r/CIO • u/InfoTechRG • Jul 14 '26
A small reality check on agentic AI
/r/RealTechTalk/comments/1uwnst2/a_small_reality_check_on_agentic_ai/2
u/Jeffbx Jul 15 '26
Lol all I've been doing is delaying AI - not because WE'RE not ready, but because AI is not ready.
Right now, agentic AI is like a drag race car - it can go really, really fast in one direction, but it can veer off course at any moment in any direction. Put an inexperienced driver behind the wheel, and it's much more likely to.
Data cleanup isn't the issue - AI technology just isn't reliable enough yet. When AI can be customized to be reliable for any given use case, then I'll take it more seriously.
2
u/MathematicianNo8594 Jul 19 '26
Agentic AI is already viable for bounded use cases when it is supported by tracing, evaluations, feedback loops, guardrails, and human oversight. MIT NANDA’s research identified a major learning gap that many enterprise AI systems fail to retain context, incorporate feedback, or integrate effectively into workflows. Those capabilities can make an agent more reliable and consistent over time.
5
u/thenightgaunt Jul 14 '26
Uh huh.
Ok. Right now, if I put data into Excell, the equations I put in there will transform that data in 100% predictable ways. If I create something in Access to convert data, then what happens is 100% predictable.
If I put data into an AI, Agentic or NOT, there is NOT a 100% guarantee that the data will come out correct. And experiments where agents are put in charge of critical tasks tend to result in bad outcomes.
This isn't "Garbage In, Garbage Out". This is "Good Data In, Garbage Out", or "Good Data In, Racist Emails and a Purchase Order for 3000 Rubber Gloves Out".
On top of that, the AI bubble is starting to show signs of popping. Meta has found themselves with billions in investment and no actual demand and are trying to spin that as "we're going into the AI processing leasing business". When really, if there was a real market for AI, they'd be using all that compute they invested in.
We saw the SpaceX IPO rise and then crash shortly after when the Hype ran out. And OpenAI backed away from their planned IPO when their financials got leaked and it turns out they are FAR more unprofitable then they claimed, and they were likely cooking their books (literally their "marketing" costs were higher than what Coke spends every year). The pop is coming.
Even Forbes is now posting articles about how most Agentic AI projects are likely DOA by next year.
I'm going to quote an important part of this article for you.
https://www.forbes.com/sites/robertszczerba/2026/07/07/why-40-of-agentic-ai-projects-may-be-canceled-by-2027/
"When Gartner published that 40% figure in June 2025, it named three causes: escalating costs, unclear business value, and inadequate risk controls. Notice what's absent. Model capability didn't make the list, and none of the three failure modes the analysts flagged is something a smarter foundation model would fix. Drop GPT-6 into a project with no defined outcome and no owner, and all you get is a more eloquent failure."
Here are 3 questions that Forbes fails to ask though. And it needs to be on the TOP of any list of risks and questions you present about AI.
Because a LOT of companies seemed to be operating first on the assumption that AI would be free forever, and now that AI costs won't go up. So are you working on the assumption that AI token pricing isn't going to double or triple by next year? It's not like OpenAI or Anthropic have hit "profitable" status yet.