Anthony Cecchini is the President and CTO of Information Technology Partners (ITP), an ERP technology consulting company headquartered now in Virginia, with offices in Herndon. ITP offers comprehensive planning, resource allocation, implementation, upgrade, and training assistance to companies. Anthony has over 25 years of experience in SAP business process analysis and SAP systems integration. ITP is a Silver Partner with SAP, as well as an Appian, Pegasystems, and UIPath Low-code and RPA Value Added Service Partner. You can reach him at [email protected].
This month we’re diving into a critical question for any business leader, CIO, or operations executive thinking about automation — What’s the difference between agentic automation and robotic process automation (RPA), and why does it matter for your business?
We’ll unpack what these two approaches really are, where they overlap, where they diverge, and how to think strategically about automation investments as we move into the next decade.
Let’s start with the basics
What Is RPA? 
Robotic Process Automation (RPA) has been part of the enterprise automation toolkit for over a decade, and many organizations have successfully deployed it. At its core, RPA is about using “bots” to replicate human actions—clicking, typing, reading screens, and moving data—without modifying the underlying systems.
There are two major types of RPA bots you’ll hear about:
Attended bots
These run alongside a human worker and assist them in real time. Think of a customer service rep who hits a hotkey and a bot pulls up relevant customer records, fills in a form, or fetches pricing info from another system. The bot is triggered by the human and works in tandem.
Unattended bots
These operate on their own, executing predefined tasks on a schedule or in response to specific events. Think of a bot that logs into a system every night at 2 a.m., downloads reports, formats them, and emails them to stakeholders. No human interaction required.
Both types of RPA bots follow scripts—which means they work well when:
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The process is highly structured
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The inputs are predictable
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The systems don’t change much
But whether attended or unattended, RPA has a common limitation: it doesn’t reason, plan, or adapt. If something deviates from the script, it needs a human or a developer to step in. For awhile we started hearing about how to get the “HUMAN in the LOOP”…
What Is Agentic Automation
Now let’s talk about : Agentic Automation.
At its core, agentic automation refers to software agents—or “AI agents”—that can:
- Understand goals
- Plan multiple steps to achieve them
- Make decisions along the way
- Adapt if something changes
- Chain together multiple tools, APIs, and systems
In short, agentic automation isn’t about following a strict script. It’s about achieving an outcome. The agent figures out how to get there, even if the path isn’t fixed or known in advance.
Think of an AI agent like a junior analyst or project manager you hire. You give them a task (“Get me the latest compliance report and notify finance”), and they figure out where the data is, how to access it, what tools to use, what steps to follow, and how to communicate the result.
How Agentic Automation Goes Further Than Unattended Bots
It’s tempting to think of agentic automation as just a “smarter” unattended bot—but that would be underselling what’s happening here. Here’s the big shift: agentic automation isn’t just about running without human input—it’s about running with intent, adaptability, and autonomy.
Let’s break that down…
Reasoning & Decision-Making
Agentic systems are powered by LLMs and reasoning engines that can interpret instructions like:
“Pull all contract modification notices from the last 90 days, summarize them, and notify procurement of anything that impacts SLAs.”
They don’t need a pre-scripted process. They plan one on the fly based on context, resources, and outcomes.
Multi-step Orchestration
An RPA bot might be good at one job: logging into a portal and downloading data. But an agent can string together:
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API calls
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Document parsing
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Internal system lookups
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Email generation
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Exception handling
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Notifications
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Even invoking an RPA bot if needed
This is process orchestration with intelligence baked in.
Error Handling & Recovery
Unattended bots fail when the process breaks. An agent can:
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Notice the failure
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Diagnose the root cause
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Retry the step
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Try an alternate method
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Or escalate to a human with context
That’s resilience, not just automation.
Dynamic Human Collaboration
Attended RPA bots require a human to initiate them. Agentic automation collaborates proactively with humans:
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Asks for clarification when data is missing
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Pauses workflows for approvals
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Adjusts its behavior based on natural-language feedback
This isn’t a macro waiting for a button press—it’s a teammate.
Cross-Domain Capability
RPA bots often stay in one domain (e.g., finance, HR, or IT helpdesk). Agentic automation doesn’t care where the boundaries are. It can:
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Access and analyze policy docs
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Extract data from unstructured PDFs
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Reference business rules
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Coordinate actions across CRM, ERP, and third-party platforms
That’s not just automation—it’s goal-driven intelligence that crosses silos.
Take a look at the table below, it will highlight the differences by capability
But Let’s Be Real: There’s No Magic Button
Agentic automation is powerful, but not plug-and-play. Responsible adoption requires:
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Governance and human oversight
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Training your teams to collaborate with agents
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Monitoring and continuous improvement
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Clearly defined boundaries of authority and autonomy
It’s not just a toolset—it’s an operating model shift.
Summary
Agentic automation doesn’t eliminate RPA—it extends it. It’s the missing layer that connects bots, APIs, documents, and people into an intelligent system that drives outcomes.
If RPA was automation for the known, agentic automation is for the dynamic, the unstructured, and the evolving. The question now isn’t if you’ll need it—but how soon you can leverage it to stay competitive.
