Manual data entry costs U.S. companies $28,500 per employee every year. That is not a typo. That is not a figure from 2015. That is 2026 and your people are still copy-pasting invoices into spreadsheets while the money leaks out the door. Meanwhile 80% of AI projects fail to deliver their intended business value , twice the failure rate of regular IT projects. Why are you trusting a calculator that assumes automation works like clockwork when the odds are stacked against you?
Your ROI Calculator Is Lying to You
Most AI agent ROI calculators work like this. You type in your employee count and your manual task volume. The tool spits out a savings number. It assumes your agent will run forever with zero errors. It assumes nobody will resist the change. It assumes your data is clean and your systems play nice together. None of those things are true in the real world. The calculator is a math problem, not a business problem. It tells you how much money you could save if automation was easy. It never tells you how much money you will actually lose building something that does not work.
80% Failure Rate Is Not a Bug. It's a Feature.
- Enterprise AI projects fail twice as often as regular IT projects
- 80% of AI investments never deliver the value they promise
- MIT reports 95% of generative AI pilots are failing at companies
- Most vendors sell hope, not a working system
That 80% failure rate is not a glitch. It is baked into how most automation vendors operate. They give you a model. They give you a calculator. They do not give you a system that can actually control your desktop, your browser, your terminals, and your workflow. You end up with a tool that can write code but cannot click buttons. It can generate prompts but cannot navigate your apps. It can talk about automation but cannot actually do the work.
The Real Cost of a Bad Calculator
When you trust a bad calculator you make bad decisions. You sign contracts you cannot fulfill. You promise savings you cannot deliver. You burn budget on tools that cannot actually do the job. You waste months of engineering time integrating systems that should have worked out of the box. The calculator tells you you will save $47,000 per employee. In reality you spend $47,000 on a tool that fails in production and you still have to pay people to clean up the mess. The calculator is a fantasy. Your bank account is real and it is getting smaller.
Why OSWorld Matters More Than Any Calculator
The only thing that matters is whether your agent can actually do the work. OSWorld is the benchmark that actually tests that. It runs AI models on real-world computer use tasks. It measures how well agents can navigate desktops, browsers, and terminals. It does not care about your spreadsheet formulas or your marketing slides. It cares about whether your agent can open a file, fill out a form, and submit it without human help. That is the only metric that matters for ROI. If your agent scores 40% on OSWorld, your ROI calculator is selling you a lie. If it scores 85%, you are looking at real productivity gains.
Why Coasty Exists
Most tools promise computer use but deliver API wrappers. You still have to write code to click buttons and fill forms. That is not automation. That is just a new layer of work. Coasty is different. It is a computer use agent that actually controls real desktops, browsers, and terminals. Our in-house model scored 85.6% on OSWorld with public results and 82.81% on the official OSWorld-Verified leaderboard. That is higher than any other agent on the market. It means Coasty can handle complex workflows that break other tools. You do not need to babysit it. You do not need to rewrite your entire automation stack. You just tell it what to do and it does it.
Stop trusting calculators that assume automation is easy. Start looking at benchmarks that prove agents can actually do the work. If your computer use agent cannot handle real-world tasks on OSWorld, you are not saving money. You are wasting it. Coasty.ai is the #1 computer use AI agent because it actually works. Download it today and see what real automation looks like.
Want to see this in action?
View Case Studies