We’re witnessing entire social systems—education, healthcare, taxes, and more—crumble as AI exposes how outdated their underlying assumptions have become.

Miriam is 26 years old, and every major system that’s supposed to support her path to adulthood has failed her in a different way.

She graduated from college in 2021 with a marketing degree and $87,000 in student debt. The education she received? Largely obsolete before she finished—professors teaching Facebook ads strategies from 2015 while TikTok was reshaping digital marketing. By senior year, she learned more from YouTube tutorials and AI tools than from $60,000-a-year classes. But she needed the degree because employers still required it, even though everyone knew it didn’t prove competence.

Now she works as a freelance “AI content strategist”—a job that didn’t exist when she started college. She uses ChatGPT and Midjourney to create campaigns for seven clients across four countries. She makes $73,000 annually, which sounds decent until you factor in no benefits, no retirement matching, and a tax situation so complex she pays $2,400 annually to an accountant who admits the IRS hasn’t figured out how to classify AI-generated income.

Last year, she spent three months trying to buy a small condo. She’d saved $40,000 for a down payment—five years of careful saving. She was repeatedly outbid by investment firms using AI algorithms to purchase properties 3% above asking price within minutes of listing. She gave up and continues renting a 450-square-foot apartment for $1,850 monthly—nearly half her take-home pay.

Her healthcare is a catastrophe. She pays $380 monthly for insurance covering almost nothing until she hits a $6,000 deductible. When chronic migraines started, she used an AI symptom checker that correctly diagnosed her in five minutes. Getting actual treatment required three months of waiting, $1,200 in copays for tests the AI had already identified as necessary, and a prescription costing $340 monthly because it wasn’t “covered.”

Last month, her younger brother was arrested for marijuana possession—a small amount that won’t be criminal in a few years after decriminalization, but was still illegal when he was caught. He’s in county jail awaiting trial, unable to afford bail, missing work, at risk of losing his apartment. The public defender met with him for seven minutes. An AI risk assessment flagged him “medium-high risk” based on zip code and traffic violations, making bail even less likely.

This is what system failure looks like from the inside. Not abstract policy debates, but daily life where every major institution that should enable stable adulthood is broken, inaccessible, or actively harmful.

Miriam isn’t unlucky. She’s normal. This is reality for tens of millions of young adults trying to build lives where every major system was designed for a world that no longer exists.

Why Systems Thinking Is Suddenly Everywhere

Systems thinking is a hot topic because people like Miriam are living through a collapse in real-time, and it’s becoming impossible to ignore.

We’re watching fundamental systems that have organized society for generations break down in obvious ways. Income tax is broken. College is broken. Prisons are broken. Healthcare, housing, employment—pick any major social infrastructure, and you’ll find systems designed for a previous era, straining under pressures they weren’t built to handle.

And AI is accelerating the collapse—not by attacking systems deliberately, but by revealing their fundamental assumptions to be obsolete. Every system rests on assumptions about human capabilities, information availability, time constraints, and coordination costs. AI is demolishing those assumptions faster than we can adapt.

The question isn’t whether these systems can be saved. It’s how much broken infrastructure we’ll pass to our kids, and whether we’re brave enough to rebuild from first principles while we still have time.

Miriam’s story reveals how a tax system built for 1920s workers is collapsing under the realities of AI-driven, borderless, multi-income digital life.

The Income Tax System: Built for W-2 Employees

Miriam’s tax situation illustrates how broken the system is for anyone whose work doesn’t fit 1920s categories.

The income tax system was designed around a specific economic reality: most people worked for a single employer, earned predictable salaries, and received W-2s at year’s end. That worked.

That world is vanishing. Miriam represents the future—gig economy, remote work, AI-generated income, global freelancing, multiple revenue streams that don’t fit any tax category. She has seven clients across four countries. She’s never physically met them. Her “work” involves using AI tools to create content. So whe

re does she owe taxes? Where was work performed—her Denver apartment, servers in Virginia where ChatGPT runs, or countries where clients are located?

When AI generates marketing copy that earns her money, who did the work? She prompted the AI, curated results, and delivered products. But GPT-4 wrote the words. Is that business income? Service income? Is she selling a product or a service?

Her accountant filed under five different income categories last year, making educated guesses about classifications the IRS hasn’t clearly defined. She paid $2,400 for this—money W-2 workers don’t spend—and still isn’t confident it’s correct.

Meanwhile, the wealthy deploy AI-powered tax optimization experts, exploiting system complexity for aggressive avoidance. The system punishes people like Miriam—straightforward income, modest earnings—while enabling sophisticated avoidance impossible without AI analysis of regulatory loopholes. Income tax assumes human labor, physical presence, and clear employer-employee relationships. AI obliterates all three. Rather than rebuilding for new realities, we’re forcing AI-age economics into 1920s categories. It won’t work.

The College System: $87,000 for Obsolete Education

Miriam borrowed $87,000 for a marketing degree. Her monthly loan payment is $780—more than many people’s rent. She’ll pay until she’s 36.

What did she get? Professors teaching outdated material. Social media marketing from 2014. Data analytics teaching Excel when industry used Python and R. Digital strategy never mentions AI tools already reshaping the field.

By senior year, Miriam learned more from free YouTube tutorials and AI experimentation than from paid classes. She used GPT-3 to help write papers, Grammarly to edit, Quillbot to paraphrase sections, avoiding plagiarism detection. She learned actual marketing from side projects and freelance work, not classroom instruction.

But she needed the degree. Employers still required it, even though everyone knew it didn’t prove competence. The degree wasn’t education—it was an expensive signal she could complete assignments and stick with something for four years.

Now she works in a job that didn’t exist when she started college, using tools that didn’t exist when she graduated, applying skills learned outside the classroom. And she’s paying $780 monthly for that increasingly meaningless credential.

AI makes this more absurd. Students use AI to write essays. Professors use AI to detect AI work. It’s an arms race where everyone knows credentials mean less yearly, but institutions can’t acknowledge this because their business model depends on pretending degrees still matter.

