
A strong majority of organizations in Canada are embedding layers of artificial intelligence into their financial operations, suggests new from KPMG.
“Canadian organizations are increasingly weaving AI into the DNA of their finance functions,” says Chris Moore, who serves as National Leader of Finance Transformation for KPMG in Canada.
This is “because they want better data-enabled decision making, the ability to more accurately predict trends, and increased data accuracy and reliability,” according to Moore.
Canada’s rate of AI fintech adoption, at 82%, is markedly above the global average adoption rate of 71%.
“Canadian firms are leading the way in tapping the power of AI to improve returns in their finance functions,” Moore commented.
“And this is only just scratching the surface,” he continued. “We’re still in the early stages, and there’s considerable runway for organizations to implement AI in a way that impacts the entire enterprise in an even more meaningful way.”
In addition to a higher adoption rate, Canadian organizations reported a higher rate of return on their AI investments than their global peers (69% in Canada vs 61% globally).
“Canadian organizations are realizing the value AI can bring to their finance function, but embedding it deeper cross core operations, processes and workflows will further improve the quality of financial reporting, which ultimately enhances public trust,” stated Moore.
Accounting, financial planning, taxes, and treasury management are the most common functions within finance where respondents are already using AI or have pilot projects, according to KPMG’s “AI in Finance” report, which surveyed nearly 3,000 organizations across almost two dozen countries, including 100 firms from Canada.
KPMG developed a maturity framework for the use of AI in finance with three categories of maturity: leaders, implementers and beginners. Among Canadian respondents, 25% were classified as Leaders, 60% Implementers, and 15% Beginners.
One major difference between the categories is that leaders are investing nearly twice as much as others in enterprise-wide AI activities as a proportion of their IT budgets. Additionally, leaders reported a much higher number of active use cases for AI than did non-leaders.
“Many AI leaders have a central team within finance, or specialized AI groups within each department of finance, and that’s helped those organizations address challenges such as data, security, privacy and skills gaps more effectively,” explains Moore.
“Canadian organizations that build and leverage their own internal resources will be better positioned to drive AI innovation in finance, and that will ultimately help drive innovation across the enterprise as well,” he added.
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