Is that the right question? I suspect in many types of work, it doesn’t matter.
In many cases of augmentation, there’s no motivation or structure to do better. Case in point is how consulting firms operate. They are essentially LLMs with young staffers running around like bumble bees exchanging “best practices,” and packaging them beautifully. However, Parkinson’s Law kicks in to fill in the scheduled time. In a time and materials environment, there are no gains. A version of that happens in Agile development too. (It’s the “competence trap.”)
In this scenario, some might be able to scale a new business and pressure the industry norms. In my experiences, it’s niche. Clients either don’t want answers that fast, or can’t absorb it anyways. The proof is in the pudding that consulting fees continue rising.
I love the idea of SCAN-PLAN-ACT but it’s missing a nuance. I have a version that is DESIGN-ALIGN-ENACT. There are four types of DESIGN problems… puzzles, routine, wicked, enigmatic. For puzzles and routine problems , you can scan for answers. Even in those scenarios, it’s not easy. For those who can solve wicked and enigmatic problems, winner take all! Then there’s no good technology to align. It’s why those “smart” best practice consultancies are not very good at implementing changes.
Nice breakdown. But the title is off. It presumes absolute salary is mainly a function of skill premium. Under stable conditions, that may be true. But not under conditions of innovation. As productivity rises rapidly, purchasing power must rise, either through falling prices or increased salaries.
Not to everyone all at once. There can be short term losers, and that’s what your analysis focuses on.
But these effects don’t last long. Certainly the advent of tractors upset some farmers for a short time. But the crazy gains in productivity quickly eclipsed any dislocations.
Whether displaced developers move up or down the skill chain, they’re gonna be richer. Probably some blacksmiths became other types of craftsmen, but even assembly line workers were much richer than their blacksmith fathers.
Yes, AI empowers low-skilled workers, but also the degree of specialization increases over time: today, highly skilled workers aren't wielding axes anymore but working on ASML lithography machines or developing new ML architectures beyond transformers at some AI startup – highly specialized tasks that very few people in the world can do, and they can charge for it a huge premium
Interesting perspective. I believe the use of AI (and now generative AI) is a great vector for automation and simplification of the interactions with the end user (aka. the consumer).
In traditional enterprises, such automation will only happen in the areas where the process (succession of task to accomplish a goal) has been clearly defined, which is usually not the case.
This is early because many steps of a given process (procure to pay, order to cash etc...) require some judgment calls. taking the context of the decision into consideration, context that is too difficult to digitalise to automate the entire step.
For example: granting a multi millions dollars loan to an individual or a corporation is unlikely to be fully automated. Buying a property might not be fully automated anytime soon, even if AI powered agents could automate all steps. Regulations (anti money laundry etc...) will step in, preventing such end-to-end automation.
I believe we will reach an "AI frontier" when the tasks are "too sophisticated to be automated". Such frontier might just be the limits of digitalisation: taking a cab, ordering online, automating a 10 days trips will all reservations have been possible for years already, removing the need of any intermediary, outside platform fees that might fund the various entities behind each AI agent in some innovative business model.
As more sophisticated services become available, we continue to move up the "automation limit" , with a K shape result (I believe you mention it in you platform article): below the automation limit, people don't get any negotiation power and above the "automation limit" people get negotiation power as long as they keep moving up faster that the automation limit.
One additional thought that I had while reading your article is that in some industries we actually don’t have an honest conversation or even a clear idea what we are charging for and why – independent of AI.
I’d argue that in many fields – let’s say creative industry or consulting – the actual work output is already much more commoditized than we pretend, and what is mainly being monetized is access/ network/ brand etc. With AI driving down the cost of doing a lot of the actual work, what is becoming relatively more important is precisely this other vague bundle of “access, network, brand” etc. So I can see a world where McKinsey’s margins are actually becoming even thicker, because for some reasons corporates still want to have that brand, but McKinsey’s cost structure is going down.
Is that the right question? I suspect in many types of work, it doesn’t matter.
