In this episode of Future Finance, Paul Barnhurst and Glenn Hopper discuss AI fatigue and why finance professionals should focus less on chasing new models and more on using AI effectively. They share practical ways to improve AI results through better instructions, reference files, context, and data foundations.
In this episode, you will discover:
- Why AI fatigue is becoming a real challenge.
- Why prompting alone is no longer enough.
- How context and reference files improve AI results.
- Why clean data and clear KPIs matter.
- How finance teams can start using AI more effectively.
Paul and Glenn emphasize that finance teams do not need to build complicated systems immediately. Starting with clear data definitions, documented sources, and simple context files can already make AI much more useful.
Follow Glenn:
LinkedIn: https://www.linkedin.com/in/gbhopperiii
Follow Paul:
LinkedIn: https://www.linkedin.com/in/thefpandaguy
Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration produced under human editorial review.
Future Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai.
Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.
In Today's Episode:
[00:00] - Introduction
[01:07] - AI Fatigue
[04:09] - Using AI Effectively
[05:44] - The Changing Role of Prompting
[07:40] - AI for Financial Modelling
[11:37] - AI and Finance Data
[14:47] - Building a Data Foundation
[18:10] - Practical AI Tips
[19:08] - Closing Thoughts
