Author: Nathan Burke

Overview

Much of the opinion on how AI will change human work is polarizing: AI will either create a paradise where we’re all relaxing with our newfound time and wealth or it will cause the rapid downfall of civilization and kill us all. To me, the result of changing in the division of human/AI labor will be much more gradual, but will cause monumental shifts in education, work, recreation, and how we meatbags spend our time. In this article, I want to explore a few obvious shifts, the second and third-level effects, and finally a prediction that we’ll see the TikTok-style “Snakeoilification” of entry-level work.

Part One: Obvious Predictions on What AI Will Change in Human Jobs

Displacement of Blue-Collar Workers in Construction, Manufacturing, and Agriculture

One of the most common predictions is that AI will replace construction, manufacturing, and agriculture jobs. I think that the combination of semi-manual labor and how much technology has changed these industries make these sectors an easy target. Some examples:

• Mining and Construction: AI-powered robots and machinery can take over dangerous tasks in mining, construction, and oil drilling, significantly reducing the risk of human injury. This displacement benefits workers by removing them from hazardous environments.
• Manufacturing: In sectors where repetitive tasks dominate, like automotive or electronics manufacturing, AI can perform tasks with greater precision and consistency. This can free human workers to focus on more complex, creative, or supervisory roles.
• Precision Farming: AI can help optimize the use of resources in farming, reducing the need for manual labor while increasing crop yields. Automated machines can plant seeds, monitor crops, and apply fertilizers or pesticides in precise amounts, reducing waste and environmental damage.
• Farm Management: AI systems can monitor soil health, weather conditions, and pest activity to help farmers make data-driven decisions, improving efficiency and sustainability in agriculture.

Let’s then look at the 2nd and 3rd level effects that could result from AI taking over these jobs,

Second-Level Effects:

• Disruption of Unions and Worker Protections: As AI takes over dangerous and repetitive jobs in these industries, unions that traditionally protect blue-collar workers could lose influence. This could result in fewer collective bargaining opportunities, wage stagnation, or less job security in remaining roles.
• Impact on Trade Schools and Vocational Training: Institutions that train people for trades like welding, carpentry, and machinery operation may see decreased enrollment, forcing these schools to pivot toward emerging industries like robotics maintenance, AI system operation, or renewable energy technologies.
• Shift in Supporting Industries: Companies like Home Depot, Lowe’s, and others that rely on DIY construction, repair, and renovation may experience downturns in sales as demand for construction tools and materials declines. The retail economy could see fewer in-person customers, forcing adaptation through new business models, such as focusing on automation maintenance tools or smart home devices.

Third-Level Effects:

• Migration to New Sectors: Blue-collar workers displaced by AI in mining and manufacturing may seek opportunities in sectors like healthcare, renewable energy, or logistics. These sectors will need to adapt by offering reskilling programs for workers with a different skill set and expanding job openings in roles like technician and maintenance.
• Economic Shifts in Regions Dependent on Traditional Industries: Regions whose economies are heavily reliant on mining, construction, or manufacturing might suffer economically. This could lead to regional economic depressions, a shrinking tax base, and a shift toward service-based or gig economies.

AI in Retail

Right after manual labor is retail, and the lowest paid, lowest margin industries are always looking to cut costs and have lower turnover.

Second-Level Effects:

• Decline of Traditional Retail Jobs: As AI takes over customer service (via chatbots) and in-store operations (via automated checkout), traditional retail jobs will diminish. This will impact roles like cashiers, stock clerks, and even customer service representatives.
• Shift in Retail Skills: Retail workers will need to shift from customer-facing roles to more technical ones, such as robotic maintenance, supply chain optimization, or AI system management. Retail training programs may need to focus on technical literacy rather than interpersonal skills.

Third-Level Effects:

• Increase in E-commerce Jobs: While traditional retail jobs may shrink, e-commerce platforms and digital services could see growth in positions related to logistics, warehousing, and customer experience design. New job opportunities will emerge in areas like managing AI-driven supply chains and optimizing last-mile delivery.
• Impact on Local Economies: Local economies reliant on brick-and-mortar retail could see a decline, which might prompt cities to rethink urban planning. Commercial spaces may transition to co-working hubs or experience-driven retail (e.g., pop-up stores, interactive events) that provide something AI cannot replace.

Displacement of Support Staff by AI in Administrative Work

Moving down the “perception of humanness” continuum of work, we can then look at support staff in the professions. Administrative roles. Again, these are roles that perform similar, repeated tasks that are often entirely computer-based.

Some examples:

• Document Review and Contract Analysis: AI can handle routine legal tasks like reviewing contracts, analyzing case law, or preparing documentation. Lawyers and legal professionals can then focus on more complex tasks like litigation, negotiations, and client advisory roles, where human judgment and creativity are indispensable.
• Tax Preparation: AI can streamline tax filing processes, reducing errors and speeding up the work that accountants do for routine tax returns. This allows accountants to focus on more strategic financial planning services.
• Customer Support: AI-driven chatbots can handle routine customer service queries, such as FAQs or simple troubleshooting, reducing the workload for human support agents. Displacement here allows human workers to focus on more complex, personalized, or higher-level customer issues, which can improve overall service quality.

