• Lots of people aren't aware of what the models can do.
• They also aren't paying attention, and getting their attention is hard.
• Their impression of AI was formed by cheap low quality AI like free ChatGPT as of two years ago, Google AI overviews or Microsoft Copilot. So they think it sucks.
• A LOT of executives got burned by early pilots that overpromised then failed. Enterprise IT is a wasteland of dead AI pilots.
• Their IT systems are difficult to connect to models because they lack proper APIs or auth systems. Note the huge emphasis on fast computer use in the Astra announcement. A lot of work can only be done by clicking things.
• Executives don't want to let employees go, but aren't sure they can find new work for them either.
The last point is worth dwelling on. HN is full of socialists who imagine corporate executives as cigar smoking top hat wearers who chuckle all the way to the bank. The reality is more mundane: most executives don't want to lay people off and will fight hard to avoid doing so.
The average person in a position to make an AI project work either isn't incentivized with stock - this is often the case outside the US even for quite high ranking execs - or they are but don't believe laying people off will raise the share price enough to be worth the pain.
Also, executives often measure their success and self-worth by how many people report to them. Laying off half their department, even if it gets them a monetary bonus, would lead directly to a loss of social status as they can no longer say they manage 1,000 people but only 200, which matters if their social circle are all managers too (and for their wives, girlfriends, etc).
Layoffs suck and people HATE doing them, which is why companies often resort to forced percentage based layoffs to get managers to do it. If the incentives aren't there, the average executive will just sit on obvious AI deployment opportunities and/or deliberately sabotage them because getting rid of people is just all downside for them with no upside.
So institutions have enormous inertia. Model capabilities will run far ahead of what is actually used in reality, and this will continue for decades. It does mean that startups have a better chance than ever of outcompeting much larger incumbents though, as not hiring is far easier than firing.