Paul Peterson, CEO & Managing Partner, Wiss.
Automation isn’t new to accounting. From cloud-based general ledgers to optical character recognition for receipt management, firms have chipped away at automating manual work year after year. But what’s happening now is something else entirely. Agentic AI is starting to take over complete workflows, with accuracy and reliability that’s getting hard to beat.
This shift changes the very value proposition of accounting work. Tax preparation, reconciliations and expense classifications no longer define the job. They’re becoming the by-products of a broader client relationship built on insights, planning and continuous support.
For example, through the use of agentic AI at my accounting firm, we have a much more informed starting point, specifically with comparisons of financial information year over year. The AI agent cannot only quantify the variances but also the reasons for such variances.
As firms continue to face talent shortages and growing expectations around advisory services, accounting leaders need to understand how this next phase of AI is reshaping the way firms operate, grow and deliver value.
Operations Shift From Human-Led To AI-Led
Unlike traditional automation tools that follow set instructions, agentic AI works with more autonomy. It understands context, adjusts to the specifics of each client and handles multistep workflows directly inside live financial systems.
Take invoice processing as an example. Tasks that once required a person to check vendor details, assign GL codes, verify budgets and route for approval now run on their own.
At my firm, we leverage AI agents to analyze and interpret invoices, determine appropriate approval workflows based on historical trends, and notify us of any discrepancies from previous experiences. For audits, agents efficiently collect evidence, compare data, identify issues and only forward items needing human review, eliminating the need for manual record searches.
Growth No Longer Depends On Headcount
Growth in accounting has always been closely tied to hiring. More clients meant adding more staff, which worked—until the talent pool started to shrink. That’s where agentic AI shifts the equation. Firms no longer need to scale people at the same pace they scale clients.
This opens the door to a different kind of growth. Instead of being limited by how fast they can hire, firms can gain flexible capacity that can be dialed up or down depending on demand.
Value Moves To Interpretation And Insight
AI agents can interpret transactions, detect anomalies and even anticipate risks, but they don’t understand the relationships, history or strategic goals behind a client’s decisions. That still falls to accountants, who bring the perspective and judgment needed to see the full picture.
Some firms are already exploring how to pair agentic AI with deeper client support. If a system flags a likely covenant breach, it doesn’t stop at detection—it can draft a report, alert the team and even recommend initial next steps. But it’s the accountant who uses that insight to engage the client, talk through options and help shape the right response.
This shift is also changing how firms grow their teams. Entry-level staff may no longer start with reconciliations or data entry. Instead, they’ll need early exposure to advisory work—learning how to oversee AI agents, validate their actions and build the kind of judgment that earns client trust.
Preparing Your Firm: Data, Systems and People
In a recent poll of over 3,300 accounting and finance professionals, the top three barriers to adopting agentic AI were lack of trust in the technology (21%), difficulty integrating AI into existing systems (20%), and limited internal skills to manage AI tools (15%). To overcome these challenges, your firm should focus on three core areas: data, systems and people.
1. Data
Most firms aren’t short on data—they’re short on usable data. Client knowledge lives in inboxes, shared drives, Slack threads and spreadsheets that haven’t been touched since the last audit cycle. AI can’t learn from that kind of mess. It needs structure.
Map out what work gets done, how it’s done and where client-specific rules and preferences live. That means organizing your files, tagging repeatable processes and building reusable templates. It also means teaching AI not just the standard chart of accounts, but how certain clients code software expenses or handle partial invoices.
2. Systems
Agentic AI doesn’t just analyze; it also acts. Therefore, you need to ensure your data is clean and workflows are identified.
Start with digitizing what’s still manual. Eliminate spreadsheets that live outside core systems. Then add integration layers—APIs, data connectors, access controls—that let AI move through systems without breaching compliance or skipping approvals. With the right system access and controls in place, your firm can start small, automate low-risk workflows like invoice categorization or transaction matching, and expand from there.
3. People
As AI agents take on more routine work, accountants will be expected to supervise outputs, apply judgment and lean more into advisory. But most firms haven’t built the training paths or performance models to support that shift. Reskilling needs to happen across all levels, helping your people understand how to review AI-driven work, interpret results in context and guide clients through decisions.
Then there’s the trust gap. When people don’t know what AI is doing or how it affects their roles, it opens the door to doubt. Teams need visibility into what the tech does well, where it needs oversight and how human input still shapes the outcome. Clear communication and change management are essential, especially early on.
The Agentic Future Of Accounting
I believe agentic AI is the next inflection point in how firms create and deliver value. In my view, the firms that benefit most won’t be those that deploy the most AI agents, but those that reengineer their data, systems and talent model around AI as a core operator.
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