- Report the financial leaders of finance prioritize Excel on AI for automation and security
- Prudent optimism defines the approach of finance to the challenges of IA integration
- Regulatory compliance remains an important obstacle to the deployment of AI
There is an important gap between the excitement of the industry about AI tools and the prudent reality of their implementation in finance, said new research.
Rossum questioned 470 financial leaders from the United Kingdom, the United States and Germany to understand how they sail in the current automation landscape, and what challenges await us.
He revealed that financial leaders are cautiously optimistic, recognizing the potential advantages of AI but still distrusting associated risks – a point reflected in 58% of financial leaders always based on traditional productivity tools like Excel.
The leaders of the financial industry, known to manage sensitive and highly regulated data, face unique challenges when it comes to adopting AI.
Cybersecurity is a major concern for many leaders, as AI agents and systems introduce new vulnerabilities that cybercriminals can exploit.
The AI also complicates compliance with the GDPR and the financial data protection law, and financial services must establish clear directives to govern how these technologies are used.
AI or not, compliance and legal requirements have long laid an obstacle to cloud -based tools. Google Sheets, often presented for its native advantages of the cloud, remains much less popular than Excel, especially in large companies.
Although AI is considered a powerful tool to automate document management, the survey has revealed that 27% of financial managers believe that the risk of implementation of AI prevail over potential advantages.
For financial leaders who seek to adopt the automation fueled by AI, the report describes several tactical stages. First, the realization of the gap between current tools like Excel and the more advanced AI technologies is crucial, and Rossum advises organizations to invest in the training of employees in the implementation of the AI.
In addition, the construction of robust cybersecurity frameworks and the guarantee of compliance with regulations will help to mitigate the risks associated with the adoption of AI, and to establish governance protocols, in particular for generating AI, will be essential to navigate the complexities of maintaining ethical standards while implementing AI.
