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The AI Revolution: Redefining Roles or Cutting Jobs? ??

Just a few months ago, as I was gearing up to become an AI Consultant, I found myself grappling with a troubling thought: Am I helping workers cut their own throats?

The promise was clear: our AI training guarantees a 2-3x ROI for employers through productivity gains. But there was a catch—once employees hit those 50-100x productivity targets, would management start slashing jobs?

Let’s not sugarcoat it—this is already happening. Take Klarna, for instance. The Swedish payment giant cut hundreds of jobs, thanks to AI handling customer queries. Generative AI, trained on U.S. Department of Labor data, can now analyze any role, prioritize deliverables, and optimize them with AI—often without needing the employee’s involvement. This new reality allows employers to draw a straight line from an employee's role to deliverables, and ultimately, to profit.

The Strategic Dilemma:

1. Lean Optimization: Cut costs, reduce payroll, and optimize operations.

2. Scale Output: Ramp up production.

3. Reinvention: Reimagine the organization’s structure and purpose.

The big question? What will employers do with the time, cost, and labor savings?

But here’s the twist—employees won’t just sit back and let this happen. Over 59 million U.S. workers are unhappy in their jobs, with 86% not working in their dream roles. And guess what? 66% are still open to switching careers. For these employees, AI could be the ticket out of jobs they hate and into roles that offer purpose, satisfaction, and rewards.

Generative AI's Promise:

- For Solopreneurs & Enterprises Alike: Transform productivity by automating or augmenting tasks with AI.

- A Global Perspective: The Northern economies exploit 826 billion hours of labor from the global South—a system that’s unsustainable without drastic changes.

This isn’t just about technology; it’s about the future of work. AI could either widen the economic divide or create new opportunities for both the global North and South. The choice is ours—will we use AI to cut costs or to reimagine the world of work? ??

A Western View of the Impact of Generative AI on Labor

A few months ago I was getting trained to be an AI Consultant to do training for employers and employees in businesses. I made the comment. "I can't help feeling that somehow I'm helping workers cut their own throats." But yet I still had hope.

At the time my belief was that:

1. Employers would rally around the training we offered because we offered 2-3x ROI guarantee on the cost of the training in productivity gains.
2. Employees would be trained to get to the productivity gains of 50-100x, and once that happened, management would start slashing jobs from the payroll. to the productivity gains of 50-100x, and once that happened, management would start slashing jobs from the payroll.

For example, Swedish payments group Klarna said it had reduced hundreds of jobs and sees more reductions to come as it implements AI to handle customer queries.

Generative AI was trained on data available from the U.S. Department of Labor , through the Bureau of Labor Statistics (BLS) , and categorizes jobs in the United States using the Standard Occupational Classification (SOC) system.

The SOC system is used to classify workers into one of approximately 867 detailed occupations according to their occupational definitions. These occupations are grouped into 23 major occupational groups.

Across the U.S. there are certain occupations that dominate the workforce, with huge numbers of workers taking on these roles. They may be the first thing that comes to mind when we think of a ‘typical’ job.

The Most Common Jobs in America

In this analysis , data was used from the Bureau of Labor Statistics (BLS) to put together a list of the most common jobs in America, including the most popular jobs in each state. Also analyzed average salaries, typical responsibilities, and predicted employment changes for these popular occupations.

Highlights

• The most common job in America is retail salesperson, with over 3.76 million people in this role across the U.S.
• Retail salesperson is the most common job in 14 states, with the highest number of these workers (298,000) working in Florida.
• Of the top 20 most common jobs in America, general and operations managers had the highest median salary at $98,100, while fast food and counter workers had the lowest at $27,930.
• Fast food and counter worker is the most common job in nine states, with most workers in this role working in Ohio (136,220).
• The average salary across all 20 of the most popular jobs in the U.S. is $45,309.
• While retail salesperson is the most common job, it comes 16th out of 20 in terms of salary compared to the rest of the most popular jobs ($30,600).
• The role of nurse practitioner is expected to grow the most over the next few years, with a predicted employment increase of 44.5% in this occupation by 2032.
• Data entry keyers are expected to see the largest decline in employment between now and 2032, with a predicted 26% reduction in workers in these roles.
• Retail salesperson has been the top most common job in the U.S. since 1997.

Enter AI Training

Realistically, any employer can have generative AI take a given work role, and get a list of deliverables for it, then have AI create the prioritized list of the deliverables based on how effectively they can be created or enhanced using generative AI, starting with those that can be most efficiently executed with AI.

With or or without the employee's involvement it will happen because the employer has been waiting to draw a straight line from an employee's role, to the deliverable, to revenue and profit. Now they can.

The only thing that an employer as to now resolve is the strategic choice of what to do with the time/cost/labor savings.

AI Transformation Strategic Choices:

1. Lean optimization - cut the fat, cost and expense reduction, cut payroll
2. Scale output-increase production
3. Reinvention - reimagine the organization

But the U.S. workforce is not going to just sit there and let this happen to them. The mood right now is one of discontent.

Over 59 million workers across the U.S. expressing dissatisfaction with their careers.

• About 14% are currently working in their dream jobs, while a significant 86% are not. Many respondents abandoned their childhood career goals around age 25. |
• 35% of people said financial limitations presented a major obstacle when it came to pursuing their dream career, as well as a lack of opportunities (34%), and family commitments (22%).
• 1 in 3 (38%) of these respondents said they hated the job they chose
• 66% of respondents are still open to the idea of switching careers to pursue their childhood dreams.

