Agents Are What Automation Wishes It Could Be
If automation does, agents do and decide. Knowing the difference between both could change how your firm runs.
Automation is fast, efficient, and predictable. It follows rules, processes data, and delivers results—until something unexpected happens. Then it stops.
AI agents don’t stop. They adapt. They understand context, make decisions, and improve over time. Where automation executes, agents think. Where automation follows, agents lead.
Firms that stick to automation get efficiency. Firms that embrace AI agents get intelligence, insight, and a real competitive edge.
While automation follows rules, agents make decisions. Knowing when to use each can change how your firm operates.
Automation: Rule-Based and Predictable
AI automation is designed to execute structured, repeatable tasks with high speed and accuracy. It follows predefined rules and does not adapt or learn from new data. If X happens, it does Y. This is what most firms already use, whether they realize it or not.
- Auto-categorizing transactions in bookkeeping software based on set rules
- Extracting invoice data and populating fields in an accounting system
- Running standard financial reports on a recurring schedule
Automation is ideal for high-volume, low-complexity tasks. It eliminates manual work, reduces errors, and speeds up processes. However, it cannot interpret data, identify inconsistencies, or make decisions beyond its programmed rules.
AI Agents: Context-Aware and Adaptive
AI agents go beyond rule-following. They analyze data, interpret meaning, and make context-aware decisions. Unlike automation, which always does the same thing given the same input, agents adjust their actions based on new information. The more they interact with data, the better they become at identifying patterns and making informed recommendations.
- Identifying inconsistencies in financial statements and flagging risks
- Interpreting client emails, detecting urgency, and drafting responses
- Analyzing cash flow trends and suggesting proactive adjustments
AI agents do not just complete tasks—they assist in decision-making. They can recognize anomalies, suggest corrections, and even ask follow-up questions when data is incomplete. This makes them valuable for improving accuracy, providing insights, and enhancing client service.
So, when do you use each?
Automation is there already with
- Bank rec: Automatically match transactions with bank feeds based on preset rules
- Invoice processing: Extract key details from invoices and enter them into accounting software
- Payroll processing: Calculate wages, apply tax rates, and generate payslips without manual input
- Report generation: Produce standard financial reports on a set schedule
There are even countless robots built by firms to automate their workflows to an inch of their existence.
Agents though, are just getting started, and their reach could be mind bending!
Can you imagine your AI-powered agent cross-referencing multiple files, detecting missing journal entries, identifying anomalies, and suggesting adjustments Flagging irregular transactions that may require further investigation? Understand client emails, prioritizing urgent issues, and escalating accordingly?
Up until now, automation was the name of the game: in a world ruled by man hours, efficiency was king since saving time meant saving dollars. But AI agents flip the script. You still get the efficiency (on steroids!), but layered with context, judgement, and adaptability. It’s not just speedy work, but smarter output.
Automation gets you far. Agents expand what’s possible.
