Artificial intelligence has moved far beyond static dashboards and basic reporting tools. A new generation of “agentic AI” systems is beginning to reshape how finance professionals manage reconciliation, reporting, and forecasting. Agentic AI refers to autonomous agents capable of acting independently within financial platforms.
These tools are more than data crunchers — they can initiate tasks, make recommendations, and, in some cases, even execute transactions without direct human intervention. As a controller, it’s your responsibility to embrace this technology while also maintaining accountability and financial integrity. Here’s what you need to know.
What Are AI Agents in Finance?
Traditional finance automation tools typically require explicit instructions. For instance, you have to set reports to run at specific times or manually trigger a reconciliation process.
Agentic AI changes the equation by introducing unprecedented levels of autonomy. These systems:
- Monitor Finance Activity: AI agents can watch data in real time, flagging anomalies or triggering workflows without waiting for a human prompt
- Initiate and Complete Tasks: An AI agent may generate and post journal entries, reconcile accounts, and more
- Learn From Patterns: Agents improve their forecasts and anomaly-detection capabilities as they ingest more data
- Collaborate Across Systems: Because they integrate with ERP, treasury, and reporting, agents act like digital colleagues that remove silos
Implementing these systems can enhance the productivity of your team members due to their proactive nature and autonomy.
Opportunities for Controllers
Finance departments are often tasked with doing more with fewer resources while maintaining flawless accuracy. Imagine how much more effective your team could be with the backing of autonomous AI.
Investing in autonomous AI can benefit you in the following ways:
- Reducing Manual Workloads: Routine reconciliations, invoice matching, and other common tasks become faster with the power of AI agents
- Enhancing Real-Time Visibility: Continuous monitoring allows for earlier identification of cash flow issues, compliance gaps, and budget deviations
- Improving Forecasting Accuracy: AI agents can process a wider set of variables, from macroeconomic data to internal sales metrics
- Supporting Decision-Making: AI agents provide timely information for strategic planning
These benefits can translate into more agile reporting cycles, stronger business partnerships, and a clever narrative for boards and investors.
Risks and Governance Considerations
As a finance professional, risk mitigation is in your blood. With that in mind, you’ve undoubtedly considered the dangers of turning an AI agent loose within your organization.
You’re ultimately responsible for financial integrity, which means you can’t simply hand off control to algorithms. Governance is key to getting the most out of your artificial intelligence tools and protecting your business.
When rolling out AI agents, prioritize accuracy and transparency. AI outputs must be explainable and auditable. Avoid “black box” solutions that don’t reveal how conclusions are reached or how they might impact your business.
You must also promote data integrity. Because agents act based on the data they receive, robust information governance and validation processes are essential. Establish policies defining when an AI agent can act independently versus when human review is mandatory.
When allowing AI agents to take over or assist with critical processes, make sure they adhere to reporting standards and comply with frameworks such as SOX. Autonomous systems with the ability to post journal entries or initiate payments present new security risks that must be managed carefully.
By anticipating these issues, you can innovate without throwing risk management out the window. The result will be trustworthy AI agents that are properly governed and monitored.
When governance and transparency are foundational parts of your rollout, regulators, auditors, and stakeholders will be much more supportive of the initiative.
Practical Steps for Controllers
If you’re ready to explore how AI agents can increase your organization’s productivity and output capacity, begin with a phased approach. Consider these steps:
- Start With a Pilot Project: Identify a low-risk, high-volume process, such as vendor invoice matching or simple account reconciliations
- Engage With IT and Compliance Early: Collaborate with internal audit, risk, and technology teams to ensure systems are secure
- Document New Workflows: Treat AI agents like any other team member by setting up guardrails and defining responsibilities
- Train Finance Teams: Help your staff understand what the AI is doing, how to review its outputs, and how to intervene when necessary
- Monitor and Iterate: Regularly assess performance, identify errors, and refine both the AI models and your internal control environment
The goal isn’t to replace your team — it’s to complement their abilities so you and your skilled workforce can focus on judgment and strategy. AI agents can handle redundant tasks with near-perfect accuracy in the background, which is their ideal application.
Controllers Must Become AI Stewards
By preparing carefully now, you can enable your organization to harness the power of agentic AI without compromising accuracy or trust. Remember, your competition is already leaning into artificial intelligence. Now is the time for you to do the same.
