Open your inbox or LinkedIn feed, and you’ll find a dozen posts about the next wave of AI: autonomous agents. Everyone seems to be talking about them. But what exactly are they, and are they something your finance team actually needs?
AI agents are being touted as a future-ready solution for everything from scheduling to accounting. These digital coworkers, in theory, can string together complex tasks with little to no oversight. They're like ambitious interns: give them a goal, and they'll attempt to "figure it out" using prompts, tools, and machine learning.
It’s a fascinating concept. But when you’re buried in month-end reporting or chasing down invoice approvals, you’re probably not thinking, “What I need is a semi-autonomous AI intern.” More likely, you're thinking, “I just need this thing to work.”
That’s where the real conversation starts. Not with the future of agents, but with the kind of AI that actually delivers value today.
Let’s cut through the buzz. AI agents are essentially software programs designed to operate with a level of autonomy. They don’t just respond to a single command; they can observe, plan, and execute a chain of actions based on a goal.
For example, instead of simply extracting data from an invoice, an AI agent could (in theory) process that invoice, match it to a purchase order, identify a mismatch, notify the right person, and update the ERP. All without direct human prompts.
They’re being explored in sectors like customer service, marketing, and finance. According to PwC, agent-based tools could one day assist with real-time financial reporting and process orchestration. But it’s still early. Many AI agents are limited to relatively basic task flows or operate in silos that don’t integrate well with core finance systems.
Even Forbes cautions that while AI agents hold promise, businesses need to balance that potential against practical application, especially in high-stakes environments like finance, where accuracy, auditability, and compliance are non-negotiable.
Most finance and operations teams aren’t asking for futuristic copilots. They’re asking for fewer logins, less rework, and systems that reduce manual effort. The day-to-day grind is still real:
That’s not a failure of vision. It’s a sign of disconnected tools and manual dependencies that automation should have solved already.
These teams need intelligent automation that fits into their existing systems. They need tools designed to:
And most importantly? It needs to just work. From day one.
There’s a time and place for exploration. But for finance teams facing shrinking headcount, rising workloads, and compliance risk, experimental tech isn’t always the answer.
Here’s where AI agents can create more complexity than clarity:
The World Economic Forum notes that while AI agents can improve efficiency and inclusion, the burden of implementation still falls on human teams. If you’re already spread thin, managing and maintaining AI agents might not be the time-saver it’s pitched to be.
Ask any finance leader what they want from AI, and the answer usually isn’t “more tools.” It’s less manual work, fewer errors, and faster processes from day one.
That’s where intelligent automation, not just intelligent agents, is already making an impact.
Take invoice capture. Many AI tools require finance teams to “teach” the system by correcting fields, building templates, and retraining it every time a vendor changes their format. In practice, that means your team is stuck doing the heavy lifting while trying to keep operations on track.
But there’s a better way.
Instead of relying on your team or your vendors to train the tools, forward-thinking organizations are choosing platforms with the right AI. These solutions are already trained on millions of real invoices and know what to look for from the start. These tools don’t need weeks of fine-tuning or vendor-specific setup. They just work.
Compare that to traditional OCR. A typical implementation can take two to three months, including template creation for every vendor format and ongoing maintenance whenever suppliers change layouts. With pre-trained AI, the same implementation takes just weeks, with no templates required.
Here’s what that looks like in action:
The best systems combine this kind of out-of-the-box intelligence with human-in-the-loop support, so results improve over time without adding more work for your team.
Instead of delivering a tool you have to train, these platforms deliver one that’s already trained and gets it right 99.9% of the time.
That’s not a promise for the future. That’s happening right now.
Let’s consider a few hypothetical examples based on common outcomes from high-performing finance teams:
These are the kinds of outcomes finance leaders expect from AI: real operational gains, not theoretical innovation.
As Becker’s Hospital Review explains, the true ROI of AI in finance comes from reducing manual burden, not introducing tools that require more oversight. And that’s exactly what intelligent automation should do: remove friction from workflows, not add to it.
AI agents may very well become more embedded in financial operations down the line. But right now, what most finance teams need isn’t autonomy, it’s accuracy. It’s reliability. It’s automation that adapts to the way they work without requiring them to become AI trainers.
That’s where onPhase delivers.
From Smart Capture and built-in approval workflows to human-in-the-loop accuracy and real human support when you need it, onPhase gives you automation that’s ready right now.
Still sorting through the AI noise?
If you're trying to make sense of what AI can actually do for finance teams, check out this post: The Million Dollar Question: AI in AP – Reality vs. Hype? It’s packed with insights to help you cut through the buzz and focus on what really drives results.