Alternative credentials are emerging—AI competency assessments, industry certifications, portfolio-based hiring. But Miriam’s generation is caught in transition: too late to benefit from the old system, too early to skip college entirely.

So they take on massive debt for partly obsolete education, increasingly disconnected from employer needs, then spend a decade paying it back while the system loads the next cohort with the same broken promises.

Miriam’s years of saving meant nothing in a housing market dominated by AI algorithms that outbid humans in seconds, turning homes into investment code instead of living spaces.

The Housing System: Algorithms Pricing Out Humans

Miriam saved $40,000—five years of discipline. Still couldn’t compete with AI-powered investment algorithms.

She spent three months seriously buying. Viewed dozens of condos, made offers on seven, was outbid every time.

The pattern was consistent: properties listed, and within hours—sometimes minutes—she competed against cash offers 3-7% above asking. Investment firms using AI algorithms identified undervalued properties and automatically submitted offers, beating individual buyers.

The algorithms had data she couldn’t see, analyzed comparable sales faster than humans, submitted offers instantly, and could afford overpaying because they optimized for portfolio returns across hundreds of properties, not finding one home to live in.

She never had a chance. Individual buyers with jobs and down payments can’t compete with institutional investors deploying AI-optimized purchasing strategies.

So she continues renting. $1,850 monthly for 450 square feet. Nearly half her take-home pay. No equity. No stability. No control over whether her landlord raises rent $200 next year (he probably will—his property management uses algorithmic rent optimization too).

Her parents bought their first home at 28 for $180,000 (about $280,000 today). They put down 10% on her dad’s single income. The house is now worth $650,000.

Miriam’s equivalent starter home costs $520,000. With 20% down, she’d need $104,000—more than twice what she already saved. And she’d compete against algorithms that don’t care about overpaying.

The system isn’t just hard. It’s broken. Housing has been financialized, and AI strategies are accelerating it. Homes are increasingly investment vehicles rather than places to live, and first-time buyers are systematically priced out.

The Healthcare System: AI Diagnosis, 1950s Delivery

Miriam’s healthcare shows the worst system failure: we have technology to do better, but institutional inertia prevents proper use.

When chronic migraines started, she used an AI symptom checker. Input symptoms—frequency, location, triggers, family history. The AI suggested three likely diagnoses, with migraine most probable. Recommended specific tests and treatments. Five minutes, free.

Then she entered actual healthcare.

First appointment: 11 weeks out. The doctor asked the same questions, ordered the same tests, and referred her to a neurologist. Another six-week wait. The neurologist confirmed the AI diagnosis from three months earlier and prescribed medication.

Total cost: $1,200 in copays before filling the prescription. The medication costs $340 monthly because insurance didn’t cover it—despite being a common, proven treatment.

Her insurance costs $380 monthly with a $6,000 deductible. She pays $4,560 annually in premiums before insurance covers anything meaningful. Then pays everything out of pocket until hitting $6,000.

She’s paying $380 monthly for “insurance” that didn’t help with $1,200 in diagnostic costs or $340 monthly medication. She might as well be uninsured until catastrophic events.

The absurdity: AI correctly diagnosed her immediately, free. The human healthcare system took three months and $1,200 to confirm what AI already knew.

We have technology for accurate diagnosis, treatment suggestions, and continuous monitoring. But we’re using systems designed around in-person visits, paper records, and insurance companies extracting maximum revenue while providing minimal coverage.

Miriam’s brother sits in jail because an AI risk score, built on biased data, labeled him ‘high risk’—a perfect example of technology making a broken justice system more efficiently unjust.

The Prison System: Her Brother’s Destruction

Miriam’s brother was arrested with a small amount of marijuana. In a few years, this won’t even be illegal—decriminalization is coming, just not fast enough.

He’s been in county jail for six weeks, awaiting trial because he can’t afford $5,000 bail. Lost his warehouse job after two weeks. About to lose his apartment. His public defender spent seven minutes with him and hasn’t returned calls.

An AI risk assessment scored him “medium-high risk” based on zip code, age, and two traffic violations. This influenced bail and will influence sentencing. The algorithm was trained on historical data reflecting decades of discriminatory policing, so it encodes and automates that discrimination while seeming objective and scientific.

Miriam watches helplessly. Her brother isn’t dangerous—he had personal-use marijuana. But the system will likely give him a criminal record, destroy employment prospects, make housing nearly impossible, and set him toward further criminal justice involvement.
This is supposed to be rehabilitation. It’s actually life destruction.

AI is making it worse—not through cruelty, but by automating bad decisions at scale. Risk assessments encoding historical bias. Surveillance flagging low-income neighborhoods for enhanced policing. Predictive systems create self-fulfilling prophecies.

We have technology enabling better alternatives: electronic monitoring instead of incarceration, AI-powered rehabilitation programs, personalized interventions. But we’re using AI to make a broken system more efficient at breaking people.

The Pattern: Automating Dysfunction

We’re not using AI to fix broken systems. We’re using AI to automate dysfunction at scale.

Income tax was already too complex and inequitable. AI makes it worse by creating income types not fitting existing categories while giving wealthy individuals AI-powered optimization that ordinary people can’t afford.

College was already unaffordable and disconnected from labor needs. AI makes it more irrelevant by doing work that students supposedly learn, while institutions pretend nothing has changed and charge $87,000 for increasingly obsolete credentials.

Housing was already difficult for first-time buyers. AI algorithms make it impossible by outbidding humans with superior information, instant decisions, and portfolio optimization.

Healthcare was already expensive and inefficient. AI can diagnose in minutes, but we still run three-month processes, charging thousands for confirmations of what algorithms already knew.

Prisons were already expensive and counterproductive. AI makes them more efficient at destroying lives through automated risk assessments encoding historical bias.

This is the infrastructure we’re passing Miriam’s generation: systems designed for worlds that no longer exist, failing at stated purposes, resistant to reform, and now being automated in their dysfunction.

