We Should Replace CEOs With AI – planetearthandbeyond.co
The big promise of AI is that it will decouple productivity from labour, enabling rapid, infinite growth. Let’s gloss over the fact that infinite growth within a finite system is literally the definition of cancer. AI is not meeting this promise. Study after study has shown that it is too inaccurate to augment jobs, let alone replace them (read more here). They also show that, in the vast majority of cases, AI is way too expensive to have a positive effect on the bottom line (read more here). What’s worse, more and more research is suggesting that, even with the trillions of dollars being poured into AI development, they aren’t going to get much better than they currently are (read more here). Thanks to diminishing returns, AI is about as good as it will ever be. But what if I told you this is only because we have approached AI the wrong way? AI can massively disrupt the labour market, massively boost productivity, improve workers’ lives, and make a killing while doing so. It just can’t do this from the bottom-up, as we have been trying to do. But it can be done from a top-down approach, and in fact, it makes a whole lot of sense. This is why we should replace CEOs with AI.
AI hallucinates (or more accurately, gets things wrong) constantly. In fact, OpenAI’s latest research paper found that there is no viable way to reduce the current model’s rate of hallucination (read more here). This severely limits what tasks/jobs AI can automate. Basically, it needs to be a task/job where accuracy is not important. But you still need expert human oversight of this output to catch, correct and mitigate these mistakes. Ideally, this oversight will be inherent in the structure around the task/job; that way, oversight will not have to be an additional hired position.
Even when a task/job meets these requirements, there is a “cost floor.” AI models are extremely expensive to run, let alone build and develop. There is a reason OpenAI and its cohorts are light-years away from profitability. As such, for AI suppliers to be sustainable, and the companies using AI to automate jobs, to generate a return from their AI use, the most expensive tasks/jobs should be the ones automated first. This gives the best chance of the massive cost of AI deployment being less than the money it saves, ensuring the AI supplier and user aren’t experiencing a net loss.
So, AI can automate extremely well-paid jobs that don’t depend on accuracy and that involve inherent human oversight.
Notice how that is the total opposite of how AI is currently being deployed? From report writing to bookkeeping and data entry, and even coding, AI is being used to replace relatively low-paid jobs that depend entirely on accuracy and have very little inherent human oversight. This is a total arse-about-face way to deploy AI.
Okay, so do we know of a job that doesn’t depend on accuracy, has inherent human oversight and is extremely well paid? Yes, we do. CEO.
The average US CEO pay in 2024 was $22.98 million. That makes them the highest-paid ‘job’ around. In 2024, the average US CEO earned 281 times the average worker beneath them. Almost all S&P 500 companies cluster around this ratio, but some outliers pay their CEOs significantly more. For example, Starbucks’ CEO made 6,666 times more than the average Starbucks worker in 2024.
On a totally separate note: Join a union.
As such, automating just the single job of CEO can save most companies as much, if not more, than automating their entire low-paid admin staff. Take S&P 500 company Welltower. Its CEO earned $17,199,891 in 2023, while its 533 employees earned, on average, roughly $100,000. So if Welltower automated its CEO position, it would save as much as automating a third of its workforce! And, Welltower is not an outlier here.
What’s more, automating a single roll with a single AI is far easier and cheaper to deploy, as well as far easier and cheaper to manage, than automating hundreds or thousands of different interconnecting jobs with AI.
In terms of the economics and practicality of deploying AI automation, the CEO position makes the most sense.
Okay, but surely the job of CEO needs 100% accuracy, right? They are literally running the ship. Well, truth be told, the public perception of what a CEO does and what a CEO actually does are miles apart. They aren’t this all-important captain, but more a busybody, and we have data to back that up. And guess what, busybodies don’t need to be accurate.
Okay, so what data supports this?
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source
This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
AI hallucinates (or more accurately, gets things wrong) constantly. In fact, OpenAI’s latest research paper found that there is no viable way to reduce the current model’s rate of hallucination (read more here). This severely limits what tasks/jobs AI can automate. Basically, it needs to be a task/job where accuracy is not important. But you still need expert human oversight of this output to catch, correct and mitigate these mistakes. Ideally, this oversight will be inherent in the structure around the task/job; that way, oversight will not have to be an additional hired position.
Even when a task/job meets these requirements, there is a “cost floor.” AI models are extremely expensive to run, let alone build and develop. There is a reason OpenAI and its cohorts are light-years away from profitability. As such, for AI suppliers to be sustainable, and the companies using AI to automate jobs, to generate a return from their AI use, the most expensive tasks/jobs should be the ones automated first. This gives the best chance of the massive cost of AI deployment being less than the money it saves, ensuring the AI supplier and user aren’t experiencing a net loss.
So, AI can automate extremely well-paid jobs that don’t depend on accuracy and that involve inherent human oversight.
Notice how that is the total opposite of how AI is currently being deployed? From report writing to bookkeeping and data entry, and even coding, AI is being used to replace relatively low-paid jobs that depend entirely on accuracy and have very little inherent human oversight. This is a total arse-about-face way to deploy AI.
Okay, so do we know of a job that doesn’t depend on accuracy, has inherent human oversight and is extremely well paid? Yes, we do. CEO.
The average US CEO pay in 2024 was $22.98 million. That makes them the highest-paid ‘job’ around. In 2024, the average US CEO earned 281 times the average worker beneath them. Almost all S&P 500 companies cluster around this ratio, but some outliers pay their CEOs significantly more. For example, Starbucks’ CEO made 6,666 times more than the average Starbucks worker in 2024.
On a totally separate note: Join a union.
As such, automating just the single job of CEO can save most companies as much, if not more, than automating their entire low-paid admin staff. Take S&P 500 company Welltower. Its CEO earned $17,199,891 in 2023, while its 533 employees earned, on average, roughly $100,000. So if Welltower automated its CEO position, it would save as much as automating a third of its workforce! And, Welltower is not an outlier here.
What’s more, automating a single roll with a single AI is far easier and cheaper to deploy, as well as far easier and cheaper to manage, than automating hundreds or thousands of different interconnecting jobs with AI.
In terms of the economics and practicality of deploying AI automation, the CEO position makes the most sense.
Okay, but surely the job of CEO needs 100% accuracy, right? They are literally running the ship. Well, truth be told, the public perception of what a CEO does and what a CEO actually does are miles apart. They aren’t this all-important captain, but more a busybody, and we have data to back that up. And guess what, busybodies don’t need to be accurate.
Okay, so what data supports this?
Subscribe to Will Lockett’s Newsletter to keep reading this post and get 7 days of free access to the full post archives.
source
This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
