progressing within the finance function, its impact on internal finance teams, and expectations for external auditors.

Alan Yau, Audit Innovation Leader, Partner, at KPMG China, said: “The adoption of AI in financial reporting is gaining significant momentum in Greater China, with the use universally applicable to both auditors and clients, leading to greater productivity for financial reporting teams and enhancing talent acquisition and skills development.”

North America Is Leading the Way, According to KPMG

Among regions, companies in North America are moving at the fastest pace with 39% of companies in the region selectively or widely adopting AI for financial reporting, followed by Europe (32%) and Asia Pacific (29%).

In terms of sectors, telecoms and technology businesses have made the most progress, with 41% responding that they are now selectively or widely adopting AI within their financial reporting processes, followed by energy, natural resources and chemicals (35%). Consumer products and retail businesses, however, trail other industries (26%).

Companies are investing strategically and substantively in AI. According to the KPMG research, AI now accounts for 10% of the IT budget and is set to rise significantly. All surveyed companies said their Boards have taken strategic action regarding AI.

Nearly two-thirds of respondents (64%) say they expect auditors to have the role of conducting a more detailed review of the control environment in relation to their use of AI in financial reporting. Over half (53%) foresee auditors carrying out an AI governance maturity assessment, while a third expect to ask them to provide third-party attestation over the use of AI technology. However, this is an area where regulation needs to move and maintain pace with the rapid pace of development of use of AI in financial reporting and in auditing.

Generative AI Is Lagging But Set to Pick Up Steam

Generative AI, as a relative technology newcomer, fewer organisations are piloting or using it now (43%) compared to ‘traditional’ AI—but adoption is set to accelerate significantly over the coming three years. Indeed, over the next 12 months leaders are set to prioritise genAI for financial reporting more than any other technology. KPMG found that almost half (47%) will prioritize it, ahead of data & analytics (44%), process mining (39%) and cloud (36%).

Yau added: “Looking ahead, businesses in Greater China are increasingly recognising the immense potential of generative AI. In the realm of financial reporting, AI emerges as a formidable tool that not only enhances decision-making with insightful data analysis but also complements human expertise with its speed and precision.”

He further stated: “By automating routine tasks, AI enables financial professionals to devote more time to strategic planning and fostering client relationships. This symbiotic relationship between AI and human professionals is revolutionizing financial reporting, elevating service standards, and delivering unparalleled value to companies and their stakeholders.”

Businesses, according to KPMG, are also very cognisant of the risks of AI, with data security, privacy, and ethical issues the top concerns. In general, there are currently more concerns over genAI than traditional AI, including cybersecurity issues and copyright & IP alongside other areas such as privacy and hallucinations. Managing the risks and taking an ethical approach to AI implementation is critically important.

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