For employees, generative AI will more like be used to get them out of the jobs that are hated, and into roles that provide purpose, satisfaction and rewards.

In the AI role equation, the transformation that occurs to deliver the productivity gains when a percentage of the tasks are shifted over to AI automation or augmented AI run by a virtual assistant (VA). This equation benefits the solopreneur as well as the enterprise, as many out sourcing firms, and off shoring firms provide staffing services with VAs.

The Hidden Truth Behind Global Trade: 826 Billion Hours of Labor Exploited in 2021

A recent study reveals a staggering reality: Northern economies, including the U.S. and Europe, rely heavily on the labor of the global South, siphoning off 826 billion hours of work in 2021 alone. This hidden workforce, equivalent to 369 million "ghost workers," doubles the labor available to Northern economies, sustaining their high consumption and wealth.

Despite contributing 90% of global labor, workers in the South receive only 21% of global GDP, with wages up to 95% lower than their Northern counterparts for equal work. This unequal exchange is not just a matter of low wages but is deeply rooted in systemic exploitation across all skill levels and sectors.

The study underscores that the current economic model of the North is unsustainable and cannot be replicated globally. To maintain their consumption levels without exploiting the South, Northern countries would need to drastically increase their own labor hours or reduce their consumption—an unlikely scenario.

Ending this exploitation will require a significant shift in global power dynamics, akin to the anti-colonial movements of the 20th century. International wage floors, fair trade policies, and economic sovereignty for the global South are essential steps toward a more just global economy.

This discussion isn't just academic—it's a call to action for leaders, businesses, and consumers to acknowledge and address the deep inequalities that underpin our global economy. The time for change is now.

Integrating the information from the survey about American workers' dissatisfaction with their current careers into the discussion about generative AI's impact on jobs in the global North and South provides additional insights into potential future trends:

Impact on the Global North

1. Job Dissatisfaction and Career Switching: The survey reveals that a significant number of workers in the U.S. are unhappy with their current jobs, with many considering a career switch. This dissatisfaction could be a driving factor for the adoption of generative AI in various industries. Workers who feel stuck in unfulfilling roles might be more willing to embrace AI-driven automation, either to free themselves from mundane tasks or to pursue opportunities in emerging fields that AI might create. As generative AI takes over routine and repetitive tasks, workers in the North may find opportunities to pivot toward more creative, strategic, or human-centered roles, potentially aligning closer with their childhood aspirations.

2. Redistribution of Labor: If generative AI enables more efficient and automated processes, it could reduce the need for certain jobs that are currently disliked, such as those involving routine administrative or data processing tasks. This could lead to a shift where workers are either displaced or transitioned into roles that require more creativity or interpersonal skills, which might better align with their original career dreams (e.g., creative fields like writing, acting, or entrepreneurship).

3. Skills and Training: As the North integrates more AI into its workforce, there may be a growing emphasis on reskilling and upskilling to help workers transition into new roles that are less susceptible to automation. This could create a push for education and training programs, potentially reducing the gap between current jobs and childhood dream careers. For instance, someone unhappy in a data entry job might be retrained to work in AI-driven content creation, which could be more fulfilling.

Impact on the Global South:

1. Vulnerability to Automation: In contrast, the global South may face greater challenges as generative AI potentially automates labor-intensive and low-skill jobs. Since these jobs are critical to the economies of many Southern countries, the impact could be severe, leading to widespread job losses in sectors like manufacturing, agriculture, and services. The survey data about job dissatisfaction in the North could indirectly influence the South if Northern companies choose to bring AI-driven operations back home, further reducing the need for outsourced labor in the South.

2. Opportunity for Reskilling: However, if generative AI becomes more accessible globally, there might be opportunities for the South to leapfrog into new industries that require more skilled labor. For instance, Southern economies could invest in technology education and infrastructure to create a workforce capable of managing and developing AI systems, potentially shifting away from labor-intensive industries to more knowledge-based economies.

3. Economic Divergence or Convergence: The outcome of generative AI's adoption could either widen or narrow the economic gap between the North and South. If the North uses AI to reduce reliance on Southern labor without equivalent opportunities for the South to advance, the disparity could grow. On the other hand, if AI technology is leveraged globally to empower workers in both regions to pursue more fulfilling and higher-skilled jobs, there could be a convergence of opportunities.

Conclusion:

Generative AI's impact on jobs will be influenced by current trends in job satisfaction and career aspirations. In the global North, AI might help address job dissatisfaction by automating disliked tasks and opening up new career paths. In the global South, the challenge will be to manage the transition away from traditional industries that could be automated, while finding ways to harness AI for economic growth and development. The key will be in how both regions manage the shift—whether they create more fulfilling jobs or exacerbate existing inequalities.

?? Join the conversation. How do you see AI shaping the future of your industry? #AI #FutureOfWork #GenerativeAI #Automation #JobTransformation #GlobalEconomy

Sources:

Are You Living Your Childhood Dream Job? Survey Reveals 59 Million American Workers Loathe Their Current Career

https://www.cardrates.com/studies/living-your-childhood-dream-job/

Unequal exchange of labour in the world economy

https://www.nature.com/articles/s41467-024-49687-y#Tab1