- Claims report Financial leaders prioritize Excel over AI for automation and safety
- Cautious optimism defines the Finance approach for the Integration Challenges of AI
- Regulatory compliance remains a significant barrier for the deployment of AI
There is a significant gap between the emotion of the industry about the tools of AI and the cautious reality of its implementation in finance, according to new research.
Rossum survey 470 financial leaders from the United Kingdom, USA and Germany to understand how they are sailing through the current panorama of automation and what challenges are coming.
He found that financial leaders are cautiously optimistic, recognizing the potential benefits of AI, but still distrust the associated risks, a point reflected in 58% of financial leaders who still depend on traditional productivity tools such as Excel.
Leaders in the financial industry, known for handling sensitive and highly regulated data, face unique challenges when it comes to adopting AI.
Cybersecurity is a great concern for many leaders, since AI agents and systems introduce new vulnerabilities that cybercriminals can exploit.
IA also complicates the fulfillment of GDPR and the Financial Data Protection Law, and finance departments must establish clear guidelines to govern how these technologies are used.
AI or not, compliance and legal requirements have long raised a barrier to cloud -based tools. Google leaves, often promoted by their native cloud advantages, remains much less popular than Excel, particularly in larger companies.
While AI is seen as a powerful tool to automate document management, the survey found that 27% of financial leaders believe that the risks of implementing AI overcome potential benefits.
For financial leaders who seek to adopt AI automation, the report describes several tactical steps. First, addressing the gap between current tools such as Excel and the most advanced AI technologies is crucial, and Rossum advises organizations that invest in the training of employees in the implementation of AI.
In addition, building solid cyber security frameworks and guaranteeing compliance with regulations will help mitigate the risks associated with the adoption of AI, and establish governance protocols, especially for generative AI, will be essential to navigate the complexities of maintaining ethical standards while implementing IA.
