Imagine walking through the misty pre-dawn streets of 19th-century London, tapping on windows with a long stick to wake people for work. This was once a real job, the knocker-up, until the alarm clock rendered it obsolete. Technological progress has always eliminated some occupations even as it has birthed new ones. Now, as artificial intelligence (AI) advances at breakneck speed, a question haunts boardrooms and break rooms alike: Will AI take our jobs, and if so, what comes next?
Renowned historian Yuval Noah Harari warns of a “rise of the useless class”, a mass of people pushed out of the economy by intelligent machines. It’s a grim scenario in which billions could become economically irrelevant, not through laziness or choice, but because AI outcompetes them at both physical and cognitive tasks. Harari’s prediction is jarring: in the 21st century, most of what we learn by age 20 might be irrelevant by age 40, forcing people to “reinvent themselves again and again, faster and faster” just to stay relevant. The fear is palpable. Yet on the other hand, optimists, including many tech leaders and economists, paint a more hopeful picture. They argue that AI cannot be a job-killer, but a job-transformer, a catalyst for human ingenuity. AI might free us from drudgery and ignite a renaissance of creativity and purpose in our work lives. Which fate awaits us: a slide into widespread joblessness, or a leap into a more abundant future of work?
A Double-Edged Sword: Disruption and Productivity
AI’s impact on employment is often described as a double-edged sword. On one edge, AI threatens to automate tasks at an unprecedented scale. A 2023 analysis by Goldman Sachs estimated that generative AI advances (like ChatGPT) could “expose” 300 million full-time jobs to automation worldwide. Around two-thirds of occupations in the U.S. include tasks that could be at least partially automated by AI, and up to half of the work within those roles could technically be handled by machines. These numbers suggest a level of disruption that rightly grabs headlines.
Yet the other edge of the sword is sharper than many realize: productivity and augmentation. AI may take over tasks, but that doesn’t always equate to taking over entire jobs. In fact, Goldman’s report was quick to note that “most jobs and industries are only partially exposed to automation and are thus more likely to be complemented rather than substituted by AI.” In other words, for the majority of occupations, AI will handle certain duties, allowing humans to focus on the rest. History supports this pattern. Technological revolutions tend to reallocate work rather than simply destroy it. For example, automated teller machines famously reduced the number of routine bank teller tasks but did not eliminate bank teller jobs, instead, human tellers shifted to more customer service and sales-oriented duties, and bank branches actually increased in number after ATMs were introduced. Each wave of automation has spurred fears of mass unemployment, and each time the economy has eventually adjusted, albeit not without pain in the transition.
Recent data offers a cautiously optimistic view that this adjustment will happen again with AI. The World Economic Forum’s Future of Jobs analysis in 2020 predicted that while 85 million jobs may be displaced by automation by 2025, about 97 million new jobs could emerge, a net gain of jobs. Likewise, as of 2023, nearly 75% of companies surveyed plan to adopt AI, yet half of them anticipate it will create overall job growth in their firm, whereas only a quarter expect a net loss of jobs. This doesn’t mean the same jobs will remain; it means new roles and industries will arise. In the past 80 years, over 85% of employment growth in the U.S. came from the creation of entirely new occupations that technology made possible. As one study notes, about 60% of workers today are employed in occupations that did not exist in 1940 . From web designers to app developers and digital marketers, none of these roles would have been fathomed by our great-grandparents. AI could similarly spawn jobs we can barely imagine now.
So, the promise is that AI-driven productivity gains will open doors even as it closes others. In pure economic terms, Goldman Sachs predicts AI could boost global GDP by 7% (almost $7 trillion) over the next decade. Productivity growth of that magnitude should create new wealth and, historically, new demand for labor in areas where humans are still needed. As Bridgewater founder Ray Dalio frames it, technology is a “two-edged sword”: it will raise output and efficiency, meaning we might not need to work as many hours for the same results, but it also raises a critical question of distribution. If a company can do twice the work with half the people thanks to AI, who benefits from that efficiency? Dalio observes that without careful societal management, the gains might accrue to a small group (e.g. tech owners and investors) while many workers feel the blade’s cut in the form of lost jobs or stagnant wages. In his words, AI is both a “super plus for productivity” and a “divider in who benefits and who doesn’t,” making it a social question as much as an economic one. The challenge ahead is ensuring the tailwind of AI’s progress isn’t overcome by the headwinds of inequality and social upheaval.
