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The other way to look at it is that the entire consulting industry is teetering on catastrophe. And IBM, being largely a consulting company now, is not being spared.




IBM isn't failing, though. They're a profitable company with healthy margins, and enterprises continue to hire them for all sorts of things, in large numbers.

So now it makes more sense why they think the AI spending will/need to fail.

Because if it didn't, that's a direct replacement of them.


AI replaces nothing. A consultant or developer is not replaced with AI, he becomes more powerful with AI. An IBM consultant with AI is still way ahead of Johnny Startup with AI.

> The other way to look at it is that the entire consulting industry is teetering on catastrophe

Oh? Where'd you get that information?

If you mean because of AI, it doesn't seem to apply much to IBM. They are probably not great at what they do like most such companies, but they are respectable and can take the blame if something goes wrong. AI doesn't have these properties.


If anything there’s likely plenty of work for body shops like IBM in reviewing and correcting AI-generated work product that has been thrown into production recently.

This is a separate argument though. A failing company may still be right in identifying other companies failure modes.

You can be prescient about failure in one area and still fail yourself. There's no gotcha.


IBM is not a failing company though, they are a Goliath in the Enterprise space.

Still besides the point. The company failing or not is orthogonal to them being able to identify failure in others.

> A failing company may still be right in identifying other companies failure modes.

Agreed if this is what they are doing, but what if theyre spewing claims to try and discredit an industry in order to quell their shareholder concerns?


They are not the only ones looking at the money spent in AI datacentres and concluding most of the investment will not be recovered anytime soon.

A lot of the silicon being deployed is great for training, but inefficient for inference and the training to inference ratio for usage shows a clear tendency to go the inference way. Furthermore, that silicon, with the workloads it runs, doesn’t last long and needs replacement.

The first ones to go online might recover the investment, but the followers better have a plan to pivot to other uses.


IBM was making "calculating cheese cutters" back in the day [0].

I'm sure they can pivot to something else if the need arises.

[0]: https://imgur.com/a/ibm-cheese-cutter-Rjs2I


The whole point of a consultant is to let the execs blame someone else.

Nobody got fired for buying something Gartner recommended, or for following EY's advice to lay off/hire

I don't see AI taking that blame away.


They own Red Hat Linux, Ansible, OpenShift, and Terraform.

If you are doing anything in the Enterprise space, they probably have their claws in you be it on-prem or cloud.

And their work on quantum...

https://www.forbes.com/sites/baldwin/2025/11/25/inside-ibms-...

Not to mention they are still doing quite a bit of Mainframe...




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