AI's Economic Ripple - The White Collar Shakeup, Blue Collar Renaissance and Silent Stars
- Natasha Sodhi
- 18 hours ago
- 9 min read
“I can ask ChatGPT to find me a date and my interview answers, but I cannot ask it to fix my flush at 1AM. Neither can I call Grok Humanoids (not yet)”
IvyAgents
AI reshaping our White Collar, Blue Collar & Silent Stars Paradigm
What is the big wave shift across the job market from white collar end to the blue collar end, creating an economic ripple? Is the fundamental meaning of work, changing more rapidly than we can imagine? Should we need to train our young generation for tomorrow, not for today?
During the Industrial Revolution, automation was feared by the manufacturing manual labor employees, classified as blue-collar. Now as AI Revolution infiltrates data analysis, marketing, finance, law, and beyond, it’s the white-collar world that’s feeling the aftershocks. Meanwhile, blue-collar jobs are quietly entering a renaissance. Skilled trades, maintenance, logistics, and sustainable production are becoming the new backbone of an AI-driven circular economy, especially led by the chip and energy sectors. The result is an economic ripple that’s rewriting how we work, spend, and value and grow human skills. As humanoids merge with AI, the story may evolve, but our blue-collar friends, and Gen Z’s joining the workforce, will enjoy this renaissance for a while.
I believe we should add a third category - silent stars or no-collar, the unpaid ones who often get overlooked for their work. These stars are our parents, partners, spouses and relatives keeping our homes safe, and us cared for and fed, that we can be successful at our official workplaces.
The White Collar Job Shakeup - Its Just Starting Today
People Lens
AI will replace 80% of jobs by 2030—and take much of the Fortune 500 with it.
- Vinod Khosla, Fortune Article
According to Stanford University’s Digital Economy Lab, early-career white-collar workers have already experienced a 13% employment decline in AI-exposed fields since 2022. McKinsey has an alternate 30% prediction for white collar #job automation by 2030. My call is that it will be closer to the 80% number, based on the AI to AGI to ASI curve, instead of projecting based on today’s AI potential.
Corporate jobs evolution projection
Across AI tech acceleration and corporate adoption
Job Shape Shifting : It is not just the repetitive and entry level roles, but jobs like experts and middle management that will collectively slim the organizational layers. We will move from a reality of managing people, to managing agents, in the new world, which will alter the need for middle management, as well as the real skillsets needed for the job. Additionally, new jobs will be added, with their nature evolving as we rapidly move from #AI to #AGI to #ASI era. By 2030, the World Economic Forum predicts 97 million new AI related jobs, although these might not fill up the reductions. These may vary for AI data scientist, prompt engineering, AI integration specialists, full stack modelers etc.
Organization & Technology Lens
AI People Wheel
When leaders embarked the prior Digital Transformation era, it took a while to get this people wheel to a relatively green state, given the number of skill needs, new growth ladders and associated talent wars that came with it. The AI Revolution is different - it is more than just a transformation, since it changes some of the most fundamental aspects that power the wheel. It is not just about what is visible, but about what is supporting it invisibly, and what is possible.
The people wheel needs to be replanned for an AI dance around 4 factors
Entry-level Vulnerability & Apprenticeship - Number of entry level employees accepted post university and the timing in the workforce, will impact the traditionally mastered apprenticeship funnel
Workforce Optimization vs Reduction - The corporate lens needs to shift from AI inspired quick workforce reduction to thoughtful workforce optimization. Yes, efficiency gains are easy wins, but if you have excellent employees immersed in your corporate culture, don’t you want to retrain them to use AI innovation to deliver 20+ top line LT value vs saving just 1+ bottom line ST value?
Upskiling vs Reskilling vs Job Modifications - It is no longer about adding Python to your skills to excel, like in the prior Digital Transformation era, but its about fundamentally learning how to best co-operate with evolving AI as your corporate best friend, to win in the AI Revolution. Additionally, many jobs will change in the very fundamental description of the job requirement, beyond pure skillset needs.