Why Systems Break: Institutional Lag

Why can’t we just fix these systems?

The answer is institutional lag—the gap between when systems become obsolete and when institutions acknowledge and act on that obsolescence.

Institutions resist change because change threatens existing power structures, career paths, and revenue streams. Universities resist alternative credentials, threatening enrollment. Tax authorities resist reform, threatening bureaucratic jobs. Healthcare companies resist AI efficiency, threatening profit extraction. Housing policy protects homeowner wealth over affordability. Prison systems resist alternatives because incarceration has become an industry.

AI has accelerated change beyond what slow-adapting institutions can handle. The gap between “how things work” and “how things should work” widens exponentially.

Previous technological transitions gave institutions decades to adapt. AI compresses adaptation timelines to years or months. Systems designed for industrial-age employment don’t work for AI-age economics. We’re trying incremental adaptation when fundamental redesign is needed.

What We’re Passing to Miriam’s Generation

A tax system penalizing straightforward AI-augmented work while enabling sophisticated avoidance for the wealthy. Compliance costs consume thousands annually. A code so complex that even professionals guess at proper classifications.

An education system where degrees cost $87,000, teach partially obsolete skills, and create decade-long debt. Where credentials matter less yearly but remain mandatory gatekeepers. Where students learn more from free resources than expensive universities, but still must pay for the signal.

A housing system where algorithms outbid humans, institutional investors price out first-time buyers, and half your income goes to rent with no ownership path. Where home-ownership, defining middle-class stability for previous generations, is increasingly closed.

A healthcare system where AI diagnoses accurately, but three-month waits and thousands in costs are required for human confirmation. Where insurance costs $4,560 annually but doesn’t cover care until you’ve spent $6,000 out of pocket.

A prison system destroying lives over soon-to-be-legal conduct, using AI to automate historical biases, providing seven-minute legal consultations, and prioritizing punishment over rehabilitation.

The Window Is Closing

Miriam is 26. By 36, these systems will either be rebuilt or collapse entirely. We have maybe 5-10 years where intentional redesign is possible. After that, we’re in crisis management.

Her generation will inherit whatever we build or fail to build in that window.

Rebuilding means starting from first principles—redesigning taxes, education, housing, healthcare, and justice for an AI-driven world instead of endlessly patching obsolete systems.

What Rebuilding Requires

Start with first principles. What are we actually trying to accomplish? Given AI and modern technology, what’s the best way? The answer is almost never “patch the existing system.”

Accept that some systems need replacement, not reform. We’ve tried reforming for decades. It hasn’t worked. Income tax needs a complete replacement. College credentials need unbundling from education. Housing policy needs fundamental restructuring. Healthcare needs redesign around AI-enabled efficiency. Prisons need rethinking around rehabilitation.

Design for AI-age realities. Stop fitting AI-generated income into W-2 categories. Stop pretending four-year degrees are necessary when AI can provide personalized education. Stop allowing algorithms to price humans out of housing. Stop making people wait three months for diagnoses AI provides in minutes.

Move fast before the window closes. Every year we delay, more people take on debt for devalued degrees, pay thousands navigating incomprehensible taxes, get priced out of homeownership, and watch their families destroyed by counterproductive incarceration.

Be willing to threaten existing power structures. These systems don’t get fixed because fixing threatens those benefiting from current dysfunction. Reform requires confronting those interests.

Final Thoughts

Miriam is living through system collapse in real-time. Every major institution that should enable stable adulthood is broken, inaccessible, or actively harmful. She’s working hard, making responsible choices, and still falling behind because the infrastructure that previous generations took for granted has failed.

She’s normal. Tens of millions experience the same thing. This isn’t individual failure. It’s a system failure at scale.

We can do better. We have the technology. We have the knowledge. What we lack is political courage and institutional willingness to prioritize the next generation over preserving systems benefiting current stakeholders.

Miriam is 26. Her generation deserves better than inheriting our dysfunction. The question is whether we’ll give it to them.

AI is making each of us exponentially more capable, which will cause us to take on exponentially bigger projects!

Counter to most people’s thinking that AI will be used to kill jobs and reduce our workforce, AI will instead become the greatest job creator of all time. AI will make each of us exponentially more capable and exponentially more accomplished, and for this reason, we will begin to take on exponentially bigger projects. It will open the door to mega projects, even giga projects. All this activity will spawn exponentially more startups, with each of them requiring exponentially more employees.

In spite of all this ramping up and increased AI involvement, human learning is still the key to our future!

The Rise of AI in Society

In just a few short months, AI has become truly pervasive. From the convenience of virtual assistants like Amazon’s Alexa to the precision of IBM Watson assisting in healthcare diagnostics, AI’s presence is ubiquitous. In finance, AI algorithms are revolutionizing trading and risk management, while in transportation, autonomous vehicles by companies like Tesla and Waymo are redefining mobility.

A landmark breakthrough was Google DeepMind’s AI, AlphaGo, which defeated the world champion in the complex board game Go, signifying AI’s advanced problem-solving capabilities. However, public sentiment remains mixed, with AI often portrayed in the media as either a technological marvel or a looming threat to human employment.

Dispelling the Myths of Job Displacement

Still, the fear of AI-induced job losses is a significant concern, with Oxford Economics predicting that up to 20 million manufacturing jobs could be automated away by 2030. Yet, this perspective overlooks the historical pattern of technology-driven economic shifts where new technologies have always led to job transformations rather than net job losses.

The concept of ‘creative destruction’, coined by economist Joseph Schumpeter, aptly describes this phenomenon where old industries are disrupted, but new opportunities arise, often leading to more and better employment prospects.

The Promise of AI: A Net Increase in Job Creation

Contrary to popular belief, AI is poised to be a net creator of jobs and a catalyst for new entrepreneurial ventures. Its ability to augment human capabilities and enhance efficiency opens the door to an era of significant economic growth and innovation.

