By Doug Anderson, CPO, AvidXchange.
Agentic AI is reshaping finance faster than any innovation we’ve seen in decades. For years, AI promised efficiency. Now, with the rise of agentic AI, that promise is becoming a tangible reality.
Major financial institutions like Citi and JPMorgan Chase are already piloting AI agents across research, client profiling, and back-office workflows, while smaller organizations are feeling the pressure to keep pace.
Companies are pushed to do more with less, and agentic AI can be a catalyst. According to a new study, nearly half of finance teams are planning to increase AI investment and almost 80% are confident in its ROI. The moment for agentic AI is here, but leaders need to adopt it with clarity, discipline, and focus. And for many organizations, the fastest path to value will not be building agents from scratch, but adopting solutions where agentic capabilities are already embedded into proven workflows.
Not All Agents Are Created Equal: Understanding the Two Types
Today, 62% of organizations are experimenting with agentic AI, but only 23% have successfully scaled it. That gap will widen between those who understand how to deploy the right agents – and those who don’t. One of the biggest misconceptions is treating all AI agents as interchangeable. In reality, there are two distinct categories, and understanding the difference is critical.
- Research agents sift through massive amounts of unstructured data, summarize insights, and support decision-making. They’re ideal for tasks like market analysis, client profiling, or compliance reviews. Because their output requires human interpretation, they carry lower risk and are often the easiest place to start experimenting.
- Task agents, by contrast, execute processes like processing a payment, updating a ledger, or initiating a transaction. These agents are where the real productivity gains lie for most finance teams, but they also introduce greater risk because they interact directly with financial systems.
For leaders in smaller organizations, the most practical entry point is task agents in low-risk, high-volume areas like accounts payable. Automating repetitive, rules-based workflows delivers immediate ROI while minimizing risk exposure. Many leaders also find greater near-term success adopting agentic capabilities through platforms that already include the guardrails, integrations, and governance required for financial workflows.
The Human Hand Still Matters: Oversight is the Safety Net
Here’s the reality finance leaders need to hear: autonomous doesn’t mean unsupervised.
AI agents excel at speed, precision, and pattern recognition, but they lack the human capacity for control, contextual risk assessment, and accountability. That’s why human oversight remains essential.
An AI agent can flag a suspicious invoice, automate three-way matching, or generate a detailed variance report between actuals and budget. However, a human must still perform the final review, authorize the payment, and ultimately carry the fiduciary responsibility. The agent finds the needle in the haystack; the human decides what to do with it.
This dynamic is also reshaping talent expectations. Finance teams are hiring more tech-proficient professionals, who understand both financial workflows and how to operate alongside digital agents. The technology is powerful, but it’s human expertise that ensures its safe, effective use.
Why Finance Teams Win: Efficiency Without the Risk
For small and mid-sized businesses, time is the scarcest resource. Manual processes consume countless hours and slow down decision making. Agentic AI is designed to compress that time dramatically.
An invoice that once required several touches across disconnected systems can now be categorized, checked for potential fraud, prepared for payment, and sent for human approval – often in minutes instead of days. Forbes reports that agentic AI can reduce banking process time on things like loan approval and disbursement periods from years to months.
This hybrid approach isn’t a temporary bridge – it’s the blueprint for responsible AI adoption in finance. It builds trust, mitigates risk, and allows teams to scale AI gradually as comfort increases.
The Bottom Line: AI Agents Are a Low-Risk Way to Modernize Finance
Agentic AI is no longer an experimental technology. In an environment shaped by inflation, tariffs, labor shortages, and operational strain, finance teams need tools that deliver efficiency without increasing fiduciary risk. AI agents deliver exactly that.
The key is thoughtful, targeted adoption. Understand which type of agent you need. Pair autonomy with human oversight. Start where impact is immediate and measurable. In many cases, that means choosing technologies where agentic AI is already built into the workflow, so teams can move from experimentation to outcomes faster.
Agentic AI won’t replace finance professionals – it will empower them. By freeing teams from manual work and increasing precision, AI agents enable finance leader to focus on strategic, high-value decisions.
Organizations that embrace AI agents now won’t just keep up. They’ll set the pace for the future of finance.
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