You face enterprise-level expectations often with small company resourcing.
Finance leaders are under pressure to adopt AI while balancing opportunity and risk, including cyber threats, tariffs, regulatory complexity and talent shortages.
CFOs are vetting the best tools for finance, and overseeing AI investments across the organization. An overabundance of “bright shiny” tools is vying for your attention and budget. But the long runway for results from those tools is now much shorter. It’s time to “bring the receipts” with respect to AI.
KPMG’s recent CEO Outlook found that 90 percent of CEOs have accelerated their AI ROI window dramatically. They now expect to see AI results within just six months to three years. This is up from only 22 percent expecting rapid results in 2024.
AI can catapult companies ahead, but in a beneficial or detrimental direction. Whether it becomes an advantage or exposure depends entirely on the readiness of the people steering it.
Decisions made in haste are already playing out in the market. Recently a very established SaaS company, facing ROI pressure from investors, suddenly reduced its workforce by nearly 40 percent, causing an immediate strain on customer service, communication and broker relations. The consequences from these actions could be long-lasting.
The temptation to reduce headcount in the name of AI efficiencies can unfortunately remove essential human oversight. AI also can spark a greater need for crisis-communication planning. AI-driven customer impact can be swift and costly if not handled well.
There is no universal playbook for AI integration, but there are leadership shifts you can take to protect your investments.
1. Trust in leadership is equally important as trusting the data.
Two key themes I hear most from leaders about the risks to AI adoption are: data quality and people-related challenges. Mitigating people risks requires transparency.
A September AI at Work survey of 1,000 white collar workers found that 70 percent question HR’s ability to manage AI adoption fairly; and 68 percent want AI training and more than job guarantees.
If leaders skip the conversations about why the change is happening and what it means for people, employees fill the silence with their own story. That story is usually wrong, spreads quickly and puts leaders in a reactive position.
Why it matters: A $100M revenue B2B software firm in 3Q 2025 implemented AI for internal processes without adequate training, and teams resisted adoption because of the skills gap. The culture suffered a significant decline with increased turnover and 40 percent of staff reporting job insecurity.
People will adapt to almost any change if they believe their leaders are being honest about the reason for it and provide necessary tools and ongoing support to maintain it.
2. Adoption isn’t a rollout; it’s a relationship.
When adoption is treated as a relationship, the focus shifts from installation to integration. Leaders pay attention to the ongoing exchange between their people and the system, and learn to pivot quickly when indicated.
Why it matters: Morale and well-being suffer with AI cuts. In October 2025, a $500M mid-market logistics company cut 15 percent of its 1,400 staffers due to AI automation changes. Afterward the remaining staff reported increased workloads, job insecurity and a 30 percent drop in morale.
With retention a persistent burden for many firms, ongoing feedback is essential before such costly consequences occur.
3. This isn’t traditional change management.
AI moves too fast for that approach. Traditional change management assumes a finite project with a defined end state. But AI, automation and data-driven decision-making change the pace and texture of work itself, not just the tools. AI-enabled transformation requires continuous internal and external calibration of behavioral (and mindset) shifts, feedback loops and engaged leadership. That means supporting leaders and teams in a way that gives them clarity, reduces stress and builds confidence in what is changing. Misaligned priorities, slow governance and overextended talent can magnify risk.
Why it matters: Brand impact monitoring is equally important. An $80M mid-market marketing agency used AI art-generating tools for client ad campaigns to cut their creative staff. Consumers called the images “soulless,” leading to a 20 percent decline in engagement for their clients. Agency competitors seized on the chance to launch an anti-AI marketing campaign and exposed the vulnerability of mid-market firms that can lose their human authenticity to staff cuts without forethought.
AI readiness depends on how well you prepare your people. Tools and training are critically important, yet are limited without leadership that sets tone, clarity and consistency.
Workday’s 2026 Evolution report emphasizes new CFO skills: empathy, storytelling and cross-functional influence. If finance, HR and operations each run separate transformation tracks, invisible friction builds, causing duplication, confusion or competing priorities. Traditional change programs often don’t catch this because they treat each function as an island.
To capitalize on the propellent power of AI, focus on your people for better ROI in 2026
Start now with these actionable steps:
- Define your why. When leaders all describe AI’s purpose in one clear sentence, alignment is critically important and enables acceleration.
- Invest in upskilling and re-skilling as a retention strategy.
- Foster curious, cross-functional, tech-fluent teams.
- Prioritize agile change management and communication.
- Lead with empathy, communicating the vision for how technology augments (not replaces) talent.
Mid-market CFOs may have smaller budgets, amid enterprise-sized expectations. But they can leverage their size and inherent agility to bridge technology, strategy and talent to become chief architects of AI transformation.
