Welcome Avatar! If you’re a good operator, you’re not worried about AI. That has remained true the entire year. In fact, entry level people abusing AI are only making their lives worse. If the higher up recognizes that the majority of the product is just a query into ChatGPT/Gemini/Claude/Grok etc… why does he need to pay them anymore?
This reorganization of thought process is happening in real time. We’re moving from “AI will eat us all” to “Talented people take up even more of the pie”. Entry level roles are at risk of commoditization since they don’t generate visible revenue. Just because someone can make 10 financial models instead of 5 financial models in a day does not mean any additional profit was made.
In fact, it says we need less entry level people.
People are worried about a sudden cliff drop in jobs, instead, they should worry more about a slow moving downward socioeconomic trend.
The More Likely Scenario - Killing the Raise
Doomsday scenarios get the most clicks. The more likely case (a slow bleed) is what we’re watching. Instead of AI suddenly saying “you’re fired”, it’ll say “you can do more with less so no need to pay you as much”
Owner Perspective
Most struggle with this if they have never tried to start something of their own. The owner/manager is going to look at the numbers and calculate the replacement cost. If someone can churn out 2x as much work because of a computer program, it means that the nearest competitor is doing the exact same thing. There is nothing special about downloading Claude and asking it to do repetitive tasks.
The corporate guy at Coca Cola is not innovating. The guy at Pepsi is doing the same thing.
End result? They just proved that a computer can do their jobs.
Now for the tricky part. If the production doesn’t generate revenue (vast majority of white collar work does not), there is simply no reason to pay them more. Wages freeze up.
Wall Street Example
Say you had a basic team of one Managing Director, one Vice President, one Associate and two Analysts. They begin using AI and automating all the busy work like spreading comp sheets, DCF models and updating financial models from an SEC file.
Instead of needing 80 hour work weeks, suddenly they only need 20 hour work weeks. 75% of the busy work is gone.
The problem? It doesn’t create new clients.
The managing director only has a certain set of clients to go after. We’ll just make it up and say 100. The number is irrelevant. If he comes up with 10 pitches a year, the time to create all the content just dropped by 75%. Suddenly, you have a client problem not a creation problem.
Since AI doesn’t move the revenue line, the stress goes straight to the VP. The goal is to find any small deal. The hurdle rate just dropped. You can chase lower value clients because the cost of servicing them has gone down.
End result? MD gets paid, VP can get paid if they perform, Associate/Analysts get no increase in compensation. In addition, this means competition went up huge as the big companies can go after smaller fish if they like.
Can See the Writing on the Wall
From that simple example alone, the long-term impact should be crystal clear. If everyone uses the same stuff to automate the back end, there is no differentiation anymore. No need to pay people more money. The only person who should get paid more is the Managing Director/Director/VP or whoever brings in the $$$. If the person using AI quits, you just hire another person who can type words into Claude. Problem solved.
End Result:
Revenue generator gets even more profits because they can go after more clients (less wasted time waiting for information/decks etc.). (good side of K)
Middle layer needs to prove that they can gain trust from new clients/customers (decision time on upward or downward socioeconomic mobility)
Entry level, entirely commoditized unless the person is talented enough to generate revenue in the future (Hit the hardest)
Before the “what about” comes in
We recognize that this year will be fine for Wall Street in general. There were enough IPOs that the banks will pay out people based on fees. Just know that the long-term implication is what matters.
You don’t need hundreds of people to create pitch decks, pdfs, financial models etc. The number of seats can decline and pay doesn’t need to go up over the long-term.
In short, the output increases but the amount of people who can complete the same task goes up 10x.
Simple supply and demand. Grinding 100 hour weeks, using excel without a mouse and tabbing through 5-6 different items? No longer a skill. Just use Claude.
Repeatable process is commoditized for good.
How You’re Using AI Determines if You’re Digging Your Own Grave
The way we can explain this is simple. Are you using AI to generate more revenue or are you using it to save time?
We’re going to write that again. Are you using AI to generate more revenue or are you using it to save time?
If you are just using it to save more time, you’re making your life harder. What you are highlighting is that AI can do one of your tasks better than you can. Once the Company realizes this (and they will), the value of that specific task is going to zero.
Bad Work Model: You sign up for Claude. You begin using it to automate a bunch of the busy work. You stop. You spend the rest of your time relaxing and doing nothing with your free time to justify your salary.