Not Our First Rodeo: Lessons from Past Revolutions
To understand what’s coming, it helps to step back and recall previous technological upheavals. The Industrial Revolution of the 18th–19th centuries mechanized physical labor, from weaving looms to steam shovels. Many manual jobs vanished, yet new industries – textiles, railroads, manufacturing – exploded. The 20th century’s automation and computer revolution again shifted the landscape: farm labor plummeted as tractors arrived, but factories and service sector jobs grew; later, assembly-line work declined while entirely new fields in computing and information rose. Each era of disruption created new kinds of work even as old kinds faded.
A key insight from economists is that humans are not horses. When automobiles and tractors debuted, the population of working horses collapsed (from 26 million in the U.S. in 1915 to only a few million by the 1950s), a horse can’t retrain to become a truck driver or a factory worker. Humans, by contrast, can learn and adapt. As one example, the rise of automobiles didn’t just put blacksmiths and carriage drivers out of work; it spawned entire new categories of employment that would have sounded like science fiction in 1900. “The horse-and-buggy drivers’ jobs were all gone,” notes economist Harry Holzer, “but the number of jobs that opened up in the auto industry… produced not just new categories of jobs, but enormous new numbers of jobs.” From assembly-line workers to auto mechanics, highway planners, motels, drive-thru restaurants, the car reshaped the economy in ways no one predicted. Similarly, when ATMs and online banking emerged decades later, pundits predicted bank tellers would disappear; instead, teller roles evolved and banks shifted employees into relationship-based roles (like financial advising and sales), and the banking sector continued to grow . The takeaway is that we’ve been here before, though perhaps not at this speed. AI is often dubbed the engine of a “Fourth Industrial Revolution”, one that may ultimately dwarf the previous ones in scope. But as we face it, we carry the lessons (and scars) of past disruptions. One lesson is the importance of time. Past transitions often took decades for society to adapt. There was pain: old industries in decline, workers needing reskilling or suffering unemployment, and social unrest (think of the original Luddites, textile workers who smashed mechanical looms around 1811 in protest of job loss). Over time, however, new generations entered a labor market with entirely new assumptions and opportunities. The children of farmers became factory workers; the children of factory workers became programmers; each generation encountered a changed world of work.
Will the AI revolution be faster and more jarring? Quite possibly. Unlike mechanical inventions that replaced muscle, AI targets the cognitive realm, the “white-collar” office jobs and even creative and decision-making tasks once seen as uniquely human. That broad reach has some experts concerned that this time could be different, compressing the upheaval into a shorter window and climbing the skill ladder. A recent study by OpenAI and University of Pennsylvania researchers found that a surprising range of jobs may be heavily affected by generative AI, not just routine clerical work, but roles like accountants, financial analysts, legal assistants, journalists, translators, and even software developers could see a large share of their tasks automated . Unlike past automation which hit factory workers or bank clerks first, this wave is intruding into work that requires a college education.
However, even this has a precedent of sorts. When personal computers and the internet arrived, they dramatically changed office work, yet also created whole new occupations (IT managers, web admins, digital marketers) and boosted demand for high-skill workers. Many experts thus believe that, while AI will be profoundly disruptive, humans are unlikely to face a total “job apocalypse” in the near future . We will see churn: certain jobs declining, others growing. In fact, the World Economic Forum’s latest forecast for the next five years highlights this churn. Among the fastest declining roles due to AI and other trends are clerical jobs such as data entry clerks, secretaries, and bank tellers, positions involving routine paperwork and organization . By contrast, the fastest growing job titles are those like AI and machine learning specialists, data analysts, information security analysts, and digital transformation specialists, all expected to see demand surge by 30–40% (adding millions of jobs globally) . The economy is essentially reallocating work toward tech-centric and human-centric roles. The real question is not if enough new jobs will emerge, history suggests they will, but whether those losing jobs can transition into the new jobs readily, or whether we face a prolonged period of skill mismatches and social strain as the workforce adjusts.
