Agentic workflows vs traditional RPA

The RPA pattern

Classic RPA binds to screens. When the UI moves, bots break. Exception handling is often a hard stop.

That still works for stable green-screen or locked-down portals where APIs do not exist.

The agent pattern

Production agents pull context, apply rules, call tools under permissions, and open human tasks when confidence is low.

They are not magic replacements for every bot. They win when inputs are messy language or documents and systems have APIs.

Migration reality

Many teams keep RPA for UI-only systems and put agent loops on document and API paths. Hybrid is normal.

Do not "AI" a process that is undefined. Fix the workflow first.

Hybrid is the default

Keep RPA where the only interface is a locked vendor UI. Put agents on API and document paths where language and exceptions dominate.

Trying to replace every bot in one program is how budgets die. Replace the paths that break weekly or burn the most analyst hours.

What to measure

Bot breakage rate and mean time to repair for RPA. Override rate and field accuracy for agents. Compare cost per completed case, not cost per license seat alone.

In practice

Map the workflow on a whiteboard before you open a framework: inputs, systems of record, humans, and irreversible writes. If that map is fuzzy, the agent will encode the fuzz.

Pick ten to fifty real historical cases as an eval set. Include the ugly ones. Run the agent offline against them until critical fields and hard rules are acceptable. Only then connect write tools.

Ship with a pause switch, a human queue, and a weekly review of override reasons. Promote repeated overrides into rules. That loop is how production systems improve—not another prompt brainstorm.

Common failure modes

• Treating a demo on clean samples as readiness for production volume.
• One shared service account with broad write access across systems.
• No owner for the exception queue, so failures pile up as noise.
• Changing prompts and models without regression gates on real cases.
• Measuring only model latency or thumbs-up, not completed-case cost and audit completeness.

What good looks like after ninety days

The first workflow is boring: stable override rate, known failure modes, operators who trust the queue. Config changes go through review. Traces answer "what happened to this case?" without archaeology.

At that point you can add a second document type or a second agent role. Expanding before the first path is boring is how programs stall with five half-built pilots.