The purpose of hiring them is to make them come to the conclusion you already have, so when it goes well you get the credit for doing it, or if it goes sideways you can pin the blame on them.
Most companies are not _just_ tech companies and don't have business analysts, consulting analysts, solutions consultants, software engineers and DBA's on staff.
Many, many, many companies are very happy with the consulting firms they hire.
Of course, those are the consulting firms that aren't publicly traded and in the news all the time (for all the wrong reasons).
Having done some work with these F500 companies, this is part of it. These legacy companies have long seen tech as a cost center, haven't invested in it, and are unable to attract talent. And, for whatever reason, these companies insist on working with large consulting firms, when a dedicated software or tech consulting firm that is smaller would be way better.
Ultimately, why would a large company hire a consultancy company that is bad at tech and has a lot of bad processes to do their tech for them? Because the company itself is even worse and doesn't know what good looks like. If you are hiring McKinsey or Deloitte to do your tech, it's because you are completely lost and don't have the slightest clue how to become unlost. And you have no concept of what good looks like.
If you think the actual tech talent and systems are bad, when you work with these consulting firms, they are going to do the most heavy SAFe process you have ever seen. For me, the worst part is not the tech talent, but rather the most by-the-book, heavy-handed agile process possible. Everything moves way slower because of this "agile" rot, and there is almost no concept of doing proper ideation and prototyping work.
These legacy F500 companies try to do everything cheaply with consultants and offshoring, and yet it always ends up costing way more than it would if they just had proper in-house tech talent.
They look to package up something and sell it as long as they can.
AI solutions won't have enough of a shelf life, and the thought around AI is evolving too quickly.
Very happy to be wrong and learn from any information folks have otherwise.