Originally aired December 29, 2025 on Extropy On AIr.
Most organizations tried AI in 2025, but only a small share saw real value, and the difference came down to trust, collaboration and a clear why. Recording together at Extropy’s headquarters in Fort Myers, Florida, Ravit Gutman and Mike Jasper look back at what AI taught the market and Extropy in 2025, and how the company is approaching AI, advisory and utility tools in 2026.
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Key takeaways
- In the McKinsey research Ravit cited, only about 6% of organizations saw true value from AI in 2025, even though most were trying it.
- Start small the right way: solve a smaller problem thoroughly with AI and people, not a big problem with a simple tool.
- The organizations seeing value deployed AI across multiple departments and learned from each other.
- Build AI with the team, not for the team. Trust and a clear why are what make it stick.
- Look for manual work where digitized processes start and stop. That is where small utility tools give time back.
Why did so few companies see value from AI in 2025?
Ravit pointed to a McKinsey report that she called heartbreaking: while most organizations were trying to implement AI strategies, only about 6% saw true value. That gap is driving a lot of AI fatigue. She sees three common approaches, each with its own pitfalls:
- Building homegrown tools. Mature teams built their own solutions, but models changed so fast that something working today could need rebuilding a few months later.
- Buying from technology partners. Many promised big returns, but organizations didn’t build trust or a real working relationship between AI and their people. A great tool delivers little if the team doesn’t understand the why or how to use it.
- Working with consulting partners. The approach Ravit is most excited about: finding the small problems with big value and solving them with the team.
Mike adds that “start small” was often misread. Teams aimed a simple AI tool at their biggest problem and got simple results. The better approach is to take a smaller problem and solve it thoroughly with an AI and human strategy. That creates a win story, builds momentum and earns support from the C-suite down.
Ravit was candid that Extropy had its own failed experiments in 2025 while figuring out how agentic AI could support its consulting teams. Mike sees the positive side: companies now understand AI matters, and failure is a stepping stone as long as it isn’t where the journey ends.
What did the organizations that succeeded do differently?
One finding Ravit took to heart: the 6% seeing value didn’t start with one team and one problem. They deployed AI across multiple departments and learned from each other. Mike points out that in finance this makes sense. Issues in AP, AR or the wider finance function touch suppliers, audit, operations and more, so solving them in a silo only gets you so far. Ravit connects it to what Extropy calls the entropy problem: one team implements a system that affects others who never adopt it, or IT solves a problem the business didn’t know it had.
What is the most important advice for an AI initiative?
For Ravit, it is building trust by building together. You can have the best IT and AI resources, but if the business isn’t part of shaping the tool, refining the outputs and even writing prompts together, that is where failure creeps in. Extropy learned the difference between solving something for the team and solving something with the team. Its AP and procurement users helped shape the MVPs for SmartFetch and SmartSplitter, tools now shared across clients.
Mike’s advice is to understand and align on the why, and to let it grow. Initiatives usually start with one group and one issue, but as you learn how it affects other parts of the organization, the why needs to expand to cover their problems too. Getting buy-in from everyone affected is what builds trust. Ravit admits this was one of Extropy’s biggest lessons of 2025, and everything the team does now starts with being extremely clear on the why.
What AI trends should finance leaders expect in 2026?
Ravit sees much of 2025 spent figuring out AI security and which tools to deploy, whether Copilot, ChatGPT, Gemini or others. She has come to see these tools like employees with different skill sets. With security questions being answered through private servers and closed environments, and new partnerships making it easier to build applications, she expects more mature teams to build their own solutions in 2026. The noise is settling, and companies are ready to build real strategies with partners, whether for solutions, consulting or custom AI tools.
How is Extropy approaching AI in 2026?
Extropy’s product team now works across three lanes: automating its own implementation practices, solving specific problems for clients, and turning common solutions into products it can take to market. Mike likes that Extropy implements everything internally first, which builds both speed and a deep understanding of the why behind each tool.
With clients, the approach starts with inefficiencies, not tools. Every system starts and stops somewhere, so the team looks at the manual work entering and leaving already digitized processes, the places that still frustrate people after a transformation. Ravit sees huge value in small utility tools for work like downloading and splitting documents or managing supplier interactions. Because they are built in short, sprint-like cycles, some can be implemented in a day and show value the same day, then improve through user feedback. Learn more about SmartFetch and Extropy’s other products.
Looking ahead, Ravit is focused on the people side of this revolution. After a decade of building a people-focused, empathetic transformation methodology, she sees it matter more than ever with AI, and previewed the Extropy Playbook, a step-by-step guide to applying that methodology at scale.
In their words
AI is great, but it’s horrible when it’s just tried to be used by itself. And as a replacement.
Ravit Gutman, Extropy Advisors
Every system that you implement starts and stops somewhere.
Mike Jasper, Extropy Advisors
About the speakers
Ravit Gutman is Founder and CEO of Extropy Advisors, a women-owned finance transformation consultancy.
Mike Jasper is VP of Finance Transformation at Extropy Advisors, where he leads digital transformation and client success, working hands-on with clients to set success criteria, optimize their people, process and technology, and measure the results.
FAQ
Why did so few companies see value from AI in 2025?
In the McKinsey research discussed in this episode, most organizations were trying to implement AI strategies, but only about 6% saw real value. Common reasons included homegrown tools that broke as models changed, good tools that teams didn’t trust or understand, and simple AI fixes aimed at big, complex problems.
How should companies start their AI journey?
Start small, but pick a smaller problem and solve it thoroughly with both AI and people, rather than throwing a simple tool at your biggest problem. Build it with the team that will use it, align on the why across every department it touches, and use early wins to build momentum and executive support.
How is Extropy Advisors approaching AI in 2026?
Extropy builds and tests AI solutions on its own work first, then brings what works to clients as solutions, not just products. The team looks for manual work at the start and end of already digitized processes, builds small utility tools that give users time back, like SmartFetch and SmartSplitter, and refines them through user feedback.
Keep exploring
- More episodes of Extropy On AIr
- Previous episode with show notes: The CFO’s 10 Resolutions: From Strategy to Execution
- The follow-up: From AI Hype to Real Impact: How Leaders Create Value
- Six months later: AI in Finance at the Midpoint of 2026
- SmartFetch
- Why Extropy
Want to start your AI journey with the why, not the tool? Book a discovery call with our team.
