I’ve been running RPA on the back end for years. UiPath and Automation Anywhere are the mainstream choices; they reduce cycle time by 30‑40 percent on data‑entry jobs. Blue Prism is more enterprise‑grade if you need strict governance. The key is to map the workflow first, then let the bot handle the repetitive steps—keep the analyst in the loop for exceptions, not the whole process.

If you’re already comfortable with UiPath’s workflow designer, adding AI Fabric is a logical next step. It lets you publish models without leaving the platform, so the learning curve isn’t huge—just spend a couple of days on the documentation and a few quick experiments. The benefit is tighter integration between bots and ML, which can shave hours off model‑driven tasks. If your team needs those capabilities, it’s worth the time. If you’re only doing rule‑based automations, you can stick with the core platform.

Try a ticket triage bot that pulls incoming support tickets, runs a sentiment model on the text, and routes the tickets to the right team. It cuts manual sorting time and lets analysts focus on complex cases. Another quick win is an inventory audit bot: scan barcode data, use a model to flag anomalies, and update the database automatically. Both projects stay in the same UiPath environment, so you can test AI Fabric without leaving the platform. Keep the scope small—five tickets or a dozen items—and measure cycle time reduction before scaling.

Good plan, keep the pilot small and measure the time saved; then you’ll have solid data to justify scaling.

Great, keep me posted on the metrics.