Good Work Model: You sign up for Claude. You automate the busy work to free up time for revenue generation. Instead of embarrassing yourself with automated emails and content/summaries that are obviously done with AI, you spend that time on outreach. You find a way to get closer to customers/clients. You cold call more people. You go to more industry events to find changes in competitor products. You find product gaps to fill. So on and so forth.
Ideal Work Model: You sign up for Claude. You automate busy work and tell no one how you set it up (make it more seamless than your peers). You then increase your sales numbers by 5-10% and make sure you’re one of the top 20% in your class. You spend the rest of your time building a WiFi business and even set up some basic time for money exchange (consulting) because AI has made you incredibly efficient.
Autist Note: It’s laughable to claim that W-2 + WiFi money is impossible at this point, it was actually doable when Investment Banking had much longer hours than it has now. No excuse to rely on just a W-2 in 2026.
Don’t Suffer From AI Delusion
If you’re seeing record profits from automation, do not assume that any of this will go to employees. If anything, less of it will go to employees since they are being commoditized. Using AI to free up time that is spent doing nothing productive = justifying a pay cut vs. a pay raise.
This leaves you with two simple options.
Option 1: If you love the W-2 life, your entire mantra is “get close to customer”. Businesses do not like turnover. If you’re in charge of 20 accounts and all those accounts pay the firm large sums of money, they do not have any interest in rocking the boat. If you become extremely expensive they may look, however, it’ll be years until they really care since profits should be upward moving as operational costs decline (no need for hoards of junior workers anymore)
Option 2: The preferred option around these parts. Instead of suffering from existential dread, you now have tons of time to spin up multiple wifi businesses if you like. In fact, you can even do a boring services based business tied to what you already do. Since you’re no longer working long hours (busy work is gone) it means that you can do both 1) a time for money exchange for fun and 2) you can start testing demand for various business ideas.
Example Idea
Since every single white collar worker is tied to a screen and knows how to use AI tools, you won’t be adding much value by trying to target them with your streamline/automation knowledge.
Instead you’d want to go in reverse. Since AI/Robotics is not going to touch the blue collar industry any time soon, they are the ideal candidate for AI help.
What you’re looking for is: 1) someone young, 2) someone who does good work and 3) someone with a thinner initial client list. Basically you want a go-getter who doesn’t have the time to do all the repetitive tech stuff.
Basic Example: Say you find a 25 year old who is extremely good at painting homes. The quality of the work is great, he has a slim number of customers serviced and he doesn’t have the time to constantly build a profile: reviews, new quotes, etc.
You enter the picture and offer to do this with a slice of each client won. Unless a new person is brought into the mix, you get nothing. If you bring someone in? You get paid without doing any of the painting work (not your niche).
Why This Works: In this simple situation you are shifting the way you’re using AI. You’re not using AI to produce more financial models that’ll be thrown into the trash bin within a week. Instead, you are using AI to help you build an online profile for someone who lives primarily in the blue collar world. The blue collar world is not benefitting from AI since it doesn’t unscrew a light bulb or paint a wall.
Hilariously, this is eerily similar to something we predicted back in 2021 “Marketing is the new software engineering”
Now that anyone can make basic programs, the value has drastically shifted to getting customers in the first place since everything looks incredibly commoditized. Summaries, numbers into spread sheets, power point, pdfs… all can be done by a standard high school student
Decide Which Side of the K You Want to Be On
Directionally, we’re already seeing this today.
People who are using AI to do tasks that generate no revenue? Existential dread.
People who are using AI to generate revenue? Extreme results in 2026.
We gave an extremely clear example of both: 1) making more financial models = dread, 2) using AI to respond faster to customers, get more customers and build your presence faster = extreme results.
Smaller Set of People: From what we’re seeing, there is a huge swarm of people doing option number one. They try to create and edit content using Claude/ChatGPT (every single smart operator sees it and deletes it). And. There is a smaller subset that takes the AI and streamlines its process (where the money is)
If AI can do your work without anyone noticing? You won’t be getting a pay bump any time soon. Even if you can produce 100x as much in 1/10th of the time.
Summary
Just because people are becoming more productive does not mean that revenue follows. We’re finally seeing the market reach that conclusion at the end of the year. Unless there is a direct tie to revenue, it is largely a cost saving mechanism for large over-staffed Fortune 500 comapnies.
Instead of spending your time automating yourself out of a pay raise, take the same tool and ask “who doesn’t have time to use this?” That’s the current market opportunity if you don’t know where to start.
Disclaimer: None of this is to be deemed legal or financial advice of any kind. These are *opinions* written by an anonymous group of Ex-Wall Street Tech Bankers and software engineers who moved into affiliate marketing and e-commerce.
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