In this episode of Future Finance, Paul Barnhurst and Glenn Hopper discuss how AI is changing the finance technology stack and what it means for CFOs deciding whether to buy new software, build custom solutions, or improve their existing systems. They explore whether AI could disrupt traditional SaaS platforms, where agentic AI is delivering value, and why core financial systems remain essential.

In this episode, you will discover:

• Why AI is changing finance technology without replacing core systems.
• What the Finance Stack Survey reveals about AI adoption.
• The difference between agentic AI and traditional automation.
• When finance teams should buy software or build custom solutions.
• Why data quality, integration, and security matter for AI success.

Paul and Glenn emphasize that finance leaders should focus on solving real business problems rather than chasing new technology. The key is choosing reliable tools, improving data connectivity, and using AI where it delivers meaningful value.

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] - Trailer

[04:21] - Is SaaS at Risk?

[10:27] - Buy vs. Build: Filling the Gaps

[11:09] - Finance Stack Survey Findings

[14:00] - What Is Agentic AI?

[18:20] - AI Adoption and Software Satisfaction

[23:36] - Data and Integration Challenges

[29:41] - Custom AI Solutions

[36:17] - The Future Finance Stack

[42:51] - Closing Thoughts

In this episode of Future Finance, Paul Barnhurst and Glenn Hopper discuss why finance professionals should stop chasing every new AI model and focus instead on building strong processes, durable skills, and better workflows. They also explore the race toward AGI, AI guardrails, and how quickly the technology landscape is changing.

Paul and Glenn explain that the real advantage is not knowing every new model or benchmark. It is knowing how to use AI effectively, understand processes, and build systems that can adapt as the tools continue to evolve.

In this episode, you will discover:

• Why keeping up with every new AI model is becoming impossible.
• Why process design matters more than chasing the latest tool.
• How AI is changing the way finance professionals work.
• Which AI skills are likely to remain valuable over time.
• Why governance and guardrails matter as automation increases.

Paul and Glenn explain that finance professionals do not need to master every new AI release. Instead, they should choose useful tools, learn the fundamentals, and focus on building repeatable processes that can work across platforms.

Follow Glenn:

LinkedIn: https://www.linkedin.com/in/gbhopperiii

Follow Paul:

LinkedIn: https://www.linkedin.com/in/thefpandaguy

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:

[00:58] - The Race for AGI

[04:31] - AGI Risks, Regulation & Uncertainty

[07:12] - AI Is Moving Too Fast

[10:32] - Astra vs. Claude

[15:09] - Secret CFO’s Take on AI Updates

[21:38] - Wrap-Up

In this episode of Future Finance, Paul Barnhurst and Glenn Hopper discuss the accelerating pace of AI development and why trying to keep up with every new model is becoming a losing battle. They explore what finance professionals should focus on instead, including AI workflows, process design, data, governance, and automation.

Paul and Glenn also discuss how AI is changing the way finance teams work. As tools become more capable, they believe the lasting advantage will come from knowing how to structure processes, give clear instructions, manage AI-powered workflows, and apply human judgment where it matters most.

In this episode, you will discover:

• Why finance professionals should stop chasing every new AI model.
• Which AI skills are likely to remain valuable as tools continue to change.
• Why process thinking, data, and orchestration are becoming more important.
• What risks finance teams should consider when using vibe coding and automation.
• Why governance and human oversight still matter in AI-powered workflows.

Paul and Glenn explain that finance professionals do not need to constantly switch tools to gain value from AI. Instead, they should focus on building strong processes that can work across different platforms as the technology continues to evolve.

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] - Welcome

[02:21] - The Race for AGI

[08:28] - AI Is Moving Fast

[17:38] - Stop Chasing Models

[19:43] - Durable AI Skills

[25:03] - Data & Orchestration

[28:08] - Vibe Coding Risks

[32:18] - AI Governance

[34:42] - The Cost of AI

[42:07] - What to Focus On

[44:35] - Closing Thoughts