PwC estimates that AI could contribute up to $15.7 trillion to the global economy by 2030, with increased productivity and consumer demand. This column will delve into how AI is reshaping the labor market, fueling the startup ecosystem, and necessitating a realignment of the workforce.

As we explore AI’s transformative impact, it’s important to note that it is not just replacing jobs but creating a new paradigm of work where AI and humans collaborate on developing a prosperous future.

The future of work in an AI-driven world is not one of diminished prospects but transformed opportunities!

The AI Effect on the Job Market

The narrative of technology as a disruptor is as old as industry itself. The Luddite movement of the early 19th century, with skilled artisans smashing mechanized looms, is an early example of resistance to technological change due to the fear of job loss. Yet, history has consistently shown that while technology can render certain jobs obsolete, it also spawns new sectors and vocations. During the Industrial Revolution, the workforce transitioned from agriculture to manufacturing; in the late 20th century, the advent of the internet gave rise to entire industries that previously didn’t exist, from web development to digital marketing.

Today, AI poses a similar paradigm shift. Jobs involving repetitive, routine tasks are most at risk. According to a report by McKinsey Global Institute, activities like physical labor in predictable environments, data collection, and processing are likely to be automated, affecting positions in manufacturing, retailing, and data entry. However, the same report suggests that this will catalyze the creation of jobs in developing and deploying new technologies, managing the human-machine interface, and attending to tasks that require social and emotional skills, which AI cannot replicate.

The nature of work is undeniably changing, pivoting away from repetitive tasks toward roles that require creativity, decision-making, and strategic thinking. For instance, AI tools can analyze legal documents more efficiently than humans, but lawyers are still needed for complex negotiations and court appearances. In medicine, AI can help diagnose diseases from images more accurately than human doctors, yet the physician’s role is expanding into areas requiring human touch and judgment.

The future of work in an AI-driven world is not one of diminished prospects but transformed opportunities. The key lies in recognizing the evolving landscape and proactively adapting to it—turning AI into a partner that enhances human capabilities rather than a replacement that diminishes them.

What will your next job opportunity look like?

The Startup Ecosystem Revolution

As we venture into the new age of artificial intelligence, the startup ecosystem is experiencing an unprecedented revolution. AI is not only enabling existing businesses to thrive; it’s also the catalyst for a burgeoning breed of enterprises. Here are three reasons for this new breed of enterprises.

1. Case Studies of AI-Enabled Startups

Take the story of Blue River Technology, acquired by John Deere for $305 million. This startup’s “See & Spray” technology uses computer vision and machine learning to manage crops, reducing herbicide use by an astonishing 90%. Then there’s Zipline, an AI-driven startup delivering medical supplies via drones across Rwanda and Ghana, which has drastically improved supply chain inefficiencies and access to essential health products in remote areas.

2. Lowering Barriers to Entry

AI is democratizing entrepreneurship. Consider Casetext, a legal research startup utilizing AI to make comprehensive legal information more accessible, thereby leveling the playing field between large law firms and independent practitioners. Similarly, Chatbot technologies, such as those developed by Ada Support, allow small businesses to provide customer service at a scale previously only attainable by corporations with vast resources.

3. Identifying Market Gaps and Opportunities

AI is particularly adept at recognizing patterns and extrapolating insights from massive datasets—capabilities that startups are leveraging to identify and capitalize on market gaps. Stitch Fix, for example, uses algorithms to personalize clothing items for customers, a service that has filled a unique niche in the e-commerce space. Moreover, BenevolentAI harnesses AI to accelerate medical research, identifying treatment opportunities that may have otherwise been missed.

The role of AI in the startup ecosystem is multifaceted and profound. It’s not just a tool for innovation but a foundational element that is reshaping how businesses are conceived, operated, and scaled. As we look to the future, the symbiosis of AI and entrepreneurial spirit promises a landscape ripe with opportunities for those ready to embrace the AI revolution.

The AI-driven economy is not a zero-sum game but a multiplying force provided we embrace it with open arms and a willingness and readiness to adapt!

The Emergence of New Job Categories

The advent of AI is not a harbinger of job scarcity but a beacon for new job creation. This technological leap forward has catalyzed the birth of roles and industries that are as revolutionary as the technology itself. Here are three illustrations of emerging job categories.

1. Spotlight on New Roles and Industries

The landscape is rapidly evolving, with AI-driven industries like autonomous transportation, AI-personalized healthcare, and AI-enhanced cybersecurity emerging. Jobs like AI ethics officer and machine learning facilitator are gaining traction. For instance, Nauto, an AI technology company improving the safety of commercial fleets, relies on machine learning specialists to fine-tune their algorithms. Similarly, PathAI employs AI to assist pathologists in diagnosing and treating diseases, necessitating a new breed of AI-savvy healthcare professionals.

2. Reskilling and Upskilling: A Workforce in Transition

As routine tasks are automated, there is a growing emphasis on reskilling workers for the AI era. Programs like Amazon’s Upskilling 2025 initiative aim to retrain workers, while IBM’s New Collar jobs focus on roles where skills matter more than degrees. These programs are vital in transitioning workers into burgeoning fields where human-AI collaboration is quintessential.

3. The Crucial Role of Educational Institutions

Colleges and universities are rethinking their curriculums to prepare students for an AI-integrated economy. MIT’s Schwarzman College of Computing is a prime example, designed to educate the bilinguals of the future—those fluent in both their field and AI. Meanwhile, Stanford’s Institute for Human-Centered Artificial Intelligence aims to guide AI’s development and application for human benefit, training individuals who can lead the charge in ethical AI implementation.

The emergence of these new job categories underscores a clear message: the AI-driven economy is not a zero-sum game but a multiplying force for the workforce, provided we embrace the change with open arms and a readiness to adapt.

We are opening the door to a whole new class of human potential, not a force to be feared but one to be harnessed!

The Expansion of Human Potential

In the rapidly evolving AI landscape, the story is not one of replacement but augmentation. AI’s greatest potential lies in its capacity to expand human capabilities, allowing us to reach new heights in efficiency, creativity, and problem-solving.

