Where CFOs stand: Insights from our recent AI-focused dinners

Article    November 24, 2025
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At Accordion’s recent AI-focused CFO dinners, leaders across industries confirmed that AI interest is high – but most organizations still lack the roadmap, data foundation, and governance to adopt it responsibly. While early wins are emerging in operations, Finance remains largely untapped, and sponsors are pushing for progress. CFOs are ready to move. They just need a structured plan to start.

We recently hosted dinner in Dallas, Chicago, and LA, where CFOs came together to talk AI – not as a buzzword, but as a real operating pressure point for middle-market CFOs. Across industries, CFOs described the same tension: AI is advancing quickly, and their organizations can’t afford to fall behind… yet most still lack a clear roadmap for adoption. 

Here’s what we heard from our CFOs about what’s working, what’s not, and where CFOs see the most immediate opportunity.  

 1. AI interest is high, but maturity varies widely

CFOs expressed active interest in AI, but few feel they have moved beyond early experimentation. Most companies are: 

  • Dabbling with automation or machine learning tools 
  • Testing use cases in finance, HR, or operations 
  • Letting pockets of the workforce “self-experiment” with GenAI tools 

Only a handful have deployed AI in a systematic, governed way. The gap between aspiration and execution remains significant. 

 2. Practical use cases are emerging (especially in operations)

Across sectors, CFOs shared real examples of where AI is beginning to show impact, including:  

  • Predictive maintenance: Using device-level data to anticipate breakdowns and reduce downtime 
  • Interview screening and staffing optimization: Automating initial candidate assessments 
  • Warehouse efficiency: Slotting, picking, and packing improvements based on product/component intelligence 
  • Field service enablement: AI-generated checklists or installation guides 
  • Finance automation: Early attempts at automating reconciliations, AP workflows, or F&A routines 

These use cases tend to be tactical, not transformational… but they’re generating enough value to build executive momentum. 

 3. Talent shortages and workforce constraints are major drivers

Several CFOs noted that AI is becoming a necessary lever because: 

  • Skilled labor is increasingly scarce 
  • Newer generations enter the workforce expecting automation 
  • Traditional processes can’t scale with existing headcount 

Today, AI isn’t being viewed as a threat to jobs but rather as a way to bridge capability gaps, improve consistency, and reduce dependency on tribal knowledge. 

 4. The biggest barriers are governance, change management, and data

While enthusiasm is high, CFOs consistently flagged the same obstacles: 

  • Lack of data readiness (fragmented systems, poor data hygiene) 
  • Unclear ownership between IT, Ops, and Finance 
  • Fear of “shadow AI” as employees adopt tools without controls 
  • Limited time and expertise to distinguish hype from reality 

There are a ton of available tools. It’s the lack of structure, more than anything, that has CFOs feeling behind. 

5. CFOs want a roadmap

Despite the explosion of AI vendors, CFOs expressed fatigue with product pitches. What they want instead is: 

  • Help connecting use cases to ROI 
  • Confidence that their teams can adopt AI responsibly 
  • Practical guidance to sequence the journey (from data, to process, to tools, to governance) 

The recurring sentiment: “Help us plan this, not just buy this.” 

 6. The finance function is still an untapped opportunity

While many teams are experimenting with AI, most adoption has started outside of Finance (in operations, service, and warehousing). Several CFOs acknowledged they have: 

  • Not yet implemented AI in core Finance 
  • Limited visibility into AI capabilities within their ERP 
  • Interest in exploring how AI can enhance close, planning, and reporting 

It’s a clear opportunity for more education and hands-on support to help Finance catch up.

7. PE sponsors are starting to push for adoption

Our AI survey found that 98% of sponsors want their CFOs to prioritize AI adoption – and CFOs are feeling the pressure. Sponsors are increasingly: 

  • Asking about AI use and readiness 
  • Expecting early wins in efficiency and governance 
  • Curious about portfolio-wide adoption patterns 

But sponsors are not prescribing solutions – they’re looking for direction. CFOs are in the driver’s seat. 

The Accordion Advantage 

For PE-backed CFOs, AI is no longer a future trend – it’s a competitive requirement. Interest is high, but most middle-market companies are still missing the essentials: a clear roadmap, a strong data foundation, a practical view of what “good” looks like, and a partner to guide implementation. CFOs are ready to move. But they need the structure and support to do it right. 

That’s where we come in. We know that the “AI talk” you’re hearing from all sides can be deafening. We help cut through the noise by creating a custom roadmap for you based on your unique business.  

Accordion Intelligence transforms your data and tech capabilities into decision-making engines. We leverage leading-edge AI-enabled technology, future-thinking analytical techniques, and the most advanced machine learning so you can use your data and tech to make the kinds of decisions that drive outsized value creation.    

FAQ

Why are middle-market CFOs feeling pressure to adopt AI?

Middle-market CFOs are feeling pressure because AI is advancing rapidly, and organizations worry about falling behind competitors. At the same time, most companies lack a clear roadmap and mature adoption strategy. PE sponsors are also pushing for AI readiness, with 98% expecting CFOs to prioritize adoption. The result is heightened urgency—but without the structure CFOs need to move confidently.

What is the current state of AI maturity among middle-market companies?

Interest in AI is high, but maturity remains low. Most companies are experimenting rather than scaling: dabbling with automation, testing small use cases, or allowing teams to self-experiment with GenAI. Only a small group has implemented AI in a structured, governed, enterprise-wide way.

What AI use cases are showing the most value for CFOs today?

Practical, tactical use cases are emerging across operations, including:

  • Predictive maintenance to reduce downtime
  • Automated interview screening and scheduling
  • Warehouse slotting, picking, and packing optimization
  • AI-generated installation guides for field service teams
  • Early automation of reconciliations, AP, and finance workflows

These aren’t transformational yet—but they deliver enough ROI to build internal momentum.

Why are workforce shortages driving AI adoption?

CFOs cited AI as essential to address persistent labor shortages, rising skill gaps, and new workforce expectations around automation. Rather than replacing jobs, AI is helping teams scale capacity, improve process consistency, and reduce reliance on tribal knowledge.

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