Why UiPath Is The Wrong Answer in 2025
Manual data entry costs U.S. companies $28,500 per employee every year. That is not a typo. Over 40% of workers spend at least a quarter of their week on repetitive manual tasks like copy-pasting data between systems. Meanwhile AI computer use agents are finishing those tasks in minutes. UiPath is stuck building better robots for a dying problem.
RPA Is Built For 2015, Not 2026
UiPath and other RPA tools were designed to automate rule-based clicks. They excel at clicking the same buttons in the same order every day. They fail at anything that changes even slightly. A UI layout update breaks a bot. A new form field appears and the robot crashes. You spend more time fixing the bot than you saved by running it. That is the reality of enterprise automation today. The tech has not evolved much since the early 2010s. It is brittle. It is fragile. It requires constant maintenance. Meanwhile the world has moved on to agentic AI that can reason about what it sees on screen and adapt in real time. UiPath is trying to catch up with AI features but it is still fundamentally an RPA product at its core. You are paying for legacy infrastructure wrapped in new marketing.
The Numbers Don't Lie
RPA implementation projects fail at a rate of 50%. That is half of them. Gartner predicts over 40% of agentic AI projects will be canceled by the end of 2027 because they cannot deliver on their promises. UiPath's own documentation admits that automation failures happen in real time and require constant intervention. You are not buying a set-it-and-forget-it solution. You are buying a maintenance headache. Meanwhile AI computer use agents are hitting benchmarks that make those RPA stats look embarrassing. OpenAI's Computer Using Agent scored 38.1% on OSWorld. Anthropic's models are in the high 40s. But the real winners are pure computer use agents like Simular's Agent S3 which achieved 72.6% on OSWorld. That is above the human baseline. One year ago the highest OSWorld score hovered around 20%. This is a technology that went from zero to human-level performance in twelve months. UiPath cannot match that trajectory because it is tied to rigid process automation, not general AI reasoning.
Simular's Agent S3 scored 72.6% on OSWorld, above the human baseline. That is what happens when you build an AI computer use agent instead of a glorified macro recorder.
Why Companies Keep Using UiPath Anyway
You are probably still using UiPath because it is what your finance or ops team knows. You already have licenses. You know how to record a process. You hired a consultant to design workflows. It feels safe. It feels familiar. But familiarity is not a strategy in 2026. The cost of inaction is massive. Every employee wasting time on manual data entry costs your company $28,500 annually. Multiply that by 100 people and you are bleeding millions every year. That is money you could spend on product development, marketing, or hiring better talent. UiPath costs money too. You pay per user or per robot. You pay for cloud infrastructure. You pay for maintenance and upgrades. You pay for training. The total cost of ownership is high. Meanwhile an AI computer use agent can run on a cheap cloud VM or even a desktop you already have. It gets smarter with every task. It does not need a dedicated team of developers to maintain it. You stop paying for complexity and start paying for results.
The Future Is General, Not Rigid
The business world is moving from rigid, scripted automation to agentic workflows that can handle exceptions, learn from mistakes, and coordinate across multiple applications. This is what computer use agents actually do. They see the screen. They understand the context. They decide what to click next. They recover when something goes wrong. UiPath's "Healing Agent" and AI-driven recovery features are attempts to add this capability, but they are bolted on to a framework designed for rigid processes. You cannot retrofit general intelligence onto a rigid architecture. The best computer use agents are built from the ground up to handle real-world complexity. They do not need you to document every possible path. They do not need you to anticipate every edge case. They figure it out as they go. That is the difference between 2015-style RPA and 2026-style AI computer use. One requires you to design the process perfectly. The other lets the AI figure out how to complete the process.
Why Coasty Exists
You need a computer use agent that can actually do the work. Coasty.ai is the #1 computer use agent. Our in-house model achieved 85.6% on OSWorld with public results, plus 82.81% independently verified on the official leaderboard at osworld-v1.xlang.ai. That is higher than every competitor. We control real desktops, browsers, and terminals. Not just API calls that pretend to interact with software. You can run Coasty on your own desktop, in a cloud VM, or as a swarm of agents that work in parallel. We support BYOK so you can bring your own model if you prefer. There is a free tier to get started. We built Coasty because we saw the same problems you see every day. People stuck in meetings while a bot tries to click buttons that do not exist. Teams paying millions for RPA that breaks every time a form changes. It is absurd. The technology has advanced so much faster than the tools companies actually use. We are trying to close that gap.
UiPath is a 2015 technology trying to pretend it is 2026. RPA works for simple, repetitive tasks that never change. It fails at everything else. AI computer use agents are not just faster. They are fundamentally different. They can handle complexity, learn from mistakes, and evolve with your business. You do not need to replace everything overnight. Start with one workflow that bleeds money every day. Feed it into a computer use agent. Watch the savings pile up. Then expand. The future of automation is not robots. It is agents. The question is whether your company is going to lead or get left behind. Go to coasty.ai and see what a real computer use agent can do for your business.