(ProcessMiningGuru):
This "agent washing" problem is getting out of hand too. Half the vendors claiming to offer agentic AI are literally just rebranding their existing RPA bots with fancier names. We got burned by this - paid premium pricing for what was supposed to be an intelligent agent system and it turned out to be basic automation with some NLP bolted on. No real decision-making capability, no learning from outcomes, just marketing BS. Before you invest, demand to see the actual architecture and how it handles exceptions. Real agentic systems should adapt when conditions change, not just fail and send alerts. If they can't demo that convincingly, walk away. The technology's real but most of what's being sold right now isn't ready for enterprise deployment. Focus on understanding which problems actually need agentic versus what works fine with deterministic bots. Not everything needs AI and frankly most processes don't.
(AutomationArchitect_Sarah):
You're hitting on something real here and it's not just your company. We evaluated switching our Blue Prism setup to agentic and the cost projections were insane. What nobody talks about is that agentic systems need completely different data architecture. Your current ETL pipelines that work fine for RPA don't cut it because agents need context-aware data, not just structured inputs. We surveyed our data stack and realized we'd need to rebuild 60% of our infrastructure just to support proper agent deployment. The hidden cost there is massive and most orgs don't find out until they're knee-deep in migration. The other thing is governance - you can't use the same control frameworks. Traditional IT oversight doesn't account for systems that make independent decisions, so you're basically creating new risk management processes from scratch. Our CTO made the call to keep scaling our existing RPA for another 18 months and only pilot agentic in non-critical workflows. Boring decision but probably the right one financially.
Original Post (TechOps_Ryan):
So Gartner just dropped that bomb about 40% of agentic AI projects getting axed by end of 2027. Our company's pushing hard to move from traditional RPA to these new AI agents, and honestly I'm starting to sweat. We've got 200+ UiPath bots running pretty solid, but management thinks we need to "evolve" to stay competitive. The pilot we ran last quarter with an agentic system actually added more work to the process instead of streamlining it. Anyone else dealing with this? The sales pitch sounded amazing but the reality is we're spending twice the time babysitting these things compared to our old rule-based bots. I'm not anti-AI but feels like we're rushing into something that's not ready for production scale. What metrics are you guys using to actually decide if agentic makes sense versus just keeping your RPA stack?
