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Home » Toughest job in AI implementation: Midmarket CFOs need to lead differently
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Toughest job in AI implementation: Midmarket CFOs need to lead differently

adminBy adminDecember 10, 2025No Comments5 Mins Read1 Views
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Small business resources often face enterprise-level expectations.

Financial industry leaders are under pressure to deploy AI while balancing opportunities and risks such as cyber threats, tariffs, regulatory complexity, and talent shortages.

CFOs are scrutinizing the best tools for finance and overseeing AI investments across the organization. A plethora of “shiny” tools are competing for your attention and budget. But the long road to getting results from these tools is now much shorter. When it comes to AI, the era of “bring the receipt'' has arrived.

KPMG's recent CEO Outlook found that 90% of CEOs are dramatically accelerating their AI ROI window. They now expect to see AI results in as little as six months to three years. This is up from just 22% who expect rapid gains in 2024.

AI can dramatically advance companies, but it has no beneficial effects or harmful direction. Whether it's an advantage or an exposure depends entirely on the preparation of those operating it.

The hastily made decisions are already reflected in the market. Recently, a highly established SaaS company facing ROI pressures from investors suddenly reduced its workforce by nearly 40%, causing immediate strain on customer service, communications, and broker relationships. The effects of these actions can be long-lasting.

The temptation to reduce headcount in the name of AI efficiency can unfortunately result in the loss of important human oversight. AI may also further increase the need for crisis communication plans. The impact of AI on customers can be swift and costly if not properly addressed.

Although there is no universal strategy for AI integration, teeth Leadership can change to protect your investment.

1. Trust in leadership is just as important as trust in data.

The two key themes we hear most often from leaders about the risks of AI deployment are data quality and data quality. people-Related challenges. Transparency is needed to reduce people's risk.

A September AI at Work survey of 1,000 white-collar workers found that 70% doubted HR's ability to fairly manage AI implementation. And 68% want AI training more than job security.

When a leader skips a conversation about why Employees fill the silence with their own stories about what change is happening and what it means for people. The story is usually wrong, spreads quickly, and leaves leaders in a reactive position.

Why it's important: A B2B software company with $100 million in revenue in Q3 2025 introduced AI into internal processes without sufficient training, and the team resisted adoption due to skills gaps. With increased turnover and 40% of employees reporting job insecurity, this culture has significantly declined.

People will adapt to almost any change if they believe that their leaders are honest about their reasons and provide them with the tools and ongoing support they need to sustain it.

2. Deployment is not deployment. It's a relationship.

Treating adoption as a relationship shifts the focus to: install to integration. Leaders learn to pay attention to the interactions that are taking place between their people and the system and quickly pivot when directed to do so.

Why it's important: Morale and well-being suffer due to AI-induced downsizing. In October 2025, a $500 million midsize logistics company eliminated 15% of its 1,400 employees due to AI automation changes. The remaining staff subsequently reported an increased workload, job insecurity, and a 30% drop in morale.

Retention is a permanent burden for many companies, so ongoing feedback is essential before such costly consequences occur.

3. This is not traditional change management.

AI moves too fast for that approach. Traditional change management assumes a finite project with a defined end state. However, AI, automation, and data-driven decision-making pace and texture Not just about the tools, but about the work itself. AI-powered transformation requires: Continuous internal and external calibration Changes in behavior (and mindset), feedback loops, and proactive leadership. It means supporting leaders and teams in a way that gives them clarity, reduces stress and gives them confidence about what is changing. Misaligned priorities, sluggish governance, and overstretched talent can increase risk.

Why it's important: Monitoring the impact on your brand is equally important. An $80 million mid-market marketing agency reduced its creative staff by using AI art generation tools for client advertising campaigns. Consumers called these images “soulless” and customer engagement decreased by 20%. The agency's competitors seized the opportunity to launch anti-AI marketing campaigns, exposing the vulnerabilities of midsize companies that can lose their humanity when downsizing without foresight.

AI readiness depends on how well your workforce is prepared. Tools and training are critical, but they are limited without leadership that establishes tone, clarity, and consistency.

Workday's 2026 Evolution report highlights new skills for CFOs: empathy, storytelling, and cross-functional influence. When finance, HR, and operations run separate transformation tracks, invisible friction is created, leading to duplication, confusion, and competing priorities. Traditional change programs often fail to recognize this because they treat each feature as independent.

To leverage the power of AI, focus on your employees for improved ROI in 2026

Take the next actionable steps now.

  • Please define the reason. Alignment is critical and acceleration is possible when all leaders explain the purpose of AI in one clear sentence.
  • Invest in upskilling and reskilling as a retention strategy.
  • Develop curious, cross-functional, and technically savvy teams.
  • Prioritize agile change management and communication.
  • Lead with empathy and communicate a vision for how technology can augment (rather than replace) talent.

Mid-market CFOs may have smaller budgets due to company size expectations. But they can leverage their scale and inherent agility to bridge technology, strategy, and talent to become the chief architects of AI transformation.




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