As finance leaders continue to embed AI in their organizations’ workflows and guide their organizations’ investments, CFOs are increasingly focusing on whether their functions have the core capabilities to scale AI responsibly and unlock its true value – and its potential. Is their talent model and team ready to put AI insights into action?
That idea – and how leaders are working to bring it to life – is woven through Finance Trends 2027, Deloitte’s second annual cross-industry survey of more than 1,400 CFOs and finance executives across 26 countries and from some of the world’s largest companies. The research shows a marked shift from our 2026 report. While some finance executives are still prioritizing AI, automation, and data skills, in 2027, many are working to redesign how the work gets done and helping employees work through adoption opportunities and challenges. The finance executives surveyed this year are focused on whether finance has the core capabilities – trusted data, clear ownership and controls, governance, and AI-ready talent – to scale AI tools responsibly, help the business make better decisions, and realize AI ROI.
They might be learning from experience: so far, AI investment without a true talent focus isn’t paying off for organizations. In a 2025 Deloitte survey of nearly 5,000 c-suite executives, 59% reported a tech-focused approach to AI investment. But those companies were also 1.6 times more likely to report that their AI investments were not exceeding expectations.
An organization’s true return on AI investment typically requires a multi-dimensional approach: work and organizational design to turn transformation investment into enterprise value, and leadership and change enablement to ensure an organization’s leaders, people, and culture are aligned and ready to drive change. And while trust – both in the data and output – remains a key barrier to adoption for many leaders and workforce, that talent is still eager to incorporate AI into their roles, according to Deloitte research. Thirty-six percent of surveyed finance executives cited time and productivity gains as their top ROI metric for AI investment through 2027, while reducing headcount was their least cited metric. Instead, these finance executives are rewiring how finance work gets done, from upskilling and redeploying their workers to redesigning the work itself.
Rethinking the work while restructuring a talent model and implementing new technologies takes time, planning, and a commitment to continuous improvement. AI can help reshape task portfolios, so an organization workforce strategy should acknowledge that as the tech and work continue to evolve, so will talent’s skills and needs. But by redesigning the work so that humans and AI collaborate intentionally, many finance leaders are building a stronger foundation for the future – and a new competitive edge for their teams.
Here’s how a few organizations surveyed in Finance Trends 2027 are supporting their teams:
- Investing in adoption before automation: Before a global tech company launched an agent designed to reimagine their manual, static executive reporting process, finance leaders examined underlying processes, roles, and workforce implications and hired two change management professionals to facilitate. “That's money well-invested in terms of bringing those roles into the team and really driving change management and ensuring that we have the adoption and the success criteria,” says a finance leader.
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Building trusted data foundations: Carlos Alberto Pereira, CFO of Frimesa, Brazil’s largest food processing cooperative, established the company’s 10-person data intelligence team as a foundation for trusted AI use. The team curates information, strengthens governance and data quality, and integrates external data so the business can generate reliable queries across agentic controllership, pricing, and operations.
- Creating a safe experimentation environment: North American financial services company EQB Inc. created an “experimentation studio” to test how agentic workflows could improve long-standing finance processes in a controlled environment. Experimenting in a controlled setting with human oversight can often increase productivity and enhance trust in agentic processes. Just as important, it can help cultivate a stronger culture of human-machine collaboration.
- Investing in the “soft skills”: Nearly one-third of respondents are planning to upskill finance talent with more data and AI literacy skills, and among those focused on upskilling, more than one-third are honing in on development of soft skills, the human capabilities like resilience, strategic judgment, curiosity, and agility that enable strategic problem solving. For example, Alphabet Finance places finance talent in 6- to 12-month temporary assignments to broaden their experience across disciplines, Google Cloud CFO Kobi Bar-Nathan says.
In the age of AI, the CFO can also be the chief talent officer for finance. As their function continues to evolve into a humans x machines organization, finance leaders can lead the charge in building environments in which their human workforce is empowered by AI and energized by the possibilities these technologies hold – a workforce that isn’t just along for the ride, but helping plan and execute the journey.
