CFOs are under pressure from all sides - tightening margins, rising expectations and a wave of AI-enabled systems landing in their tech stack. As ERP platforms, planning tools and reconciliation workflows become increasingly AI-driven, the finance function is evolving into something new.
Automation is steadily absorbing the repetitive and transactional. In its place, finance professionals are being asked to operate at a higher level. This means combining analytical rigour with business acumen, storytelling and strategic foresight. It's no longer enough to close the books and report the numbers. The expectation now is to shape the conversation.
According to IBM's 2024 CFO Study, 65% of finance leaders are under pressure to accelerate ROI across their technology investments. But technology alone won't deliver that return. What matters is how finance teams engage with it. And whether they have the skills, mindset and structures to translate new AI capabilities into business value.
Here are five ways AI is reshaping the finance talent landscape, and what leading CFOs are doing to lead the shift.
AI literacy is the new Excel
For much of the last decade, Excel and accounting standards defined the minimum baseline of competence. That's changing. As AI becomes embedded in forecasting, reconciliation and variance detection workflows, finance professionals need a working knowledge of how these models operate, when to trust them and when to step in.
It's less about coding and more about curiosity - understanding model logic, recognising data limitations and having the confidence to challenge what's presented. Without these skills, teams risk missing critical risks buried in automation.
AI won't replace your team but it will redefine its value
Alongside this skills shift is the question of where humans now create the most value. As automation takes over reconciliations, variance analysis and data validation, finance teams will spend less time producing information and more time turning insights into actionable outcomes.
The differentiator here is how fast and effectively teams can translate machine‑generated results into business action. That demands sharper judgement, closer collaboration across functions and a willingness to take ownership of the decision‑making process.
Hybrid roles are rising in value
CFOs looking to expand their team's value should focus less on adding headcount and more on adding capability. The most valuable finance roles now combine technical skill with strategic contribution, blurring the line between analyst, business partner and technologist.
These hybrid profiles are especially critical in functions like FP&A, where scenario modelling and rolling forecasts increasingly depend on AI-enhanced systems. Professionals who can interpret outputs, engage stakeholders and shape the planning process will deliver more value than those who simply generate reports.
Centres of excellence as the new playbook
Leading CFOs are taking a deliberate approach to building internal AI fluency. Many are formalising their efforts through what IBM refers to as data science centres of excellence - cross-functional groups designed to turn AI potential into tangible business outcomes.
These centres bring together finance, IT and operational leaders to test emerging tools, scale successful use cases and identify skills gaps across the function. The focus is practical - execution, enablement and embedding new ways of working.
According to IBM's 2024 CFO Study, leading CFOs have launched data science centres of excellence 104% more often than their peers. Yet across all CFOs, just 31% have done so.
For finance teams looking to accelerate adoption, strengthen capabilities and share learnings across the business, these centres are quickly becoming a core part of the transformation playbook.
Culture is either the accelerant or the bottleneck
IBM's 2024 report found that 64% of CEOs say AI success depends more on people's adoption than the technology itself. This is because the shift to AI demands a new mindset, one that values experimentation, continuous learning and cross-functional thinking. But driving this kind of change requires clear modelling and reinforcement from the top.
CFOs have a unique role to play in creating the cultural conditions for AI success. That means carving out space for learning, rewarding curiosity and connecting AI initiatives to business outcomes that matter to their teams. It also means acknowledging fear and resistance and actively supporting teams as they navigate the change.
What it all means for CFOs
CFOs leading through the AI shift understand that tools alone won't deliver the promised transformation. What matters is the mindset and capability of the people using them.
As AI's tendrils continue to make their way into core finance workflows, building an AI-ready finance function means developing new skills, rethinking roles and creating the right conditions for teams to engage confidently with intelligent systems.