1.) AI as a Collaborative Partner

Rather than taking over jobs, AI is increasingly serving as a tool that complements human skills. In healthcare, AI systems like IBM Watson are augmenting physicians’ diagnostic processes, enabling them to analyze medical data at superhuman speeds. In the creative industries, AI like OpenAI’s DALL-E generates images from textual descriptions, providing artists with new canvases of inspiration. Meanwhile, in the area of customer service, AI chatbots are handling routine inquiries, freeing up human agents to tackle more complex customer needs.

2. Solving Global Challenges with AI

The true promise of AI extends to its potential to address some of the world’s most pressing problems. AI algorithms are being used by startups like RecycleAI to improve recycling processes, thereby enhancing sustainability efforts. In the fight against climate change, ClimateAI is harnessing predictive analytics to anticipate climate risks and inform better decision-making.

3. The Imperative of Ethical AI

The expansion of human potential through AI must be underpinned by ethical use. Organizations like The Partnership on AI, which includes tech giants such as Google and Microsoft, are collaborating to ensure AI advancements are aligned with human values and societal well-being. Ethical AI frameworks are becoming a cornerstone of AI development, with initiatives like the EU’s Ethics Guidelines for Trustworthy AI guiding companies towards responsible innovation.

As we forge ahead, it’s clear that AI is not a force to be feared but one to be harnessed. By directing AI towards the enhancement of human capabilities and the betterment of society, we ensure that this powerful technology serves, above all, the interests of humanity.

Whether we’re harnessing AI for societal benefits or carving out a new career path, AI is proving to be a substantial job creator and not the job displacer it’s often feared to be!

Case Studies: AI as a Job Creator

The transformative power of AI is not just theoretical; it’s evidenced by the flourishing of businesses and individuals who have embraced this technology. Here are some examples:

1. Successful Business Pivots through AI

Adobe, an industry leader in creative software, has embraced AI, enhancing its products with intelligent features like content-aware fill and sophisticated marketing predictive analytics. This strategic shift towards AI not only preserved existing jobs within Adobe but also led to the creation of novel positions, including AI engineers and user interface designers with a focus on AI integrations.

2. Startups Driving Social Good with AI

In the area of social entrepreneurship, AI for Good is a movement exemplified by companies like Destácame in Chile, which uses AI to build financial profiles for underserved populations, enabling access to credit and financial services. Their work has not only created jobs within the company but also facilitated employment for others by helping them secure loans to start their own businesses.

3.) Individuals Excelling in AI-Infused Careers

On the individual level, we see profiles like Sara, an AI Data Analyst at a renewable energy firm, who transitioned from a traditional data role thanks to reskilling programs. Sara’s work now involves training machine learning models to predict energy yields from solar panels, a job that didn’t exist a decade ago but is crucial in today’s data-driven energy sector.

These case studies are a testament to AI’s job-creating potential. Whether it’s large corporations adapting to the AI wave, startups harnessing AI for societal benefits, or individuals carving out new career paths within the AI sphere, AI is proving to be a substantial job creator and not the job displacer it’s often feared to be.

As we learn to leverage an AI-integrated future, these emerging technologies will begin to enhance human work rather than replace it!

The Support Structure for Transition

As the dawn of an AI-integrated economy brightens, the need for a comprehensive support structure to navigate the transition becomes paramount. Over the coming years, we will need a multifaceted approach to prepare the global workforce for the seismic shifts brought about by AI.

1. Government Initiatives for Job Transition

A robust support structure is critical for a smooth transition into the AI-augmented job market. Government initiatives play a pivotal role here. For instance, the American Workforce Policy Advisory Board seeks to develop a national strategy for workforce development that adapts to the automation era. In Singapore, the SkillsFuture initiative offers citizens credits to attend courses that improve job readiness in a digitizing economy, covering areas like AI and data analytics.

2. Private Sector Support

On the private sector front, companies like Amazon and AT&T have set exemplary standards. Amazon’s Upskilling 2025 pledges to invest $700 million to retrain 100,000 employees for higher-skilled jobs in technology. AT&T’s Future Ready initiative is another ambitious program investing in its workforce through career-focused education.

3. Creating a Conducive Legal and Economic Framework

A supportive legal and economic framework is crucial for these transitions. This includes tax incentives for companies investing in employee retraining and amendments to labor laws that reflect the new work paradigms AI is creating. The European Union, for example, has been proactive in this area with its Digital Europe Program, which invests in digital technologies and ensures that the digital transition is socially fair.

4. Fostering Public Acceptance

Public perception and acceptance are equally important. Education campaigns that explain AI’s benefits and debunk myths can shift public opinion. For example, Finland’s AI Education Program aims to educate 1% of its citizens on the basics of AI, hoping to increase public comfort with the technology.

A supportive transition structure that combines government policy, corporate responsibility, educational initiatives, and public acceptance is essential. With these in place, the workforce can move confidently into an AI-integrated future where technology serves to enhance human work rather than replace it.
.

The workforce of the future will be characterized by AI literacy, harmonious human-AI collaboration, and a culture of continuous learning!

The Future Workforce: AI Literacy and Beyond

In the fast-approaching future, a new skill set will be as fundamental as reading and writing—AI literacy. As artificial intelligence weaves itself into the fabric of industry, understanding its mechanisms, strengths, and boundaries will be paramount for the workforce. These three sections delve into the critical importance of AI proficiency, the evolving partnership between humans and intelligent machines, and the perpetual learning imperative that will define the professional landscapes of tomorrow.

1. AI Literacy: A New Fundamental Skill

The workforce of the future will not only need to be proficient in basic digital skills but also in AI literacy. This means understanding how AI works, its capabilities, and its limitations. For instance, Google’s AI for Everyone course is designed to educate individuals about AI concepts, and Microsoft’s AI Business School offers learning paths on integrating AI into business strategies.

