Given the warp speed at which artificial intelligence (AI) is advancing and businesses are transforming, it is often difficult to find some quiet time to consider the long-term horizon. Yet, CFOs, CEOs and their C-suite peers risk making short-sighted decisions if they neglect spending sufficient time to shape their strategic vision—including decisions concerning leadership pipelines, AI enablement and employee engagement and productivity.
As companies advance their AI-driven capabilities and services, the need and value of human insight, critical thinking, quality assurance and creativity will rise as more employees manage AI agents. However, if AI-fueled automation continues to drive hiring freezes, elimination of certain roles and flatter organizations, development pathways and workflows will dwindle—specifically those that equip early-career finance professionals with subject-, industry- and company-specific knowledge that enables them to sharpen their decision-making and critical thinking skills. The risks include, but are not limited to, loss of talent possessing in-depth knowledge of control activities and critical regulatory compliance requirements.
This conversation begs the question: Where do our future CFOs come from? They don’t grow on trees. They don’t just appear on your doorstep ready to lead and co-partner with demanding CEOs and boards. This pickle in leadership development explains why recent Gartner research on forces reshaping corporate finance groups through 2030 emphasizes the need to address the finance talent crunch. Most of these drivers of finance change are technological in nature (AI agents, machine learning, low-code/no-code platforms and highly standardized transactional processes and supporting systems). Other disruptions relate to organizational structure, talent and culture. Unpredictable regulatory changes round out the list.
Findings from Protiviti’s latest Global Finance Trends Survey reinforce these trends: Leadership development within the organization (which certainly includes mentoring and shaping future finance leaders) ranks among the top five priorities for CFOs.
A Day in the Life of a Future CFO
Before we consider how CFOs should shape their vision to address these changing times, let’s take a speculative look at a day in their life in 2030. Their morning begins with a quick scan of AI agent dashboards: Three peer-to-peer (P2P) bots processed 778 invoices overnight, identifying 11 variances requiring human (in-the-loop) review. Next up, a call with the financial planning and analysis (FP&A) director, who’s concerned about disengagement among remote analysts, who spend 95% of their days interacting with AI agents and feel disconnected from corporate strategy and purpose. A more pressing concern: the ongoing inability to backfill a controller position.
The CFO makes a note to check on the controller search during the biweekly call with the chief human resources officer (CHRO) concerning the finance function’s quarterly structure and skills assessment. On a positive note, a recent move to a consolidated shared-services model is paying off—the center operates with 40% fewer human employees, supported by autonomous AI agents that handle transactional workflows. Plus, three newly installed (human) “finance insight orchestrators” are earning high marks from business partners thanks to the strength of their interpretations of algorithmic outputs.
We can quibble about how long it will take for this type of scenario to come to fruition, but the forces ushering in finance’s future state are firing on all cylinders. Virtual assistants and other AI tools are driving substantial improvements throughout the record-to-report cycle, transforming ongoing close monitoring and helping FP&A teams unlock deeper, value-added financial analyses.
Our survey of global finance leaders shows that nearly three-quarters of finance organizations currently employ generative and/or agentic AI – more than twice as many compared to the previous year. Respondents in a recent, highly attended webinar answered the same question with nearly identical results. The bottom line: AI is here. The key is to begin defining a new talent development model for finance that includes humans, AI agents and tools working collaboratively and seamlessly.
While no formal protocol exists for assessing finance’s future readiness, asking the following questions will give CFOs a strong indication of their preparation needs and priorities:
- How quickly and frequently can we—or do we need to—restructure our operating model?
- To what degree are we assessing the future implications of current decisions affecting talent management, leadership development and organizational culture?
- How detailed (and up to date) are our skills inventories and process maps of all finance workflows?
- To what degree have we reconfigured early-career roles and responsibilities?
- How mature is our technology upskilling capability?
Five Ways to Prepare
Laying the groundwork for 2030 finance requires multiple strategy, talent and technology considerations. Optimizing AI-enablement activities calls for an inventory of current (and needed) finance skills, detailed breakdowns of job roles, and comprehensive workflow and process maps. The result of these endeavors will provide a clearer picture of which responsibilities and tasks are better suited for AI and which require human judgment.
From a culture perspective, finance leaders should create teams whose work aligns with the values and purpose of the organization as a whole.
Other future-readiness preparations include the following:
- Develop human-in-the-loop (HIL) as a core competency: As finance becomes more AI-enabled, the stakes of HIL decisions will soar. The algorithmic decision-making that bots perform must align with organizational risk tolerances. For example, if CFOs prefer not to have procure-to-pay AI agents push the button that sends cash out the door, HIL placements are important.
- Facilitate the transition from “doing” to “QA-ing”: In the not-too-distant future, finance professionals will perform less work themselves and instead will oversee more work completed by AI agents. This means that early-career finance professionals still need to learn the transactional work that an AI agent performs so that they know how to assess its efficacy and any risks it might pose. They also will need training and upskilling in areas such as data analytics and low-code/no-code development.
- Master the “build, buy, borrow or bot” decision: Flatter organizations, smaller staff sizes and the growing need for advanced technology skills require CFOs to expand their talent and skills-sourcing portfolios to include AI agents, who will join full-time employees, co-sourced experts, consulting partners and employees on loan from other organizational groups to seed more diverse, highly scalable finance teams.
- Demonstrate restructuring agility: CFOs should expect organizational restructuring cycles—within the finance group and the overall enterprise—to shrink from every three to five years to annually or even semiannually. Ensuring that the right people are doing the right work at the right time will require more frequent recalibrations of job roles, reporting relationships, outsourcing-FTE mixes, and shifts between centralized and decentralized structures.
- Crack the leadership development conundrum: The traditional finance talent pipeline is under strain: According to data from the American Institute of Certified Public Accountants, the number of CPA candidates who passed their fourth section of the CPA examination declined by 56% from 2010 to 2024, a stretch during which a large portion of CPAs reached retirement age. Future CFOs with the right experience and skills won’t be as easy to find, so innovative approaches to leadership development will become more valuable as more work traditionally performed by early-career finance professionals becomes automated.
A Call to Action
It is time to prepare for 2030 finance. The forces reshaping finance aren’t distant possibilities—they’re already in motion and accelerating. CFOs who wait for these changes to materialize fully before responding will find themselves playing catch-up against competitors who are laying the groundwork today.
The organizations that thrive in 2030 will be those that treat talent development, AI integration and organizational agility not as separate initiatives, but rather as interconnected priorities requiring coordinated action today and careful consideration of implications. Short-term cost savings from automation mean little if they hollow out the leadership development pipeline that sustains long-term competitive advantage.
The greater danger now isn’t moving too fast on transformation—it’s moving too slowly while the talent, technology and organizational foundations of finance shift beneath our feet.