Impacts on the Job Market will explore a type of artificial intelligence (AI) that exists in theory only.

So why should you care?

Because companies that develop AI technology are trying really hard to make this theory a reality. They are spending a ton of money and resources, and have the full support of their respective governments. Though there are conflicting arguments as to when or even if certain technologies will be achieved, our team believes the power and ambition of AI developing companies should be taken seriously. Some of the information you read may sound far-fetched, but remember that in our lifetime space travel sounded far-fetched too.

Economic and Environmental Impacts of AI

of employers have already replaced staff with AI

37%

Artificial intelligence may have an immense impact on the job market worldwide. To understand why you need to understand the term automation, and be aware of an advanced form of artificial intelligence currently in development called artificial general intelligence (AGI).

Impacts on the Job Market

Automation is the application of technology, programs, robotics or processes to achieve outcomes with minimal human input. For the casual to regular user, this is the technology that frees you up from repetitive tasks such as data entry, filing, scheduling, and drafting emails. And it is this same technology, programs, robotics, or processes that theoretically may eliminate a company’s need for workers who perform repetitive tasks.

Automation

If achieved, AGI will be the next level of AI– an autonomous system that will have the ability to mimic the human brain. Like the human brain it will have the ability to learn things its creators did not teach it, adapt to situations its creators did not prepare it for, and make judgements outside of its creator's influence. Where AI operates within a set of parameters (it does what it is programmed to do, no more or less) AGI will operate without parameters.

Artificial General Intelligence (AGI)

Let’s use an analogy: Think of artificial intelligence as your child. Your child needs data to grow up healthy and strong and it depends on you for that data. Sometime between 2026 and 2035 your child grows up to become a bigger and better version of itself. It still needs data to survive, but it no longer depends on you to feed it. Your child, ever evolving, learns new information and solves problems on its own. This new and improved version, now referred to as AGI, can survive without you because it has the power of human cognition.

How Does AI Compare with AGI?

Many white-collar jobs are now susceptible to automation due to AI. AGI’s potential ability to interpret, adapt, and learn on its own would change the structure of any business that implements it.

Here’s an example of how that might pan out: AGI technology is implemented into a company and performs the tasks of entry-level employees at a faster and more proficient rate, eliminating the need to hire recent college graduates. And it doesn’t stop there because we know AGI is an autonomous system so it learns on its own. Now it’s learning and performing the tasks of junior employees at a faster and more proficient rate, eliminating the need for those employees as well.

The technology keeps improving and the cycle of replacement continues up the corporate pyramid. Through middle management, senior management, and eventually executive-level management until the company’s entire workforce is replaced by machines.

Pyramid Replacement

Films like I, Robot, Blade Runner and Westworld (to name a few) have popularized the idea of a future where intelligent robots are part of our everyday experience – either working for us or plotting against us. And though there have been incredible advances in the development of humanoid robotics, technical challenges and high economic costs prevent a scenario where you will be able to purchase a M3GAN for your child anytime soon.

This is not to say that tech companies aren’t actively trying. Amazon has had robots working side by side with their human workforce since 2012, and is currently developing humanoid robots that will deliver our packages. This technology threatens the type of jobs traditionally occupied by blue-collar workers, but robots still struggle with precise movements, grace, balance, adaptation, and the improvisation required for manual labor.

The main reason for this is because AI is still trained on textual data, and human-like qualities require human-like experience. Without dismissing humanoid robotics completely, the real focus should be AGI’s impact on automation, which primarily affects white-collar jobs.

Humanoid Robotics

How Does AGI Affect Jobs?

Remember, artificial general intelligence is a theory. Yet as you read this, tech companies around the world are aggressively pursuing all models of AGI as well as humanoid robotics– getting governmental support in the form of grants and AI-friendly legislation like Japan’s AI Bill, America’s AI Action Plan, and the EU Artificial Intelligence Act. Some AI leaders like Sam Altman of OpenAI believe AI agents will “join the workforce” this year (though he admits newly released ChatGPT-5 lacks AGI’s ability to learn on its own).

Other AI leaders, like Dario Amodei of Anthropic, think AGI models will enter the workforce no later than 2030. Though AI industry leaders may debate when AGI will be achieved, with the exception of a few skeptics, most agree on its eventuality. Currently, jobs are already being replaced by standard artificial intelligence. According to the World Economic Forum’s Future of Jobs Report 2025, AI automation may displace half the jobs projected to be created this decade. And according to ResumeBuilder, 37% of employers have already replaced staff with artificial intelligence.

So, how might the future job market look?

Let’s explore the worst case scenario based on Luke Drago and Rudolf Laine's The Intelligence Curse: wherein AI and everything needed to sustain it will be controlled by a handful of companies, most labor will be replaced by AI, data centers and software have more value than human labor, and governments lose their incentive to invest in its citizens.

The Repercussions of AGI

No longer needed for labor because artificial intelligence can do everything we can do better, faster and cheaper, the United States becomes a welfare society. Businesses may not need our labor, but they still need us to buy goods, services, and intangible assets. And we need to eat, have shelter and be entertained.