2. Harmonious Human-AI Collaboration

Envisioning a future where AI and humans work in synergy is already becoming a reality. Collaborative robots, or ‘cobots’, such as those produced by Universal Robots, are designed to work alongside humans, enhancing productivity and safety. AI-powered tools like Salesforce’s Einstein provide salespeople with insights to make better decisions, exemplifying how AI can be a partner rather than a replacement.

3. Continuous Learning as the New Norm

The concept of continuous learning will be integral to the future workforce. With AI’s rapid evolution, staying current will require an ongoing commitment to learning. Initiatives like LinkedIn Learning and Coursera for Business are at the forefront, offering courses that enable workers to upskill at their own pace. Companies like PwC have pledged to invest $3 billion in job training for their employees over the next four years, ensuring their workforce remains agile and informed.

The future workforce landscape will be characterized by AI literacy as a basic competency, harmonious human-AI collaboration, and a culture of continuous learning, ensuring that workers are not only prepared for the jobs of today but are also adaptable to the jobs of tomorrow.

The research labs of the industrial era have given way to a new toolkit paradigm that revolves around the manipulation of data, audio, video, sensory inputs, cloud computing, geospatial information, and digital assets!

The Future Workforce: AI Literacy and Beyond

COVID changed many things in our lives; not the least was the nature of work. While we’ve been busy figuring out if remote and hybrid work is here to stay, another more fundamental change has been picking up steam – the four-day workweek. Curmudgeons and traditionalists may be too quick to suggest this is just another misstep down the slippery slope of accommodating non-motivated workers and coddling the workforce.

Whether they’re in an office or working at the kitchen table, you will always have employees who will try to skimp on deliverables and minimize their workplace footprint no matter what kind of time clock is in place or the calendar is followed. A shortened workweek is really no riper for abuse than the traditional five-day workweek.

A new study on the future of work released by Ernst and Young found that both businesses and workers are better off and prefer a four-day workweek. In spite of recent hiring slowdowns and layoffs in the tech and financial industries, 40% of the companies in the survey have implemented a four-day workweek or plan to do so.

The story is the same overseas, from Iceland and the UK to Japan and New Zealand.

Not as Big a Change as You’d Think

What’s the best arrangement? Four 10-hour days? Five 8-hour days? Four 8-hour days? That debate almost seems as irrelevant as the idea of a 40-hour work week itself. Work has become much more fluid for many so-called “knowledge workers,” the new euphemism for white-collar workers.

Many people can’t even quantify how many hours they work NOW, as they check company inboxes on personal phones at all hours and accept videoconference invites from overseas for meetings early in the morning or late in the evening.

And at the opposite end, employers have seemed happy to accommodate employees who must leave early to pick up a child from school or step out for a doctor’s appointment. How many object when an employee asks to leave at 2:30 on Friday to get a head start on their weekend trip? Very few.

Work from home accelerated both of those trends – stretched-out workdays and day-to-day flexibility. But we were well on our way in these areas prior to the pandemic, too, with flex work schedules and summer Friday free days … combined with our tendencies toward workaholism.

What About Employee Productivity?

Whether employees are equally productive with a four-day, compressed workweek is less easy to measure than their satisfaction with the arrangement. The evidence in favor seems pretty significant, even though it’s mostly anecdotal.

But the fact that so many companies are moving in this direction, even though the job market is loosening up a bit and the economy is heading toward a recession, is probably an indication that employers aren’t concerned with a falloff in the quantity or quality of work getting done.

Many leaders were pleasantly surprised when remote workers, for the most part-maintained productivity levels during the pandemic. They seem willing to swallow hard and give this a go, too.

They’re probably considering this factor too — with an extra weekday at their disposal, employees can schedule things like car repairs and doctor appointments for that day. And there will be no more slipping out at 2:30 on Friday. Four-day workdays may mean they can draw a darker line between work days and off days.

The chief strategy officer for the crowdfunding site Kickstarter will vouch for the four-day schedule, stating, “The 4-day week has been transformative for our business and our people. Staff are more focused, more engaged and more dedicated, helping us hit our goals better than before.”

The Psychological Effect

I interact with many people who are in a four-day work environment.

They seem more focused and deliberate with their work. They’re less likely to waste time or put things off, knowing they’re always under a bit of a time crunch. They don’t want to lose the privilege of this work arrangement, so they seem more committed to getting things done in that compressed timeframe. Maybe that tendency will ease over time.

For now, at least, four-day workweeks are a privilege, not a “right,” and those who enjoy this workplace benefit will be on their best productive behavior to keep it.

A Recruitment Tool

There’s no question that employees feel more emboldened about their status vis-à-vis their employer than in many years. The Great Resignation may have fizzled just a bit, but the labor market still places a premium on good workers. Labor unions seem to be on the ascent.

Now that employees have experienced the flexibility of a pandemic, work-from-home environment, they’ve set their sights higher – on expanded work-life benefits like shorter workweeks. “Zoom-free Fridays” are good, but they want more.

And Twitter aside, for the foreseeable future, employers will be eager to offer the perks and niceties needed to keep and retain their people. The perceived value of in-house baristas and catered lunches will pale compared to the recruiting power of a four-day week for the new generation of workers.

What’s the Big Deal?

Many employers are wising up and realizing that enforcing productivity through mandatory hours is a hopeless proposition. Knowledge workers will produce as much as they feel like producing. Period.

In fact, ideal productivity in the knowledge workplace can’t be enforced, and it can only be motivated – primarily from within. Today’s office workers will produce if they feel valued and wanted. The more creative the work, the less meaningful mandatory hours and days become.

The Four-Day Workweek will Change Workplaces

Much of what we hear about shortened workweeks is from the employee’s perspective. But this trend will create challenges for many companies. Customers and clients won’t always match their schedules to the company’s four-day workweek.

As the movement progresses, we’ll have similar kinds of challenges and dichotomies as we had during the pandemic. COVID pushed many jobs to remote status but not all. Condensed workweeks will work for many industries, companies, and departments, but not all.