Tech & Data Transformation Pace - Many organization, esp. large ones, have the unfortunate burden of legacy tech systems and unintegrated databases that piled on through decades of tech advancement and acquisitions. The pace of streamlining legacy systems will determine how well you can fully embrace AI and subsequently your pace of AI led people wheel advancement.
Blue Collar Renaissance - The New Safe Haven Gold
People view
The AI economy will depend quite a bit on the physical world for its infrastructure foundation. These jobs, which require physical presence, fine motor skills, and on-site problem-solving, are largely insulated from the current wave of AI automation.
The U.S. Bureau of Labor Statistics (2024) projects strong growth for electricians, robotics technicians, and construction specialists. As an example, electrical workers employment is predicted to grow 9 % from 2024 until 2034, adding ~810,000 jobs over the 10-year period. This is creating what economists may call a “Blue-Collar Renaissance”. There is a revival of craftsmanship and technical trade value.
There are two key variations of blue collar jobs, with different compensation structures, perceptions and technology influence:
Large Corporations - These have manual labor driven jobs for manufacturing, infrastructure upgrades, supply chain, data centers, logistics systems, renewable energy grids, robotics maintenance, amongst other. The U.S. manufacturing and construction sectors are seeing job growth due to renewed federal AI investments and trade tariffs, tech giants’ datacenter & energy needs, with AI enhancing, not replacing physical and craft-based tasks.
Small and Medium Businesses (SMBs) and Independents - The SMBs include roles such as electricians, plumbers, roofers, etc. These are the wonderful people we see fixing our homes and office spaces, to keep them safe and functioning for us. These hands-on disciplines are now viewed as stable, respected, and well paid career paths, given supply shortages, attracting college-educated workers disillusioned with the office economy.
Four key factors are playing into this blue-collar resurgence in the AI era:
Job Shakeup Immunity: You can't download a plumber. You can't ask ChatGPT to fix your broken water pipes, rewire a house or install an HVAC system. Trades like electrical work, plumbing, construction, and specialized maintenance require dexterity and physical interaction with the real world that robots and AI algorithms cannot yet replicate cost-effectively or reliably.
Pride of Nationalism: These jobs that are not easy candidates for outsourcing to another country, whether it is due to physical presence requirement or tariff implications. Especially for the second segment of SMB blue collar jobs or trades, individuals are typically proud of their motor skills and value for the work being created. This can range across wide set of professions from woodwork, to reflooring, roofing and the likes.
Surging Demand and Wages: Widening shortage of skilled tradespeople (estimated at hundreds of thousands in construction and manufacturing) is driving up demand and, consequently, wages. It’s no longer uncommon for skilled tradespeople to earn six-figure incomes, surpassing many office-bound professionals. A flooring professional with a small team, can easily bill 10k USD for 2-3 days of work.
The GenZ Pull: Gen Z is increasingly viewing vocational training and apprenticeships as a financially stable and secure alternative to expensive, debt-inducing college degrees whose returns for 50k-200k USD investments are now uncertain, with the AI white collar job shakedown.
Organization & Technology Lens
Modern blue-collar work is increasingly tech-driven: electricians program smart grids, mechanics maintain autonomous fleets, and factory operators run AI-driven machinery. These workers are not being replaced—they’re being supported, re-skilled and revalued. The expertise in this sector is critical and cannot be as easily replaced, given the true training need to excel and shortage. In this paradox lies the renaissance of blue-collar labor.
Powered by technology, not threatened by it: For our two key blue collar areas, here is how the technology will evolve and support organizational mandates:
Large Corporations - These organizations will continue to invest in technology to both address the shortage in manual work supply, as well as increase existing workforce efficiency with the AI driven tech tools, along with other emerging technologies such as 5G, IoT and Edge, to design truly innovative solutions. The AI focused technologies will partly include the evolving LLM level intelligence, but will also require hardware front with humanoid robots.
Small and Medium Businesses (SMBs) and Independents - Interestingly, we often underestimate how lucrative some of these SMBs can be. Fields requiring physical dexterity—electricians, welders, plumbers, and mechanics—remain insulated from AI’s reach. Machines may master logic, but not yet manual precision or contextual adaptability. Humanoid robots with supreme precision will be much behind the AGI ASI pace, which is relatively easier to implement with accelerating software, models, chips and infra potential. The “AI-proof” trades enjoy rising wages as demand surges.
