- Almost all companies plan to implement or scale AI in finance over the next year and a half
- Many are already exceeding ROI expectations, but use cases need to be defined
- Data security and privacy remain a major concern, cited by three in five
New research from KPMG states that while AI is now in the stage of large-scale deployment, businesses are now urged to focus on security over AI deployment to ensure the greatest success in the future.
The findings come as nearly all (93%) U.S. companies expect to implement or scale AI in finance over the next 18 months, with one in two planning more complex multi-agent AI systems.
As for returns, KPMG found that it has been a case of “so far, so good.” About three-quarters (74%) have met or exceeded their return on investment (ROI) expectations, and those experiencing slower-than-anticipated returns aren’t actually having problems with the capabilities of AI itself.
AI strategies must move to the next stage
The report explains that slow organizational adoption and change management are the biggest challenges, more than the technology itself. The more than 1,000 senior finance leaders surveyed cited a lack of clear, role-specific AI use cases (64%) and a lack of hands-on practice environments (61%) as two key obstacles.
Looking ahead, KPMG calls for more hands-on training opportunities and specific training tailored to AI roles and use cases. And as for those use cases, predictive insights for decision making (45%) are important to finance leaders, as is vibration coding, which is being tested or used by 47% and evaluated by another 26%.
“Leaders are leveraging sophisticated AI to create a finance function that is predictive rather than reactive,” explained Thomas Mackenzie, chief digital officer, Global and US Audit, discussing a “human-led, agent-operated” future.
That’s not to say AI isn’t without its challenges, and many are still concerned about data security and privacy (60%), AI model performance and reliability (56%), and regulatory and compliance issues (53%).
The solution to continued AI success and ROI is to improve the state of AI security, which in turn will increase trust and reduce threat risk.
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