It’s a pretty low bar they have to get over. And hey, they might be even better since the AI would feel the pain of their failures instead of getting a golden parachute.
I mean c-suite jobs (particularly CEO), are usually primarily about information coordination and decision-making (company steering). That’s exactly what AI has been designed to do for decades (make decisions based on inputs and rulesets). The recent advancements mean they can train off real CEO decisions. The meetings and negotiation part of being a c-suite (the human-facing stuff) might be the hardest part of the job for AI to replicate.
I don’t have a real clear idea what every one of the C suite people do exactly.
But CIOs seem to set IT strategy and goals in the companies I’ve worked. Broad technology related decisions such as moving to cloud. So, basically, reading magazines and putting the latest trend in action (/s?). Generative AI could easily replace some of the worst CIOs I’ve encountered lol.
CEOs seem to make speeches about the company, enact directions of the board, testify before Congress in some cases, make deals with VC investors, set overall business strategy. I don’t really see how generative AI takes this job.
All C suite positions are managing people and projects planning. They set initiatives and metrics to measure success for those initiatives
A CEO gives an overall direction for the company and gives the other ELT members their objectives, such as giving the CFO a goal of limiting spending or a CIO to build a user capacity within a specific budget and with X uptime.
In this age of titles over responsibility, a C suite position can cover very specific things, like Chief Creative Officer or Chief Customer Officer, so a comprehensive list is difficult. But the key thing is that almost all white collar jobs that look like a pyramid, with the decisions starting at the top that turns into work as it makes it’s way down the pyramid.
The senior VPs and directors under those C levels then come up with a plan for reaching those objectives and relay that plan to the C level for coordination and setting expense expectations. There is a series of adjustments or an approval which then starts the project. Project scope determines how long it will take and how much it will take using a set amount of bodies to work the project.
Hopefully this helps explain how C levels interface with the rest of the company.
It probably could. The trouble is getting training data for it. If you get that and one company becomes wildly successful off it, stockholders will demand everyone do it.
Not sure, those require less talking to machines and more talking to humans. I think jobs talking the most to machines should be easier to automate first in the future, because they obey to logic. LLM doesn’t follow that idea, but that’s just the latest mediatic model, there are many other algorithms better at rational tasks.
Well, there’s one good thing that will come out of this: these kinds of idiotic moves will help us figure out which companies have the right kinds of management at the top, and which ones don’t have any clue whatsoever.
Of course, it will come with the working class bearing the brunt of their bad decisions, but that has always been the case unfortunately. Business as usual…
It’s not going to be a convenient excuse. There are swaths of C-Suites who genuinely believe they can replace their workforce with ai.
They’re not correct but that won’t stop them from trying.
The irony is that AI will probably be able to do the jobs of the c-suite before a lot of the jobs down the ladder.
It’s a pretty low bar they have to get over. And hey, they might be even better since the AI would feel the pain of their failures instead of getting a golden parachute.
Need more news articles pitching this idea to shareholders.
I mean c-suite jobs (particularly CEO), are usually primarily about information coordination and decision-making (company steering). That’s exactly what AI has been designed to do for decades (make decisions based on inputs and rulesets). The recent advancements mean they can train off real CEO decisions. The meetings and negotiation part of being a c-suite (the human-facing stuff) might be the hardest part of the job for AI to replicate.
How do you figure that?
I don’t have a real clear idea what every one of the C suite people do exactly.
But CIOs seem to set IT strategy and goals in the companies I’ve worked. Broad technology related decisions such as moving to cloud. So, basically, reading magazines and putting the latest trend in action (/s?). Generative AI could easily replace some of the worst CIOs I’ve encountered lol.
CEOs seem to make speeches about the company, enact directions of the board, testify before Congress in some cases, make deals with VC investors, set overall business strategy. I don’t really see how generative AI takes this job.
CFO? COO? No fucking clue what they do.
Curious what others think.
All C suite positions are managing people and projects planning. They set initiatives and metrics to measure success for those initiatives
A CEO gives an overall direction for the company and gives the other ELT members their objectives, such as giving the CFO a goal of limiting spending or a CIO to build a user capacity within a specific budget and with X uptime.
In this age of titles over responsibility, a C suite position can cover very specific things, like Chief Creative Officer or Chief Customer Officer, so a comprehensive list is difficult. But the key thing is that almost all white collar jobs that look like a pyramid, with the decisions starting at the top that turns into work as it makes it’s way down the pyramid.
The senior VPs and directors under those C levels then come up with a plan for reaching those objectives and relay that plan to the C level for coordination and setting expense expectations. There is a series of adjustments or an approval which then starts the project. Project scope determines how long it will take and how much it will take using a set amount of bodies to work the project.
Hopefully this helps explain how C levels interface with the rest of the company.
It probably could. The trouble is getting training data for it. If you get that and one company becomes wildly successful off it, stockholders will demand everyone do it.
Not sure, those require less talking to machines and more talking to humans. I think jobs talking the most to machines should be easier to automate first in the future, because they obey to logic. LLM doesn’t follow that idea, but that’s just the latest mediatic model, there are many other algorithms better at rational tasks.
Well, there’s one good thing that will come out of this: these kinds of idiotic moves will help us figure out which companies have the right kinds of management at the top, and which ones don’t have any clue whatsoever.
Of course, it will come with the working class bearing the brunt of their bad decisions, but that has always been the case unfortunately. Business as usual…
That’s not something to be figured out once, it’s a perpetual process.
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