As explored in the first article of this series Making agentic AI work: What CFOs need to know, the agentic AI focus has shifted from experimentation to execution. Now, as AI agents reshape the operational cores of large organizations, a tougher question emerges: How to scale productivity and prove value?
The global market for enterprise agentic AI is expected to grow from $3.67bn in 2025 to $24.5bn by 2030. But separate research from Gartner predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027, with leaders citing rising costs and unclear return on investment.
For CFOs, this presents a clear agenda: driving value from agentic AI investments. Agentic systems don’t just automate tasks; they pursue goals, learn from results, and adapt in real time. Their rise will force a rethink of workforce design, performance metrics, and how value is defined across the enterprise.
Agentic AI enables organizations to increase output without adding to headcount. Once optimized, these systems can run continuously, adapt across workflows, and replicate quickly and easily. But scale only matters if it leads to real gains in efficiency.
CFOs are well-placed to judge whether agent-led models genuinely reduce friction. By spotting duplication, inefficient handoffs, or areas where rules-based tasks outweigh judgment-based work, finance teams can help target high-impact areas for agents.
This also means exercising discernment. Automation cannot benefit every process. The CFO must separate high-value opportunities from low-yield distractions.
“CFOs will increasingly need to model two types of capacity, human and agent, in parallel.”
CFOs will increasingly need to model two types of capacity, human and agent, in parallel. This hybrid workforce structure challenges assumptions about staffing, investment allocation, and cost structures, and will change how leaders plan and manage performance.
A key question is how to design teams that allow both human and agentic workers to contribute meaningfully. Agents can handle high-repetition, high-volume tasks such as pattern recognition, compliance monitoring, and data retrieval. Humans, meanwhile, should focus on judgment, escalation, and relationship-building.
CFOs should also consider how to govern workforce spend. What constitutes a productivity gain: headcount reduction, or time saved for higher-value work? They will need to establish new spending models that reflect how they answer this question.
CFOs should lead the redesign of cost metrics that capture the full value of AI-augmented workflows.
Traditional KPIs assume linear, human-driven input. Agentic AI demands a reconfiguration of that model. Agentic systems execute dozens of micro-decisions per minute, none of which appear on a cost center. That makes performance measurement more complex, but also more strategic.
CFOs should lead the redesign of cost metrics that capture the full value of AI-augmented workflows. Output quality, cycle time, and decision consistency become more meaningful than hours logged.
In many cases, the impact of agentic AI will appear indirectly. Finance leaders should look for correlation: where agent deployment reduces backlog, improves responsiveness, or frees skilled individual workers to focus elsewhere.
CFOs can also help businesses avoid one of the most common pitfalls of new technology: incrementalism. Productivity at scale rarely comes from silo-based optimization. It comes from creating value across functions.
Finance has a vital role in cutting out duplication of work, ensuring managers take decisions in a timely fashion, and streamlining inefficient workflows. Agentic AI can help CFOs connect disparate elements to galvanize the whole system.
By applying their lens of resource allocation and enterprise value, CFOs can decide which processes deserve reinvention, not just improvement, pinpoint where legacy systems and processes are constraining growth, and where agents can ‘oil the wheels.’
Agentic AI changes the nature of work.
Agentic AI changes the nature of work. But it also changes how work is measured, planned, and valued. CFOs should not be mere observers in this process. They are essential to making it coherent, accountable, and outcome-focused.
By engaging early with hybrid workforce models, rethinking performance metrics, and applying financial and operational discipline to agentic deployment, CFOs can help ensure that agentic AI delivers on its promise. That means not just more output, but better output. Not just cost savings, but lasting value creation.
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