For example, help desks and customer service departments must operate at least five days a week, even if employees are remote. Members of customer service teams will need to stagger schedules so that one or two are available on each of five or six days. While the employees might have four-day workweeks, supervisors and managers might not.

Conversely, though, while factory workers missed out on the opportunity to work remotely during the pandemic, there’s no reason these companies can’t adopt condensed workweeks for many of their employees. After all, almost a century ago, Ford Motor Company led the way in transitioning workweeks from six days to five.

Our current five-day workweek will soon seem as backward as working Monday through Saturday. I have no doubt that 100 years from now, the average employee will have nearly as many days off as on. Thanks to IT advances, the productivity levels of workers in 2123 will be off the charts. Demographic trends will slowly shrink the skilled workforce between now and then, meaning workers will have even more clout.

Take those factors together, and “work-life” will assuredly flip to “life-work.”

In hindsight, it’s easy to see that in nearly every generation, innovation impacted job markets and employment trends. It’s not news that human workers are replaced by new technology and that, fortunately, new technology spurs the creation of new jobs and job categories. The list of outdated or diminished jobs is almost nostalgic: switchboard operators, travel agents, librarians.

And twenty years from now we might be fondly recalling our former interactions with the likes of postal carriers, taxi drivers, flight attendants, and bank tellers.

In fact, the job market is an excellent barometer of society’s priorities and technology trends. Pick nearly any futurist topic we’ve explored this year and it’s not too hard to imagine the new jobs that will surround it.

In many cases, the new jobs and categories of jobs will be quite technical as people work to bring blockchain, cryptocurrency, the metaverse, self-driving transportation, and other IT innovations to fruition and then into our daily lives.

Further below, I’ve identified 57 technology-related new jobs in 15 industries that will directly support or respond to these kinds of technology breakthroughs.

It’s Not Just IT

But before we get there, we should recognize that in some cases, technology breakthroughs will lead to more than just technical jobs. Take geriatric services, for example.

Thinking beyond COVID, medical technology is extending life expectancy for seniors. That trend will continue to drive a critical demand for a variety of personal care services for retirees, who are likely to enjoy over 20 years of time after retirement at 65.

And not to overgeneralize or typecast seniors, but as technology increasingly supports our daily lives, many of them will need personalized support just to keep up. Their challenge today may be programming the TV remote or the thermostat, but it’s only going to get more complicated from there. The solution? Personal IT assistants and generalized IT help desks. Sounds like a mission for AMAC and AARP!

IT Redefining Jobs

I should also note that technology is also changing and even upgrading certain jobs, but not necessarily doing away with them. Construction workers and auto mechanics, for example, used to be generalists. But with new technology-based tools, and the need for training on those tools, specialization in these kinds of blue-collar jobs will increase. This specialization increases these workers’ labor clout, market value, and compensation.

There’s another category of jobs enhanced by technology and other tools where the job is the same but the work is not. Recently I’ve watched laborers build a retaining wall and a brick wall on the property across the street. Back-breaking work, right? Not so much as you’d think anymore. These laborers now have access to specialized backhoes, caterpillars, and other equipment downsized for residential work compared to what you’d find on a typical commercial construction site. Thanks to this equipment, you don’t see anyone carrying heavy bricks from the truck to the wall or using a shovel.

What About Retail?

The future isn’t as bright for the approximately 32 million Americans who work in retail jobs. Consumer demand isn’t going away, but how retailers choose to meet that demand will continue to evolve with technology innovations that drive efficiency.

Current trends in e-commerce and in-store automation mean there will be fewer traditional customer-facing jobs. But some of these will be replaced by new jobs managing these platforms and servicing these systems. As with the next generation of blue-collar jobs, these specialty positions may require specialized skills with a level of IT training.

Basically we will see technology taking away much of the mind-numbing tedium of retail just as it did for so many factory workers.

The Cool New Jobs

So far we’ve only talked about incremental changes and the evolution of current employment situations. On another level, we’ll see entire new professions within entire new industries built around new technology. We’ll see job descriptions that weren’t even imaginable 20 years ago.

Yes, there will be high-level computer science jobs with smart people creating new breakthroughs and new versions of breakthroughs.

But at the same time, there will be the need to define and fill some less-obvious positions along with spin-off jobs made possible and necessary by those breakthroughs.

57 Jobs of the Future

Here’s a sampling of future jobs. Some may already sound familiar and plausible. Others are just a few years away. But it would be relatively easy to concoct others and maybe add over a hundred more to this list:

Metaverse Jobs

1. Metaverse World Designers
2. Avatar Designers
3. Metaverse Storefront Creators, Developers, and Operators
4. Metaverse Law Enforcement
5. DAO Attorneys

Cryptocurrency

6. Crypto Coaches and Advisors
7. Crypto Mortgage Specialists
8. Decentralization Managers

Future Entertainment

9. Robot Personality Engineers
10. Macro VR Projection Artists
11. Entertainment Trends Analyzer

Commercial Drone Industry

12. Swarmbot Engineers
13. Swarmbot Entertainers
14. Drone Command Center Operators

Smart Cities

15. Insect, Rodent, and Snake Monitors
16. Noise Analyzers
17. Police Drone Operators

Healthcare

18. Amnesia Surgeons – Doctors who are skilled in removing bad memories or destructive behavior.
19. Memory Augmentation Therapists – Entertainment is all about the great memories it creates. Creating a better grade of memories can dramatically change who we are and pave the way for an entirely new class of humans.
20. Digital Implant Architects
21. Genetic Troubleshooters
22. Body Part Fabricators
23. AI Health Managers

Digital Twins

24. Sensor Engineers
25. Remote Operation Designers
26. Digital Twin Command Centers

Big Data

27. Privacy Strategists
28. Personal Data Managers, Archivists, and Protectors
29. Blockchain Designers
30. Vulnerabilities Analyst

3D Printed Houses

31. 3D Print Architects, Designers, and Engineers
32. Fabrication Engineers
33. Site Prep and Planning Crew