Second-Level Effects:

• Decline in Paralegal and Administrative Roles: As AI takes over document review, case analysis, and administrative tasks, there will be fewer entry- to mid-level jobs for paralegals, legal assistants, and administrative professionals. Law firms may become leaner, focusing on higher-tier roles like attorneys or legal strategists.
• Changes in Legal Education: With fewer entry-level legal roles, the appeal of law school may decrease, leading to a reduction in law school enrollments. This could shift the focus of legal education from routine work to strategic, AI-supported roles like legal technology experts or cyber law specialists.
• Mid-Level White-Collar Job Scarcity: Young professionals seeking stable, mid-level white-collar jobs like paralegals or office managers may find themselves struggling to find employment in fields traditionally reliant on administrative work. This could drive them toward sectors like data analysis, project management, or customer experience management, which may experience a surge in demand for human oversight of AI systems.

Third-Level Effects:

• Widening Gap in Legal Representation: As fewer people enter the legal profession, there may be a gap in representation for lower-income individuals or small businesses. While AI may help automate some legal services, it could increase the divide between those who can afford human legal expertise and those who must rely on AI-driven legal advice.
• Higher Education Shift: Universities may need to rethink curricula to accommodate fewer students entering traditional mid-level professions like law, accounting, or office management. There could be a rise in new academic disciplines, such as AI governance, ethics, or data rights law, to prepare students for a legal field shaped by AI.

AI and the Impact on Creative Industries

This is where it gets into the argument about whether AI can create art, and whether the “creative” industries will really only be dominated by us humans. I think there’s something uniquely human about saying “only people can do this”, but let’s put that aside and look at a few potential effects.

• Content Creation Support: In fields like design, music, and art, AI can assist creators by handling repetitive tasks such as generating design templates or background music. This doesn’t displace the creative process but augments it, enabling artists to focus on higher-level work.
• Elimination of “Low-Level” Creative Work – Things like stock photography, royalty-free music, and low-cost video work are already being eliminated as viable income-generators due to AI tools.

Second-Level Effects:

• Reduction in Entry-Level Creative Jobs: AI-driven tools in design, writing, and content creation could reduce the need for entry-level positions in advertising, publishing, and media. For example, companies might use AI-generated copy or design elements, leaving fewer opportunities for junior writers, graphic designers, or video editors.
• Evolving Creative Education: Creative arts programs may need to shift their focus from traditional skills (like drawing or writing) to AI-augmented creativity, teaching students how to collaborate with AI systems to enhance their output. This could also lead to the emergence of new roles such as AI-curators or content integrity managers who manage AI output to maintain brand and creative standards.

Third-Level Effects:

• Rise of AI-Driven “Gig” Economy in Creative Work: Many displaced creative workers might turn to freelance or contract-based work, creating a larger gig economy in the creative sectors. Platforms like Upwork or Fiverr could see a rise in professionals using AI tools to enhance their service offerings, further driving down prices in competitive creative fields.
• Shift Toward Experience-Driven Marketing: As AI takes over content generation, human creativity may become more valued in experiential fields like event marketing, experiential design, or storytelling-based marketing, where emotional intelligence, human connection, and originality are essential.

Part Two: The Decline of “Apprenticeship”

That might be the longest preamble I’ve ever written to get to my main point. Sorry. I actually cut some fluff…really…there was even more before! Here’s the main point:

For hundreds of years, we humans have accepted an apprentice system whereby the “expert” is willing to exchange mentorship and guidance for cheap labor. The entry-level worker is willing to dedicate time and effort above and beyond what they’re getting paid in order to get experience and learn from the professional. From unpaid internships to “individual contributor” roles, this exchange is seen as normal and sometimes necessary – especially in highly competitive, highly-compensated roles.

But what happens when the expert can replace cheap labor with free, AI-based assistants?

What Happens When Entry-Level Jobs Evaporate?

This will be a topic for an entire post, but here’s a teaser:

We’re already seeing a large shift where people sell “fast track” techniques to success, like courses on drop shipping, increasing followers to become influencers, affiliate marketing, and so on. These creators capitalize on people’s wish to bypass traditional pathways by promoting “passive income” strategies that avoid climbing a corporate ladder or gaining gradual experience.

This shows a type of meta-market where knowledge about how to hack or game the system becomes the product itself. These “inside secrets” essentially offer a promise of bypassing traditional expertise in favor of quick success. This shift also contributes to the gig economy and creator economy, where many people attempt to leverage platforms for short-term gains, often without building long-term skills or relationships, which might have historically come from working under an experienced mentor or within a structured organization.

In this way, the “apprentice effect” is not just hypothetical—it’s already happening, and we’re seeing people try to capitalize on this trend by selling courses on shortcuts to success. These new pathways raise concerns about sustainability and depth of expertise, but they reflect how individuals are adjusting to the changing landscape of work. 

In other words, if you roll your eyes every time you see an ad touting a new “proven method” to gaining followers, creating a YouTube channel that pays $50k per month, or teaching you to sell a course, get ready…..your eyes are going to be bleeding soon.