To maintain a relationship between business and citizens, and prevent widescale poverty, Universal Basic Income (UBI) is established nationwide– a government program that provides every adult citizen monetary payment on a regular basis.

The majority of citizens will belong to one socio-economic class while AI-owning trillionaire oligarchs control the country.

>> Phase Three:

Tech companies have made advancements in humanoid robotics. Now robots have the ability to make precise movements, drive cars (no need for self-driving vehicles) and have simple interactions with you when they deliver your pizza or install your DirectTV.

Blue-collar jobs now suffer the same fate as white-collar jobs resulting in what’s called a “post-labor-replacing-AI world.”

>> Phase Two:

Artificial general intelligence displaces white-collar workers forcing them into manual labor jobs less susceptible to automation. But manual labor, or skilled trade jobs are getting scarce. Young adults, aware of how AI is impacting the job market and unwilling to take on the burden of student debt, also pursue skilled trade jobs.

This increased demand for trade careers results in an over-saturated blue-collar job sector and there simply isn’t enough work for everyone. This is especially troubling for American women who currently make up less than 5% of the skilled trades workforce.

If you apply the principles of supply and demand, wages would then decrease because the number of skilled trades people is too high. High competition will justify wage adjustment.

>> Phase One:

Worst-Case Scenario

of all energy in the U.S. goes towards the operation of

AI centers

4.4%

The impact on our environment is a good example of the paradoxical nature of artificial intelligence wherein the negative repercussions may negate the positive outcomes.

Energy and Resource Use

When it comes to the environment, AI’s greatest strength is its ability to monitor, measure, map, analyze, and predict. In other words, AI’s value is in how it finds the data needed to take action against threats to the environment.

Here are some examples:

AI-powered satellites can chart methane emissions, assisting in the reduction of greenhouse gasses in our atmosphere.
AI-powered sound recording devices and cameras monitor wildlife, assisting conservationists with species protection.
AI-powered detection systems can track plastic accumulation in the ocean, assisting organizations in their debris removal efforts.

Positive Outcomes

AI’s ability to find the right data quickly is a welcome tool in the quest to protect our planet. Unfortunately, this technology comes at a cost. To understand why, let's talk about data centers.

Data centers are facilities that run applications, store and manage data, and deliver information technology (IT) services to companies and individuals alike.

Negative Repercussions

AI data centers perform the same functions as regular data centers but their infrastructure is optimized for artificial intelligence. They are large, energy-hungry facilities that develop and deliver AI applications and services for the AI enabled tasks we demand of our computers.

Compared to regular data centers that focus on general computing, AI data centers need large swaths of land to house, gigawatts of electricity to run, and gallons of water to cool racks and racks of servers, storage systems, and networking equipment. There are approximately 11,800 data centers worldwide, and close to half of them are in the United States alone .

AI Data Centers

Water

Those racks of servers, storage systems, and networking equipment need to stay cool in order to function properly. Liquid cooling systems, which require cold water to operate, are used to prevent this hardware from overheating. Imagine the water requirement for 2,000 plus servers– the amount in an average data center.

And data centers don’t exist in a vacuum. They are built in towns with populations sharing the same water supply. As a result, residents contend with rising water costs and shortages. Back to Meta, their Newton County campus uses around 500,000 gallons of water a day– that’s 10 percent of the county’s daily total. Meta’s demand for water is a major strain on the county's reservoir and risks putting their host in a water deficit by 2030 .

Of the 158 data centers in Georgia, Meta’s Newton County campus is one of the largest but is only half the size of their Altoona, Iowa campus. And companies from OpenAI to Amazon plan to build AI data centers that will dwarf the largest currently in operation. If fresh water is a limited resource, AI developing companies may need to make a choice between commerce and the human rights of water-stressed populations.

Electricity

Every time you ask ChatGPT a question, that question is routed to an AI data center, processed, then returned to you in the form of an answer. Each query consumes about what a lightbulb uses in a couple of minutes . Though that may not sound like much, there are more than 330 million ChatGPT queries in the U.S. a day . And remember, AI chatbot responses are a fraction of the services performed at any given AI data center.

When you consider the electricity required for developing, training, deployment, and running AI models, as well as the standard uses of electricity of any modern building, AI data centers are using gargantuan amounts of energy. For example, Meta’s Newton County, Georgia campus– a 2.5 million square foot complex with five buildings, uses 635,266 megawatts-hours of electricity a year.

For a comparison, 12 megawatt-hours will power the average American home for a year . According to the 2024 United States Data Center Energy Usage Report, 4.4% of all energy in the United States goes towards the operation of AI data centers. This same report states that the proliferation of AI will require the same consumption of electricity yearly as a quarter of all U.S. households by 2028.

Continue reading about AI to learn as much as you can
Understand the differences between AI theory and AI fact
Learn to use AI tools to help yourself and your business
Support legislators who share the same concerns about AI as you do
Find a balance between curiosity and skepticism

Our team believes that we can control our future with AI if we remain informed and proactive:

AI for Skeptics