Autonomous Transportation

34. Future Highway Architects and Designers
35. Traffic Analyzers
36. Drone Taxi Ground Crew

Cultured Meat Industry

37. Growth Process Technician
38. Vat Managers
39. Demand Tracking Planners

Future Education

40. AI Memory Assessment Engineers
41. AI Coach-Bot Designers
42. AI Teacher-Bot Developers

Future Agriculture

43. Soil Analyzers, Preppers, and Managers
44. Crop Techs
45. Harvester Team Planners and Supervisors
46. Irrigation Managers

Commercial Space Industries

47. Space-based Power Generators
48. Asteroid Trackers
49. Space Pilots
50. Space Journey Attendants

Robots

51. AI Capabilities Engineer
52. Robot Classification Gurus – Different laws will apply to different classifications of robots
53. Operator Certification Specialists

Other

54. De-extinction Engineers
55. Can We / Should We Ethicists
56. Ransomware Hostage Negotiators
57. Ransomware Police

As we’ve discussed in earlier columns, our primary and secondary school systems need to be thinking outside the box. That includes K-12, trade schools, and colleges. Each one should continually evaluate and revise their curricula and major courses of study so that we’re well-prepared to fill future jobs like these – and the hundreds of others that come to mind – so we can fully employ our future workforce and meet the needs of future societies.

Nearly every organization I work with or interact with is desperately trying to staff up. They’re not necessarily growing; they’re just trying to get back to pre-COVID staffing levels because the pre-COVID demand levels for their goods and services have returned. But staff shortages are keeping some from fully reopening and forcing some employees to work longer hours than they’d like.

The supposed goal on everyone’s lips during the last 18 months was to get things “back to normal” – to go to shows, eat out, travel, and so on. Similarly, policymakers and business owners assumed that employees would return to or remain in their jobs with the same employers, more than happy to maintain the same priorities and objectives for their lives and careers.

But we weren’t in a coma over the last 18 months. We were dreaming about traveling and socializing to be sure, but we also had plenty of time and reason to think about our engagement in the labor market. Many people decided it was time for a change, and as the economy continues to open up, that trend is accelerating. In August, 4.3 million people left their jobs, 2.9% of the workforce, which is a recent record.

Who’s leaving? Let’s dig deeper into those decisions. Why are tens of thousands of workers exploring new options or departing the workforce altogether, leaving so many jobs unfilled? And why is the great resignation accelerating? The answers lie along two general tracks.

“I’m Done”

Many of the resigning workers are late Baby Boomers and early Gen Xers who’ve decided to retire earlier than they had planned even as recently as five years ago. They’ve worked hard in the face of all the uncertainties of the pandemic, padded their savings, and rode the stock and cyber currency markets to record heights. They feel that life is too short to stay in the work world any longer given the newly proven fragility of life. And yes, the fear-ladened newspaper headlines have actually scared people out of the workforce. Their suddenly enhanced financial position has allowed for this to happen.

“I Deserve a Change”

Other workers who are remaining in the workforce, are also realizing that life is too short. They can’t retire but they’re more than willing to overcome their recent work-life inertia and break free of their employment status quo. The last 18 months have served as a wakeup call and a nudge to move on to careers that are steadier, more lucrative, and more interesting.

This is especially true in the hospitality industry. For whatever reason, the pandemic brought out the worst in too many consumers and they’ve been taking out their frustrations on hotel, restaurant, transportation, and other public-facing workers who were just trying to do their jobs.

In other cases, office-based workers have gotten used to working from home and they enjoy spending more time with their families and less time commuting. They know all about their worth and the current imbalance in the labor market. When their employers insist that they come back to the office, after more than a year of working productively at home, it’s an easy decision to look for an alternative, even for a competing employment opportunity that offers a more flexible approach.

No Going Back

In a way, what we’re seeing today is the perfect storm of mitigating circumstances that have brought us to where we are in terms of employee ascendancy and human resource management. None of these will revert to the situations so familiar last decade.

Post-COVID, employees are re-evaluating work-life balance and personal priorities.
Employers are experiencing high job vacancy rates.
New generations of workers are even less tied to corporate ladders, “paying their dues,” and “biding their time.”

9 Dimensions of Future Employer-Labor Relations

So, what will be the workplace norm for the years to come?

1. There will be increased automation in the services industries. For example, the trends toward robots in the kitchen will accelerate, along with wait staff service and food delivery. We’ll be checking into hotels strictly through kiosks upon our arrival.
2. Those hospitality-related jobs that remain will offer far higher wage rates that may help break the poverty cycle in some locations.
3. Companies will have no choice but to allow work-from-home arrangements or they’ll lose out on top talent. A friend told me of a situation where his daughter-in-law had to quit her mid-level accounting job with a large, regional manufacturer after that company refused to let her work remotely when her military husband was reassigned to a base across the country. Five years from now, you won’t see those situations.
4. Companies will increasingly crack down on abusive customers. If they don’t unequivocally side with and support mistreated employees, their employees will leave. “The customer is always right” will be far less true in the future.
5. Due to Baby Boomer retirements, a new group of leaders will emerge more quickly from the ranks of Gen X and Gen Y. Since this torch will be passed a bit sooner than it would have been, these leaders will have relatively longer careers in leadership positions.
6. The influence of this new generation of leaders will hasten the trends for more informal, entrepreneurial, and technology-oriented workplaces. Diversity in the leadership ranks will be realized more quickly than it would have been.
7. Since Gen Y and Gen Z employees are less inclined to believe in a “career ladder,” organizations will provide better ongoing experiences through salary and benefits as well as allowing flexible internal career paths and broadening opportunities like international relocation assignments.
8. Company policies and management skill sets will increasingly be focused on managing with empathetic interaction and accommodation for an employee’s life circumstances.
9. Entrepreneurialism will soar. Employees will be emboldened to take the leap to pursue gig work and consulting roles. More and more companies will be compelled to engage those resources, further spurring the evolution of virtual offices and even virtual companies.

It all adds up to a future with employees holding more cards and the need for companies to be creatively competitive to secure the talent they need.