73% of Supply Chain Teams Still Do This Manually. A Computer Use AI Agent Fixed It in Days.
Supply chain disruptions cost businesses an estimated $184 billion annually. And a huge chunk of that isn't geopolitical chaos or port strikes. It's someone on your ops team manually re-keying data from a supplier email into a spreadsheet, then into your ERP, then sending a follow-up email to confirm the number they just typed is correct. In 2025. This is real. A Parseur survey from July 2025 found that manual data entry costs U.S. companies an average of $28,500 per employee every single year. If you have 20 people touching supply chain workflows, that's $570,000 gone before a single disruption even hits. The industry has been sold dashboards, integrations, and 'visibility platforms' for a decade. None of them solved the actual problem, which is that someone still has to do the work. That's the conversation nobody wants to have.
The Dirty Secret: 'Automated' Supply Chains Aren't
Here's a stat that should make every logistics exec uncomfortable. A 2025 report on retail supply chains found that 66% of teams still rely on spreadsheets, email, and messaging apps as their primary coordination tools. A separate Freightos study found 73% of freight procurement teams are still running manual processes. Not partially manual. Primarily manual. These are companies that almost certainly have a 'digital transformation' slide in their board deck. They've bought the WMS, the TMS, the procurement platform. And their senior buyer is still spending three hours every Monday morning copying freight quotes from PDF attachments into a rate comparison sheet. The tools got better at storing data. Nobody automated the human in the middle who moves it around. That's the gap. That's where the money is bleeding out.
What Traditional RPA Actually Gets You (Spoiler: Frustration)
- ●RPA bots like UiPath break the moment a UI changes. One supplier updates their portal layout and your entire automation is offline until someone fixes the selector.
- ●Setup takes weeks or months per workflow. By the time it's live, the process has already changed.
- ●RPA can't handle unstructured inputs. A PDF invoice with a slightly different format? A supplier email written in plain English? The bot panics.
- ●Maintenance costs often exceed the original build cost within 18 months. Gartner has flagged this for years and companies keep ignoring it.
- ●73% of freight procurement teams are still manual in 2025 despite RPA being available for over a decade. That's not a slow adoption curve. That's a signal that the tool doesn't actually solve the problem.
- ●RPA requires your processes to be perfectly documented before you automate them. Most supply chain workflows aren't. They live in people's heads and email threads.
Manual data entry costs U.S. companies $28,500 per employee per year. A 50-person supply chain team is burning $1.4 million annually on work that should not require a human brain.
What an AI Computer Use Agent Actually Does Differently
A computer use agent doesn't need an API. It doesn't need a pre-built connector. It doesn't need your supplier to have a modern portal. It sees the screen the same way a person does, and it acts on it. Log into a supplier portal, pull the latest lead times, cross-reference against your ERP, flag the discrepancies, and draft the follow-up email. That full workflow, done by a human, takes 45 minutes. Done by a proper AI computer use agent, it takes minutes and runs while your team is asleep. This is the actual unlock. Not 'AI-powered insights.' Not a prettier dashboard. An agent that opens the browser, navigates the portal, reads the data, and does the thing. The reason most enterprise AI pilots fail in supply chain is that companies buy tools that analyze processes instead of tools that execute them. There's a massive difference between an AI that tells you your freight costs are trending up and an AI that goes and renegotiates the rate request on your behalf.
The Workflows That Should Already Be Gone
Let's be specific, because vague promises about 'streamlining operations' are exactly what got the industry into this mess. Here are supply chain tasks that a computer use agent can handle today, right now, without a six-month implementation project. Supplier onboarding is one of the worst offenders. Collecting certificates, verifying compliance documents, entering vendor data into systems, sending status updates. It's entirely procedural and it eats procurement teams alive. Then there's purchase order management, tracking confirmations across dozens of supplier portals, none of which share a standard format. Freight rate comparison across carrier portals. Inventory reconciliation between your WMS and your ERP when they inevitably disagree. Customs documentation prep. Invoice matching and exception flagging. Every single one of these is a task where someone is reading information from one screen and doing something with it on another screen. That is textbook computer use territory. The question isn't whether AI can do this. It's why you're still paying humans to do it.
Why Coasty Is the Obvious Answer Here
I've looked at the options. Anthropic's Computer Use is impressive in a demo. OpenAI's Operator has its moments. But when you run them against OSWorld, the benchmark that actually tests whether an AI agent can operate a real computer environment across real tasks, the scores tell the story. Coasty sits at 82% on OSWorld. No other computer use agent is close. That gap matters enormously in supply chain contexts because the tasks aren't clean. Supplier portals have weird UI quirks. ERPs have legacy interfaces that were built before anyone imagined an AI would be navigating them. PDFs are formatted inconsistently. You need an agent that can handle ambiguity and keep going, not one that scores great on a curated demo and falls apart on your actual Ariba instance. Coasty runs on real desktops, real browsers, and real terminals. Not API wrappers pretending to be agents. You can spin up agent swarms for parallel execution, so instead of one agent processing supplier confirmations sequentially, you run ten simultaneously. There's a free tier to start, BYOK if you want to bring your own model keys, and a desktop app that doesn't require IT to stand up a whole infrastructure project. For supply chain teams that are serious about actually automating the work and not just buying another platform that promises to automate the work, the choice is pretty clear. Check it out at coasty.ai.
Here's my take, and I'm not softening it. If your supply chain team is still doing manual data entry at scale in 2026, that's a leadership decision, not a technology limitation. The tools exist. The benchmarks prove they work. The cost math is not complicated. $28,500 per employee per year in manual data entry costs, against a computer use agent that can handle the bulk of that work starting today. The companies that are going to win the next five years of supply chain chaos aren't the ones with the best visibility platforms. They're the ones where AI computer use agents are running overnight, processing supplier updates, flagging exceptions, and handing humans only the decisions that actually need a human. Everything else is just expensive habit. Stop paying for the habit. Start at coasty.ai.