2026 CFO focus: accelerating AI adoption for growth and productivity

During a recent EY-hosted roundtable, CFOs explored the challenges and opportunities of integrating AI in finance as they prepare for 2026.

In brief

• CFOs acknowledge that while they are in the early stages of AI adoption, there is a collective urgency to leverage AI for growth and productivity.
• The successful integration of AI hinges on effective data management and a willingness to reimagine processes.
• As the talent landscape evolves, CFOs should consider adapting their hiring strategies to focus on analytics and digital skills.

As CFOs look toward 2026, accelerating artificial intelligence (AI) across finance and the broader enterprise to drive growth and productivity will remain a key priority. In our December CFO roundtable hosted by the EY Center for Executive Leadership, CFOs from Fortune 250 companies gathered to discuss priorities for 2026, which centered on AI and its implications on technology platforms, data architecture, process reinvention and workforce transformation.

Technology: deciding what to bolt on or what to build up

Several CFOs mentioned recent enterprise resource planning (ERP) transformations that have positioned them for success with AI, but the build-vs.-buy paradigm for new capabilities remains prominent. “I’m trying to weigh how much we build a solution or use the usual major platform vendors and just leverage something we can bolt on from them,” one participant said.

A critical consideration in technology architecture is how to marry internal and external data to drive the value from AI. Traci Gusher, EY Americas AI and Data Leader, shared: “One of the things we know about financial forecasting and machine learning is that your internal data is valuable, but external data supercharges accuracy in a forecast. In the architecture and AI models, you can get into a costly situation when you’re bringing all that external data into your ERP environment. There are new alliances that give you the opportunity to mirror your data into solutions without cloud egress charges.”

Action items: Explore new solutions that make it easier to house data, especially from external sources, for forecasting. 

Data: what makes or breaks AI for the entire organization

Scenario planning and other enterprise-wide efforts rely on data that’s housed in finance. “You need to drive cost-efficiency, but don’t throw transactions over the fence,” urged Deirdre Ryan, EY Global Finance Transformation Leader. “They are where we capture data, and that’s where we can drive consistency and drive value and compliance.” Gusher tells clients that, for every dollar spent on AI, plan to spend 20 on data: “Without it, you’ll end up in your never-ending cycle of trying to figure out why your AI isn’t delivering value.”

Although CFOs are understandably wary about “owning” responsibility for data, they are in the best position to drive value and help enable data as a function. One participant said that IT reported to the CFO at his company: “The data lead is organizing our thinking in terms of data products, and staffing with people who know how to do this is critical.”

Action items: Strive to enable data as an enterprise-wide function, and encourage close collaboration between IT and finance in your organizational chart.

Process: it’s time for reimagination, not just optimization

How would you work if you started from a clean sheet of paper? Use-case-specific approaches are yielding building blocks but no transformative value across the enterprise yet, CFOs say, because AI is being shoehorned into old ways of working. And tech leaders often have better insights into reimagining processes than those who are closest to them. 

“We’ve taken our old processes from the old ERP and put them in a new system,” one CFO admitted. “We didn’t want to throw everything in the air at the same time. But we’re going back to redesign from the ground up. We’re going back to basics: what we need to do, not what the software can do. … We hear people say, ‘But two individuals aren’t checking it like before.’ Convincing people that AI is a better control than a human has gone a long way.”

Action items: Take the time to reimagine how you work and what you can achieve with AI, uniting subject-matter leaders with tech specialists, rather than sprinkling in technology.

People: the talent equation has changed — or is being broken

CFOs will be keen to channel productivity gains into either investment for functions or headcount reductions. “We’re trying to stay flat on the workforce year over year,” one attendee said. “And as we grow as a company, we don’t want to add resources in finance or shared services. But it’s definitely a big question for us, particularly because of the amount of investment of what IT wants to make.” Another executive noted that AI was helping them improve work-life balance and make time for more employee training.

Within finance, AI-driven transformation is reshaping finance talent models, with a shift toward hiring for analytics, business acumen and digital skills. Because needed skills are changing, many junior roles where young talent should grow could be axed, even though they’re the most suited for the AI age. “During our layoffs, we didn’t change our new university hiring, but what we need out of university is very different,” a CFO said. Ryan urged CFOs to “borrow” talent through gig marketplaces and alumni networks.

Action items: Leverage rotational programs and rethink roles from across the hierarchy. Assess how to gain a balance of tech skills and technical skills and how to spread them.