Automation has traditionally meant record and replay. That built an entire industry, and a maintenance treadmill to go with it. RPA, robotic process automation, is software bots that mimic human clicks and keystrokes to run repetitive tasks. Record the steps once, replay them forever. It works, right up until the screen changes. Mobile AI agents offer a different deal: describe the outcome you want, and let the system figure out the steps. So which one is better for you?
How RPA works, and why its not ideal
RPA is how teams used to automate tasks since computers became widespread inside offices. The idea was to identify repeat workflows which always followed the exact same path, show the software the steps once where it captures the exact buttons and fields you touched, and then it repeats them. Tools like UiPath, Automation Anywhere, and Blue Prism built the category, and on mobile you'll see the same idea in things like Tasker or Appium.
Under the hood, it's hardcoded. The bot remembers precise targets, this button at this spot, that field with that name, and follows a fixed path someone drew in advance. At runtime it isn't really thinking, instead string searching for elements and hoping its still where thy were expected? If yes, it proceeds. If no (which it often does), it breaks and throws errors.
The breaking isn’t something you can really control. Most RPA workflows break and become invalid because of app updates, A/B tests or permission dialogues because some compliance process now requires them. So, unless your team gets early access to future updates, you cannot prevent process breakage, and can only optimize for how fast you fix them.
How AI agents differ
Instead of recording steps, you give it a goal in plain language. Book me the cheapest ride home. From there it runs a loop: it perceives what's actually on screen, reasons about the best next action, acts, then looks again and re-plans.
That last part is everything. Because it reads the live screen every time, it adapts. A button moved? It finds it. A new popup appeared? It deals with it. The intent survives even when the interface changes, and that's the one thing a recorded script can never do. It self-heals instead of breaking. God bless all that HTML and JavaScript training data on the internet.
It's not free, though. All that reasoning means it's slower and costs more per action, because there's a model thinking at each step. And it's less predictable, which makes it harder to audit than a fixed script. Different tool, different trade-offs.
Where RPA still wins
To be fair, RPA earns its keep in the right conditions. It's deterministic, the same steps run the exact same way every single time, which is exactly what you want for something genuinely 100% repetitive and static. It's auditable, every action is explicit and logged, which matters a lot in regulated industries where you have to prove what happened.
Furthermore, on a stable screen that doesn't change, it's fast and cheap, because there's no AI thinking in the loop, just straight execution (no tokens burnt). So if you've got a high-volume, repetitive task running on an interface you fully control, RPA is still the gold standard.
Some time should be taken to stress that RPA isn’t a bad way to automate processes, but it is a brittle one. It is shines in the flows which need to be deterministic and you have full control over. This is why, for best results, it actually makes sense to use but AI agents and RPA together, which brings us to our next section :)
Hybrids (Where true automation winners play)
The smartest setups mix both. It takes a bit more time and though to set up, but offers best of both worlds. The best automation engineers let the agent handle the messy parts, navigation, ambiguity, recovering when something unexpected shows up, then hand off to a deterministic script for the steps that must run identically or cheaply every time.
Models have gotten so good over the last couple of years that you can even flip this logic. As in, let an agent watch your RPA bots and auto-repair the selectors when they break, so a layout change becomes a shrug instead of a support ticket. There are many ways of making these mixed pipelines fit your use case. Just like how the world isnt completely solid or liquid, neither are the best automation scripts.
So, which one should you use?
Using RPA still makes the most sense when the environment it works in is fully controlled and needs strong auditing. But processes uncertainty and chaos where flexibility is needed are where embracing AI agents serve as the trillion dollar value lever. But as most things in life, the truth lies somewhere in the middle, which is why understanding and using each, and combining them together delivers the best results.
As AI gets better (and cheaper) with time, the need for RPA will likely diminish further, but there will still be niches where it is necessary. Regardless, the best automation teams will still continue to use both, and adapt as the tools improve.
