RPA vs browser agents

TL;DR Enterprises have already invested significantly in RPA, and much of that investment continues to deliver value. Browser agents offer an opportunity to extend existing automation capabilities, particularly across dynamic websites, third-party portals, and workflows that require frequent maintenance or manual intervention.

Most enterprise automation programs hit the same wall. The stable workflows were automated years ago and still run fine. The workflows left over live in browsers, on portals the company does not control, behind logins, and on pages that change without notice. Those are the bots that break most often, eat the maintenance budget, and push work back to people when they fail. Browser agents were built for that remaining work.

What is the difference between RPA and browser agents?

RPA (robotic process automation) follows rules and recorded steps, so it performs best when the screen and the process look the same every time. A browser agent is software that drives a real web browser toward a goal, using AI to interpret the page in front of it and decide the next action, so it can keep working when a layout shifts or an unexpected screen appears. RPA optimizes for repeatability on known systems. Browser agents optimize for completing work on systems that move.

How does RPA work?

An RPA bot is a recorded or scripted sequence of actions. A developer maps each click, field, and keystroke to an element on screen, and the bot replays that sequence on a schedule or trigger. This is reliable when the target application changes rarely, which is why RPA earned its place in finance, HR, and back-office operations built on internal systems. The cost shows up when the target changes. A renamed button, a new consent screen, or a redesigned portal stops the bot, and a person handles the work until an engineer repairs the script.

How do browser agents work?

A browser agent runs a real browser and works in a loop. It looks at the current page, decides what to do next to reach its goal, acts, and checks the result. Well-built agents mix two modes. AI handles the parts that vary, such as finding the eligibility results on a portal that was redesigned last week. Deterministic code handles the parts that must be exact, such as submitting a form or writing a value back to a system of record. Browserbase supports both through Stagehand, its open-source framework for combining AI actions with code, running on managed cloud browsers.

The practical result for a buyer is more completed runs, less time spent repairing scripts, and a recorded trail of what the agent saw and did when something fails.

Are RPA platforms adding AI agents?

Yes. The major RPA platforms now ship their own agent capabilities. They offer tools to build AI agents, orchestration layers that coordinate agents, bots, APIs, and people in one workflow with human approvals and governance, and reasoning engines that decide whether a given step should go to an agent, a traditional bot, an API, or a person. Calling RPA rigid or outdated misses this shift.

It also moves the buying question toward where browser work actually runs. Whichever orchestration layer a team uses, an agent that has to log into a payer portal, survive a redesign, and leave an audit trail needs an execution layer built for browsers. That layer is where most production failures happen.

When should you keep RPA and when should you use browser agents?

Keep RPA where it already works, and move browser work that is expensive to maintain. A simple sort covers most estates.

• Keep on RPA: stable internal systems, desktop applications, and high-volume flows whose screens rarely change and whose exception rates are already low.
• Move to browser agents: browser-heavy workflows on third-party portals that break often, need frequent script repair, or send a large share of transactions to manual handling.
• Start on browser agents: work that was never automated because it spans many sites, changes too often, or needs judgment on each page.

What makes browser agents hard to run in production?

Most production failures happen in the execution layer, and four problems come up on almost every serious build.

• Authenticated sessions: portals expire logins, add multi-factor prompts, and log out sessions that look unusual, so agents need to carry login state across runs.
• Changing websites: pages are redesigned on someone else's schedule, so agents need to find elements by intent and fall back to a person when they cannot.
• Browser infrastructure: running thousands of concurrent browsers, with proxies and verified access to protected sites, is its own operations job.
• Debugging and audit: when a run fails, teams need a replay, logs, and a live view to tell a portal outage from a broken step or an expired login.

Our post on the challenges healthcare orgs face when building browser agents goes deeper on each of these for regulated workflows.

How are healthcare teams using browser agents today?

Healthcare runs on portals that predate APIs, which makes it one of the clearest places to see the difference. Two Browserbase customers show the pattern.

Magicare automates skilled nursing admissions

Magicare builds an AI operating system for post-acute care. Hospital referrals for skilled nursing facilities arrive across 12-13 separate portals, and admissions teams used to log into each one and read hundreds of pages by hand. Magicare runs 13 agents per case on Browserbase, one per referral portal, and has retrieved more than 200,000 referrals and 2 million documents through Browserbase sessions. Admissions decisions that took 60 minutes now take under 60 seconds. Magicare uses deterministic Playwright code for this polling work, which is a good reminder that the execution layer matters whether a step is AI-driven or scripted. Read the Magicare story.

Commure automates claims status checks

Commure's billing specialists used to log into dozens of payer portals every day to check claim statuses and download Explanation of Benefits documents. Commure built AI agents on Browserbase that do this automatically, automating more than 8,000 hours of manual work in three months and increasing daily claim processing volume 20x for critical QA workflows. Live view lets the team watch agents work inside payer portals in real time, which gives them the oversight that health data requires. Read the Commure story.

Outside healthcare, Ramp uses Browserbase to power receipt fetching across more than 5 million receipts a month, pulling them from merchant order histories that have no API.

Where to start

Browserbase is the execution layer for browser agents. It runs managed cloud browsers that keep authenticated state across runs with persistent contexts, give agents Verified access to protected sites, and record every session with replays, logs, and a live view that lets a person step in. Stagehand lets teams combine AI actions with deterministic code in the same workflow. Browserbase runs more than 35 million browser sessions a month, is SOC 2 Type II compliant, and offers a HIPAA Business Associate Agreement on the Scale plan, which is what healthcare teams need to run agents against payer and referral portals.

Because it sits under the agent, Browserbase works alongside an existing orchestration or RPA layer. Teams can move their most expensive browser workflows first and leave the rest of the estate where it is.

The numbers that matter are your own. To build a business case around your environment, pick the 10 browser workflows that break most often and talk to our team about validating the assumptions with a side-by-side pilot.