The AI Agent ROI Calculator Nobody Wants to Show You (Because the Numbers Are Embarrassing)

The ROI Math Nobody Does Out Loud

Let's build the actual calculator right here, no email required, no 'talk to sales' gate. Take your average fully-loaded employee cost (salary plus benefits, usually 1.25x to 1.4x base salary). Multiply by the percentage of their time spent on automatable tasks. Smartsheet found that over 40% of workers spend at least a quarter of their workweek on manual, repetitive work. A quarter. That's 10 hours a week per person. For a $90,000 fully-loaded employee, that's $22,500 a year in pure waste, per seat. A computer use agent running on Coasty costs a fraction of that, handles those same tasks faster and without complaining, and doesn't call in sick on a Monday. The ROI isn't 10%. It isn't 50%. In most cases it's measured in multiples. Writer.com published a real case study showing 333% ROI from AI automation within a single year. Three hundred and thirty three percent. Your S&P 500 index fund is not doing that.

Why RPA Never Actually Delivered and Why You're Still Burned

Here's why so many companies are skeptical about automation ROI claims: they got wrecked by RPA. UiPath, Automation Anywhere, Blue Prism. They sold the dream in 2018 and 2019, charged six-figure licensing fees, required armies of developers to build and maintain brittle bots, and then those bots broke every time someone redesigned a UI. Gartner estimated that most RPA projects fail to scale beyond a handful of processes. Reddit threads about UiPath are full of teams who spent two years and $400,000 to automate three workflows. That's not automation ROI. That's a very expensive lesson. The fundamental problem with RPA is that it's scripted. It follows a hardcoded path. Change one button on a webpage and the whole bot falls over. A modern computer use agent doesn't work that way. It sees the screen the way a human does, reasons about what it's looking at, and adapts. That's not a small upgrade. That's a completely different category of tool.

OpenAI Operator and Anthropic Computer Use: The Honest Report Card

The big labs have computer use products. Let's be honest about where they actually are. A detailed independent review published in mid-2025 tested OpenAI's Operator and Anthropic's computer use agent on real tasks, including ordering groceries and navigating common web workflows. The conclusion was rough: 'Computer-use agents seem like a dead end,' and Operator was called 'the best model I tried, but that's not saying much.' Claude Sonnet 4.5 hit 61.4% on OSWorld, the gold-standard benchmark for real-world computer task completion. UiPath's screen agent, which they hyped heavily, landed at 53.6%. These are research previews and enterprise tools that companies are actively paying for. Meanwhile, the OSWorld leaderboard tells a very different story when you look at what a purpose-built computer use agent can actually achieve. Coasty sits at 82% on OSWorld. Not 61%. Not 53%. Eighty-two percent. That gap isn't marketing spin. It's the difference between an agent that mostly works and one that actually ships.

Build Your Own ROI Number in 60 Seconds

• ●Step 1: Count the headcount doing repetitive computer tasks (data entry, report pulling, browser workflows, copy-paste between systems). Be honest.
• ●Step 2: Multiply each person's fully-loaded annual cost by 0.25. That's the conservative estimate of automatable time, per Smartsheet's research across thousands of workers.
• ●Step 3: That number is your annual waste floor. The real number is probably higher because 70% of US workers spend 20+ hours a week just searching for information, per Clockify.
• ●Step 4: A computer use agent subscription runs a tiny fraction of one employee's salary. The payback period on your first automated workflow is often measured in weeks, not quarters.
• ●Step 5: Factor in error rates. Manual data entry has a 1-4% error rate industry-wide. Every error has a downstream cost: correction time, customer complaints, compliance risk. Agents don't fat-finger fields.
• ●Step 6: Add the opportunity cost. Every hour your best people spend on grunt work is an hour they're not doing the thing you actually hired them for.

Why Coasty Exists

I've watched teams try to build ROI cases for AI tools that are fundamentally toys. Browser extensions that can't handle a real workflow. Chatbots dressed up as agents. RPA bots that require a dedicated engineer to babysit them. Coasty was built specifically to be the computer use agent that actually closes the ROI gap. It controls real desktops, real browsers, and real terminals, not just API calls wrapped in a pretty interface. It runs on a desktop app or cloud VMs, and if you need to parallelize work across dozens of tasks simultaneously, agent swarms handle that. The 82% OSWorld score isn't a lab result that evaporates in production. It reflects what happens when you point a genuinely capable computer-using AI at the kind of work your team does every day. There's a free tier if you want to run your own ROI test before committing to anything. BYOK is supported if you want to bring your own model keys. The point is: the barrier to finding out your actual ROI number is basically zero. There's no excuse to still be doing this math on a spreadsheet.