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Download GenAI in Treasury - A Practitioner's Guide
Download hereIn this paper, we undertake two key tasks. First, through surveys and interviews with treasury practitioners, we offer a current view of GenAI maturity in treasury departments. Second, based on these findings and experiences of those contributing to this paper, we propose a framework to help treasury advance their digital agenda through GenAI.
Key Takeaways
- Adoption of GenAI in treasury has been limited to date. Most firms are at the early stages of opportunity identification or exploratory experimentation.
- Barriers to getting started include access to technical resources and challenges with data quality and visibility. Key concerns include risks in trusting AI outputs and the potential for data leakage.
- That said, AI is a current hot topic for corporate treasury teams. They are mindful of the myriad points of failure embedded in today’s manual processes and seek to improve the speed and quality of decisions (as well, there is perennial pressure to “do more with less”).
- Some common traits of AI leaders in treasury include gaining C-level encouragement and mandate; training to facilitate small experiments and build a change mindset; and prioritizing incremental process improvements before “moonshots”.
- Understanding treasury’s data (and limitations) is another key attribute for success. Treasurers are recognizing the importance of investing in a robust data strategy as a necessary foundation for leveraging AI, as well as readying for a world where they need real-time information to execute faster.
- Against a backdrop of broad corporate investment in AI (in talent and technology), and high expectations of productivity gains, treasurers are recognizing that AI deployment needs to be part and parcel of forward planning for their organization and talent.