Silent Stars - Will AI & Robots change their lives?
For all the silent stars in our lives, doing the work as our parents, house partners and relatives, their work is not paid but has tremendous unseen value as super valuable horse power behind the broader employed sector to do the paid work. This ranges from housekeeping, kid care, elder care to other life maintenance needs.
University of Oxford experts predict that ~ 40% of time spent on domestic tasks could be automated within a decade, freeing large blocks of unpaid labour for other activities. Grand View Research Research suggests automation could save 50–60% of total time currently spent on unpaid domestic work (with uneven gains across tasks), meaning many household routines — cleaning, shopping, medication reminders, basic transfers — may be handled or coordinated by AI and robots.
The U.S. and many countries face growing caregiving pressure (~63 million US family caregivers in 2025 per AARP), so robots can be used both to augment scarce human carers and reduce strain on family members. Market forecasts show elder-care and companion robot industries expanding rapidly (global elder-care-robot markets were estimated near USD 2.9B in 2024 with double-digit CAGRs into the 2030s), which will make assistive devices and humanoid helpers increasingly affordable and capable. Early clinical and field studies also find social/companion robots can reduce loneliness and improve engagement for older adults, indicating humanoids won’t just do chores but may also provide reminders, gentle monitoring, and social interaction. Although designers and policymakers will need to guard against reduced human contact, and privacy/safety risks as these technologies diffuse.
The question is - when will these future humanoid robots be affordable enough for the mass population to truly make a real impact. This will free up bandwidth for individuals to join back the workforce, if they need to, by assisting them with caregiving and housekeeping to keep their loved ones safe. My prediction is 2032-2035, we shall see.
So What?
It may be time to accept fully that AI acceleration is coming, whether we are ready or not in our thinking. We need to shift our mindset from fear of “any time” job loss and economic climate change, to the power of global skills equalization. This will empower developing countries facing issues like limited medical expertise, legal aid challenges, teaching resources etc. We will have to trust more in our governments, and our non-profits and corporations may need to actively pursue policy making for some level of monetary equalization measures to ensure people can peacefully fulfill their basic living requirements as job landscape shrinks in some areas and expands in others.
Please leave your comment and thoughts, on how you see the AI job landscape changing for your organization. This will spark exciting discussions for us to stay connected as an AI community!
About the Author
Natasha Sodhi is Chief Advisor at IvyAgents.AI. She served as a Director at PwC, leading the Digital Strategy & Transformation offering, as well as the flagship AI Strategy offering. Prior to that, she developed AI and people thought leadership, while leading Digital and Data engagements, at BCG in US. Previously, she led a $60B digital product P&L for a financial services leader, actively employing AL, ML and data advantages to win in the market. She started her journey as a tech entrepreneur, leading development of innovative wireless communications products centered around data and RF signal analysis. She was also awarded research and entrepreneurship grants from European Space Agency and Indian Department of Scientific Research.
References:
https://fortune.com/2025/07/01/silicon-valley-investor-vinod-khosla-ai-job-prediction-interview/
McKinsey & Company (2025). Generative AI and the Future of Work: Rethinking Talent, Tasks, and Transformation.
World Economic Forum (2025). The Future of Jobs Report.
Brynjolfsson, E., Chandar, B., & Chen, R. (2025). Canaries in the Coal Mine? Six Facts about AI Employment Effects. Stanford Digital Economy Lab.
U.S. Bureau of Labor Statistics (2024). Occupational Outlook for Skilled Trades in the Automation Era.
MIT Work of the Future Task Force (2023). Work of the Future: Building Better Jobs in the Age of Intelligent Machines.
https://www.grandviewresearch.com/industry-analysis/elder-care-assistive-robots-market-report
https://www.sciencedirect.com/science/article/pii/S0040162523001282
https://www.aarp.org/pri/topics/ltss/family-caregiving/caregiving-in-the-us-2025/
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