In many cases of augmentation, there’s no motivation or structure to do better. Case in point is how consulting firms operate. They are essentially LLMs with young staffers running around like bumble bees exchanging “best practices,” and packaging them beautifully. However, Parkinson’s Law kicks in to fill in the scheduled time. In a time and materials environment, there are no gains. A version of that happens in Agile development too. (It’s the “competence trap.”)
In this scenario, some might be able to scale a new business and pressure the industry norms. In my experiences, it’s niche. Clients either don’t want answers that fast, or can’t absorb it anyways. The proof is in the pudding that consulting fees continue rising.
I love the idea of SCAN-PLAN-ACT but it’s missing a nuance. I have a version that is DESIGN-ALIGN-ENACT. There are four types of DESIGN problems… puzzles, routine, wicked, enigmatic. For puzzles and routine problems , you can scan for answers. Even in those scenarios, it’s not easy. For those who can solve wicked and enigmatic problems, winner take all! Then there’s no good technology to align. It’s why those “smart” best practice consultancies are not very good at implementing changes.
Nice breakdown. But the title is off. It presumes absolute salary is mainly a function of skill premium. Under stable conditions, that may be true. But not under conditions of innovation. As productivity rises rapidly, purchasing power must rise, either through falling prices or increased salaries.
Not to everyone all at once. There can be short term losers, and that’s what your analysis focuses on.
But these effects don’t last long. Certainly the advent of tractors upset some farmers for a short time. But the crazy gains in productivity quickly eclipsed any dislocations.
Whether displaced developers move up or down the skill chain, they’re gonna be richer. Probably some blacksmiths became other types of craftsmen, but even assembly line workers were much richer than their blacksmith fathers.
Superb !!!!
Yes, AI empowers low-skilled workers, but also the degree of specialization increases over time: today, highly skilled workers aren't wielding axes anymore but working on ASML lithography machines or developing new ML architectures beyond transformers at some AI startup – highly specialized tasks that very few people in the world can do, and they can charge for it a huge premium
This is brilliant. Such a well-constructed inquiry into the specifics of what's really going on beyond the knee-jerk reaction of Skynet. Bravo!
Interesting perspective. I believe the use of AI (and now generative AI) is a great vector for automation and simplification of the interactions with the end user (aka. the consumer).
In traditional enterprises, such automation will only happen in the areas where the process (succession of task to accomplish a goal) has been clearly defined, which is usually not the case.
This is early because many steps of a given process (procure to pay, order to cash etc...) require some judgment calls. taking the context of the decision into consideration, context that is too difficult to digitalise to automate the entire step.
For example: granting a multi millions dollars loan to an individual or a corporation is unlikely to be fully automated. Buying a property might not be fully automated anytime soon, even if AI powered agents could automate all steps. Regulations (anti money laundry etc...) will step in, preventing such end-to-end automation.
I believe we will reach an "AI frontier" when the tasks are "too sophisticated to be automated". Such frontier might just be the limits of digitalisation: taking a cab, ordering online, automating a 10 days trips will all reservations have been possible for years already, removing the need of any intermediary, outside platform fees that might fund the various entities behind each AI agent in some innovative business model.
As more sophisticated services become available, we continue to move up the "automation limit" , with a K shape result (I believe you mention it in you platform article): below the automation limit, people don't get any negotiation power and above the "automation limit" people get negotiation power as long as they keep moving up faster that the automation limit.
Very interesting article!
One additional thought that I had while reading your article is that in some industries we actually don’t have an honest conversation or even a clear idea what we are charging for and why – independent of AI.
I’d argue that in many fields – let’s say creative industry or consulting – the actual work output is already much more commoditized than we pretend, and what is mainly being monetized is access/ network/ brand etc. With AI driving down the cost of doing a lot of the actual work, what is becoming relatively more important is precisely this other vague bundle of “access, network, brand” etc. So I can see a world where McKinsey’s margins are actually becoming even thicker, because for some reasons corporates still want to have that brand, but McKinsey’s cost structure is going down.
Thanks for the read!
ok, but under the right set of circumstances, which you control, ai can also feed you a job