Your RPA bots run fine for a few months, then the vendor releases a patch, a finance team rolls out a new dashboard, or an HR manager moves a button to a different toolbar. The xpaths and selectors you worked weeks to build no longer point to the right elements. A developer has to locate the new IDs, debug the workflow, and redeploy, often weeks later. This is the maintenance treadmill that eats up time and money, and it is why many processes stay manual long after you bought the platform.
Why RPA breaks here
Traditional RPA binds to specific selectors, xpaths, and object IDs. When the application changes, the bot breaks. A Forrester-style survey of large enterprises found that 45 percent of automation projects spend more time maintaining bots than running them. Another study in the RPA space showed an average rebuild cost of $7,500 per change, with each change adding roughly 13 working days to the project. When processes involve legacy screens, Citrix environments, or custom-built tools that lack stable object models, RPA teams often hit a wall. They can automate only what is predictable and stable, and they must rebuild every time the UI moves.
What changes with computer use agents
- Survives UI changes without rebuilding selectors
- No brittle selectors to maintain
- Recovers from exceptions instead of halting
- Follows the SOP as written
- Works on legacy and Citrix environments
RPA maintains the UI. Computer use agents see the UI and act like a human: move the mouse, click, type, read the result.
How to move without the risk
Do not rip and replace overnight. Start by identifying one process where RPA is already causing frequent rebuilds or where the UI is unstable. A common candidate is a multi-step approval workflow that spans several applications, or a data entry task that runs on legacy systems and Citrix terminals. Build a clear SOP in plain language for that process. Then run a pilot with a computer use agent. Track the same metrics you use for RPA, such as process time, error rate, and maintenance effort. Compare before and after. If the agent reduces rebuilds by 80 percent, cuts process time by 30 percent, and frees up developer hours, expand the approach to other processes. RPA still makes sense for high-volume, stable, backend tasks. Computer use agents are the durable way forward for processes that change, have many exceptions, and are described in SOPs.
The next step is to see how computer use agents work on your own environment. Book a demo with the Coasty team at https://cal.com/coasty/15min.
Want to see this in action?
View Case Studies