Adina Simu, Chief Product and Commercial Officer, Auditoria.AI
The talk of AI in finance has been dominated by automation for years. Automating reconciliations, invoice processing, and other repetitive tasks. This focus has yielded value but the industry has now arrived at a point where it’s no longer enough. Increasingly, CFOs are facing the tough reality that finance teams must deal with workloads that are outstripping their ability to manage them. They’re being asked to do more with less, while also keeping pace with delivering real-time insights to the business.
With the emergence of Agentic AI, organizations are obtaining access to a powerful tool that promises to change the financial landscape. While Generative AI generates content when prompted, agentic AI perceives context, can make decisions and act on behalf of the user. It’s a co-worker with a job description that doesn’t need to be told how and when to act. It understands what the business objective is, the data to be considered and the tasks at hand. This is resulting in a shift from task-based automation to autonomous actions and the implications are significant.
Addressing operational challenges in finance with Agentic AI
It is not uncommon for the Office of the CFO to be understaffed and overextended. Hiring is challenging, turnover is high, and burnout is real. The talent that is available is either not being used to its full potential or is spending time doing manual tasks instead of what they were hired to do, deliver more strategic insights to the business.
The irony is that in a time where most business functions have integrated some form of technology to help scale their efforts, finance has remained relatively manual. This has resulted in levels of stagnation that have slowed decision making and reduced the flexibility of the enterprise. It has also left the CFO shouldering more and more responsibility with fewer available staff to assist.
The pressure to transform finance into a more efficient, data-driven component of the business has never been greater, resulting in a move by leading finance professionals to modernize operations.
Now, picture your finance team with an extra, inexhaustible member who never misses a deadline and who gets faster with each passing week. This is a reality with agentic AI. Up until now, automation has focused on rules-based activities. Agentic AI is shaped by new data and outcomes to drive financial workflows rather than simply performing tasks.
Take the process of a financial close for example. Rather than waiting for manual input to advance each step, an agentic AI can track data all day long, know when something is missing, alert the responsible party, and reconcile data without being told what to do at each step. In short, it acts like a finance analyst who has a target destination and the knowledge to figure out how to get there.
Or consider vendor management. An AI agent can identify mismatched invoices, follow up with suppliers, and escalate exceptions without waiting for a human to check every line item. Over time, it gets better at spotting anomalies and optimizing communications.
These are not far-off hypotheticals. They are happening today in finance departments that have begun to embrace this new model.
Of course, with greater autonomy comes greater responsibility. CFOs must be able to trust that AI agents are acting reliably, ethically, and in compliance with internal policies and external regulations. That means embedding guardrails, providing visibility into AI decision paths, and ensuring human oversight is always available when needed.
Transparency is non-negotiable. Finance leaders must be able to audit not only the outcomes of AI-driven processes, but also the logic that led to them. This is not just about governance and confidence, because without trust, the value of autonomy is lost.
The good news is that agentic AI is being built with this in mind. The best systems are not black boxes. They provide explainable outputs, track decision history, and escalate appropriately when thresholds are crossed. In this way, agentic AI becomes less of a risk and more of a control mechanism, ensuring accuracy, consistency, and compliance at scale. The real deliverable is the positive change to how finance teams will reorganize for more meaningful output. Rather than replacing jobs, it frees up human talent to focus on higher-value activities. Financial analysts spend less time gathering data and more time interpreting it. Controllers spend less time chasing invoices and more time improving processes. CFOs spend less time firefighting and more time leading transformation. This is already playing out in forward-thinking organizations. The AI agents may not sit in meetings or show up on the org chart, but they are quickly becoming indispensable teammates by quietly managing the workflows that keep financial operations running.
Rethinking team management
Agentic AI provides a solution that simply hiring more people or relying on legacy automation will not solve. It is a completely new type of capacity that’s scalable and smart. Finance leaders who take the step toward Agentic AI will not only drive down costs, they will build a more agile, future-proof finance function. And to the benefit of the organization, they’ll free up human teams to do what only humans can do — applying judgement and leading operations.
About the Author
Adina co-founded Auditoria.AI in pursuit of elevating innovation in enterprise software applications for the Office of the CFO, and currently serves as Chief Product and Commercial Officer. Born in Bucharest, Romania, she lived, studied, and worked in France, Poland and Romania before relocating to the United States. With more than two decades of experience, Adina has held leadership roles at Oracle, Palerra, VMware, Cisco Systems, and several startups, where she spearheaded the development of advanced tech and ML/AI-driven solutions across Fintech, Legaltech, enterprise infrastructure and cybersecurity.