Might as well just stop using AI agents that that point.

I don’t work at Accenture, but at a group that had a similar journey from adoption to scaling back to only the included tokens and I would say that is precisely the idea: giving up on ‘Agentic’ use of AI, but still have enough for some acceleration.

From what I gather, in our group the findings were:

• Obviously, it was costing a heavy chunk of change and then even more expensive when rates were hiked
• There was no good way for them to even know what productive end the spend went toward, they know which employee expended a bunch of tokens, but no idea what they would have used it on
• Despite a crank of volume of stuff, they weren’t seeing any business value of the stuff. Requests still took about the same time to fulfill, etc
• The most eager AI producers got ahead of their skis, and their stuff was useless because nothing and no one could reliably fix/tweak it after a certain point.
• All the scary ‘AI will ruin IT security’ that the AI companies themselves have been expressing likely didn’t help either.
• Perhaps the most uncomfartable of all, they found out that however good or bad an AI project turns out to be, management can’t tell the diference until it is too late. Being able to ‘manage’ the content has always been flawed, but the AI dials it up to eleven by ‘looking’ just right as a demo to someone that understands neither the customer nor the process of creating the work, but blows up in their faces in delivery. Kind of like how so many technology article writers breathlessly talked about the photoshop clone, despite many of them never having touched the relevant software, then heavy users reporting that it is actually shit, but the people writing about it have no context to know, but felt compelled to talk about it anyway. Those are management in the fields using AI.