Generative AI has sparked interest (hype) in “agentic” systems. Most companies are internally exploring ways to integrate agentic frameworks as part of their automation workflows spearheaded by internal AI task forces. Most top-level use cases overlap with traditional Robotic Process Automation (RPA) or CRON-based workflows. The latest foundational and reasoning models have made feasible a new category of tasks that would fall under Agentic Process Automation (APA). Confusing the two can lead to misaligned tools, wasted resources, and confused expectations. Hence, I shall help demystify and clarify when each approach shines.

What is Robotic Process Automation (RPA)?

RPA uses software workflows to automate rule-based, repetitive tasks that follow strict, predefined steps. Think of it as background jobs or structured workflows that perform a pre-defined set of steps (e.g., downloading, query API, parsing files, transforming across formats, etc.).

Key Traits of RPA:

  • Deterministic workflows: Follows fixed rules (e.g., “If X, then Y”).
  • No cognitive reasoning: Executes process without understanding context.
  • Structured inputs: Relies on largely predictable data and file formats (e.g., API, spreadsheets, forms, CSVs).
  • Human checkpoints: Might require manual approvals at critical steps and runs with minimum interactivity.

Example:

  • Automating invoice processing by extracting data from emails and populating accounting software.
  • Bulk parsing email attachments and populating a database.
  • Downloading stock data post-market hours and updating portfolio with the latest stock prices.

What is Agentic Process Automation (APA)?

APA leverages AI (e.g., LLMs, reinforcement learning, chain of thought) to handle tasks requiring reasoning, adaptation, and decision-making. Instead of rigid rules, APA agents should dynamically navigate ambiguity, learn from feedback, and interact with humans when required.

Key Traits of APA:

  • Cognitive reasoning: Interprets context, infers outcomes, and solves open-ended problems.
  • Dynamic workflows: Adapt to changing inputs or environments.
  • Human-in-the-loop (HITL): Collaborates with humans for guidance or error correction.
  • Unstructured inputs: Works with text, images, or vague instructions.

Example:

  • A customer service agent that resolves complaints by analyzing sentiment, querying databases, and drafting personalized responses.
  • Travel assistant to help create a customized travel itinerary and book the respective hotels and flights.
  • Tax assistant to help me optimize and file taxes

Key Differences: RPA vs. APA

AspectRPAAPA
Task TypeRepetitive with minimal ambiguity or variability.Context-aware processes that require reasoning, judgment, or human interaction
Decision-MakingRule-based, deterministic.Reasoning-driven decision-making
Human InteractionMinimal checkpoints (approve/reject).Collaborative, Human-in-the-Loop HITL (feedback loops).
Learning AbilityNone (static workflows).Improves with data/feedback.

When to Use RPA vs. APA

Choose RPA workflows when:

  • Tasks are repetitive and rule-bound (e.g., parsing, data entry, report generation).
  • Process rarely changes and requires no interpretation.
  • Speed/accuracy matters more than adaptability.

Choose APA frameworks when:

  • Tasks involve ambiguity or require judgment (e.g., figuring out, research, troubleshooting).
  • Processes need to evolve or get personalized with new information and/or user feedback.
  • Outcomes depend on context (e.g., customer interactions, preferences).

Common Pitfalls

  • Mistaking APA for “smart RPA”: APA isn’t just RPA with extra steps—it’s a paradigm shift towards chain of thought reasoning.
  • Overengineering RPA: Don’t force rigid workflows onto reasoning processes (e.g., creative tasks) without appropriate UI/UX.
  • Ignoring hybrid workflows: Some workflows can benefit from blending RPA and APA (e.g., RPA executes steps, APA handles exceptions).

Final Takeaway

RPA automates tasks; APA solves for the problem statement.
Use RPA for repetitive, structured work and APA for adaptive problem statements. With recent advancements in foundational models and chain of thought reasoning, I look forward to seeing more intuitive UIs for APA beyond chat.