Automation Anywhere Is Charging You Enterprise Prices to Maintain Bots That Break. AI Computer Use Agents Don't.

The Dirty Secret RPA Vendors Don't Put in Their Case Studies

Here's how an Automation Anywhere bot works. You record a workflow. The bot memorizes the exact pixel coordinates, element IDs, and UI selectors for every step. It runs perfectly. Then the SaaS app you're automating pushes a UI update, which they do constantly, and your bot is dead. Now someone has to fix it. That someone costs money. And according to research across enterprise deployments, traditional RPA tools carry a 20-30% annual maintenance cost burden just to keep existing bots running. Not to build new ones. Just to stop the old ones from breaking. For SAP-based workflows specifically, Fiori UI updates alone cause 30-50% failure rates in RPA bots. You're not buying automation. You're buying a part-time job for your IT team. The vendors know this. They've known it for years. The business model depends on it, because every bot that breaks is a support ticket, a renewal conversation, and another upsell opportunity. This isn't cynicism. It's just how the math works when your product is fundamentally fragile.

What a Real Computer Use Agent Actually Does Differently

• ●A computer use AI agent sees the screen like a human does, using vision, not brittle CSS selectors or pixel coordinates that shatter on every UI refresh
• ●It reasons about what it's looking at. If a button moved, it finds the button. It doesn't throw a null pointer exception and page your on-call engineer at 2am
• ●It handles unstructured data natively. PDFs, emails, scanned documents, web pages that change constantly. RPA needs a pre-built connector for all of this
• ●It can operate across any application without custom integration work. Legacy desktop software, web apps, terminals, all of it, same agent
• ●When something unexpected happens mid-task, a computer use agent adapts. An RPA bot stops and waits for a human to intervene
• ●Deployment time goes from weeks of bot-building and testing to hours. You describe the task in plain language and the agent figures out the steps
• ●OpenAI's Computer-Using Agent scored 38.1% on OSWorld when it launched in January 2025. Coasty is at 82%. The benchmark exists precisely because this capability is now real and measurable, not theoretical

Automation Anywhere's 'Agentic AI' Pivot Is Mostly Marketing

To their credit, Automation Anywhere saw the writing on the wall. They've been aggressively rebranding toward 'agentic AI' and 'agentic process automation' since late 2024. Their homepage literally calls them 'The #1 Provider of Agentic Automation' now. But here's the thing: bolting an LLM onto an RPA platform doesn't make it a computer use agent. It makes it an RPA platform with an LLM bolted on. The core execution layer is still the same brittle bot infrastructure underneath. The AI helps with decision-making at certain nodes, sure. But the fundamental problem, that the automation breaks when UIs change, that it needs structured data inputs, that it requires extensive setup per workflow, none of that is solved by calling it 'agentic.' It's like putting a Tesla badge on a 2005 Camry because you added a touchscreen. The drivetrain is still the same. And you're still paying enterprise licensing fees that would make a CFO cry, plus implementation costs, plus the maintenance overhead, plus the consultant fees to build each individual workflow. Gartner predicted in June 2025 that over 40% of agentic AI projects will be canceled by end of 2027, largely because vendors are overpromising on capabilities that don't match the underlying architecture. That's not a knock on agentic AI. That's a knock on legacy vendors trying to rebrand their way into a category they weren't built for.

The Real Cost Comparison Nobody Talks About

Let's get concrete. A mid-size enterprise deploying Automation Anywhere at scale is typically looking at six-figure annual licensing, plus implementation costs that routinely run 3-5x the software cost, plus ongoing maintenance that eats another 20-30% per year. And after all that, IBM's own community published analysis in December 2025 declaring RPA dead as a standalone strategy, specifically because the total cost of ownership balloons the moment you try to scale beyond simple, unchanging workflows. The RPA community on Reddit is having the same argument in real time. Posts titled 'RIP to RPA' are getting thousands of upvotes. Practitioners who've spent years building bot portfolios are openly asking whether they should be learning something else. These aren't AI hype bros. These are the people who actually run the automations. When they start saying the model is broken, you should probably listen. A computer use AI agent, by contrast, doesn't need a custom workflow built per task. It doesn't need connectors. It doesn't need a team of RPA developers to maintain a bot portfolio. You describe what you want done, it does it, and if the UI changes tomorrow, it figures that out on its own.

Why Coasty Exists

Coasty was built from the ground up as a computer use agent, not an RPA tool with AI features stapled to the side. It controls real desktops, browsers, and terminals the same way a human would, by looking at the screen and deciding what to do next. That's why it scores 82% on OSWorld, the standard academic benchmark for computer-using AI, which is higher than every competitor including Anthropic's Computer Use and OpenAI's Operator. That number isn't marketing. It's a reproducible score on a standardized test with 369 real computer tasks across operating systems and applications. The architecture supports desktop apps, cloud VMs, and agent swarms for parallel execution when you need to run tasks at scale simultaneously. There's a free tier so you can actually try it without a sales call, and BYOK support if you want to use your own model keys. The point isn't that Coasty is perfect. The point is that it's built on the right foundation. When a UI changes, it adapts. When a task requires judgment, it reasons. When you need to automate something across three different applications that have no API, it just does it. That's what computer use actually means, and it's a fundamentally different thing from what RPA vendors have been selling you.