Finance leaders are under immense pressure. Rising costs, talent shortages, and demands for real-time reporting have stretched traditional finance teams to their limits. For companies in IT services, construction, and contracting, the challenge is even greater- project delays, fluctuating material costs, and uneven cash cycles make financial visibility critical. Increasingly, CFOs are turning to artificial intelligence (AI) and automation to transform finance operations from a reactive function into a proactive driver of strategy.
The shift is already underway. Protiviti’s 2025 Global Finance Trends survey found that 72% of finance organizations are now using AI, more than double the 34% adoption rate reported just one year earlier. At the same time, a BCG study of over 280 finance executives revealed that while expectations for AI are high, the median ROI from AI initiatives is just 10%, falling short of the 20%+ that many leaders target.
“It’s not enough just to implement AI tools,” says Brian, CFO Worx CEO.
“The real value comes when finance teams embed AI into core processes, measure results rigorously, and use it as a multiplier for decision-making, not just a cost-saver.”
Where AI Is Delivering Results
CFOs are finding success with AI in the areas where repetitive tasks and complex data have historically slowed finance down.
In accounts payable and receivable, automation is reducing manual processing and cutting error rates. Companies adopting AI-driven invoice matching and reconciliation report faster close cycles and fewer compliance issues. In forecasting, AI models are improving accuracy by analyzing real-time project data, labor costs, and material price fluctuations. With 28% of companies still struggling to keep cash flow forecasts within 10% of reality over a one-year horizon (EY), AI offers a step-change in predictive power.
AI is also emerging as a safeguard. By scanning large volumes of transactional data, AI systems can detect anomalies, like unexpected vendor charges or unusual expense patterns, far more quickly than manual reviews. This early warning capability is proving critical in industries where margins are thin and risk exposure is high.
For project-based companies, perhaps the most transformative use is collaboration. Real-time dashboards powered by AI give project managers visibility into financial performance, helping them adjust operations proactively. Finance is no longer just reporting results but actively shaping execution.
Barriers CFOs Must Overcome
Despite the promise, CFOs face hurdles in making AI adoption successful.
The first is data quality. Poorly structured or inconsistent data undermines even the most advanced algorithms. Without clear data governance, AI often amplifies existing issues instead of solving them.
The second is change management. Finance teams are not always equipped to interpret AI outputs, and employees may resist automation if they view it as a threat rather than an enabler.
Third is measuring ROI. As the BCG survey highlights, many companies struggle to quantify value from AI, with returns lagging behind expectations. Without clear KPIs — whether cost savings, accuracy improvements, or time reductions — AI projects risk being seen as experiments rather than business drivers.
Finally, there are security and governance concerns. Protiviti found that 76% of CFOs cite security and privacy risks as their top concern in deploying AI, especially as finance teams experiment with generative AI tools.
A Smarter Approach to AI Adoption
For CFOs, the path to success lies in being strategic, not opportunistic, about AI.
The most effective teams begin with use cases that deliver immediate, measurable results — such as invoice processing automation or predictive cash forecasting. These early wins build momentum and credibility for broader initiatives. At the same time, investing in data infrastructure is critical. Clean, standardized data is the foundation of trustworthy AI.
Defining metrics up front ensures AI projects can be evaluated objectively. Whether it’s a 20% faster close cycle, a 15% improvement in forecast accuracy, or a 30% reduction in manual processing time, hard numbers help prove value and guide resource allocation.
Finally, people remain at the heart of transformation. Upskilling finance staff to interpret analytics and pairing them with data specialists creates the bridge between technology and strategy. When employees view AI as a tool that elevates their role rather than replaces it, adoption accelerates.
The CFO Worx Perspective
AI adoption is no longer optional for mid-market companies. In project-based industries where margins are under pressure and volatility is high, AI can provide the agility and insight needed to stay ahead. But success requires discipline.
“We’ve seen firms spend heavily on technology without fixing their data or defining success measures,” Brian explains.
“That’s when ROI falls short. For AI to work, CFOs must focus on clean data, realistic metrics, and integration with operations- not shiny tools.”
Is your finance team ready to harness AI for better forecasting, efficiency, and control?
CFO Worx helps mid-market companies implement AI and automation with a practical, results-driven approach.
Content Disclaimer: The information shared in CFO Worx Insights is for general informational purposes only and should not be considered professional, legal, accounting, or tax advice. Each company’s situation is unique, and readers should consult qualified advisors before making business or financial decisions.