Humans + AI: Augmentation, Not Annihilation
One hopeful path forward is to view AI not as a replacement for humans, but as a powerful tool to augment human productivity. In the phrasing popular among technologists: AI won’t necessarily replace you, but a person using AI may replace a person who doesn’t. Already, forward-thinking professionals are finding that partnering with AI can make them far more effective at their jobs. Consider some recent empirical findings:
- Customer Support Augmentation: At a Fortune 500 software company, giving customer service agents an AI assistant (a tool that suggested responses and resources) boosted their productivity by 14% on average . Interestingly, the biggest gains were seen among junior or less-skilled workers, who with AI help could perform almost as well as more experienced agents . The AI leveled up their communication skills and knowledge, essentially compressing the learning curve. Rather than replacing support reps, the AI made each rep more productive and effective, a clear case of complementarity.
- Faster (and Better) Writing: In another study, professionals in fields like marketing and HR were asked to use ChatGPT to help with writing tasks (drafting press releases, reports, emails). The result: those using the AI completed their tasks 40% faster than those who didn’t, and independent evaluators rated the AI-assisted work as 18% higher in quality on average . The AI acted like an on-demand editor and brainstorm partner, handling routine prose or giving suggestions so that the human could refine and add the final creative touch.
- Freeing Up Higher-Level Work: Across multiple industries, workers report that AI tools are taking over menial parts of their job, freeing them to focus on more strategic or creative aspects. In a global survey, 93% of employees who actively use AI said it allows them to focus on higher-value tasks like problem-solving, strategy, and relationship-building . Rather than feeling threatened, these workers felt empowered, the tedious parts of their work (sorting data, initial drafting, routine analyses) could be offloaded to algorithms, giving them more time for decision-making and innovation.
- Closing Skill Gaps: AI can also democratize expertise. The customer support example showed novices improved with AI aid. Another case is language translation, AI translation services can enable a businessperson who speaks only English to communicate with a client in Mandarin or Spanish, roughly bridging a skill gap that once required a human translator. While this does pose challenges for professional translators, it also opens opportunities (smaller companies can now do international business without hiring large translation teams, for instance). In general, when AI handles the heavy lifting of knowledge (scanning databases, generating boilerplate content, analyzing trends), it allows non-specialists to achieve results closer to specialists. This can raise overall productivity and potentially create new roles where human judgment plus AI output is what matters.
Crucially, these examples highlight task automation rather than job automation. AI excels at specific tasks: crunching numbers, coding to a specification, generating text or images based on patterns, recognizing patterns in data. But most jobs are an amalgam of dozens of tasks, not all of which are easily automated. Many involve complex human interaction, tacit knowledge, and adaptability. As economist Harry Holzer emphasizes, the future likely won’t be black-and-white where an entire occupation is suddenly done by AI; instead, “every year, AI will get a little better and will replace human work on a certain set of tasks… and if a worker wants to keep their job, they will have to pivot to a different set of tasks that the machine cannot yet do.” In practice, this means continuous learning and adaptation will be the name of the game. The most resilient workers (and companies) will be those who constantly update their skill sets and redefine roles in partnership with AI.
We’re already seeing the emergence of entirely new job categories centered on working with AI. For instance, companies are hiring “prompt engineers”, people who specialize in crafting the right queries and instructions to get the best results from AI models . Roles like AI ethicist, machine learning auditor, or data curator are popping up to ensure AI systems are fair and effective. Professional services firm Accenture suggests breaking down existing jobs into their component tasks to identify which tasks can be done by AI and which require humans, then upskilling employees to work alongside AI for the best outcomes . By doing so, organizations can redesign jobs in a way that maximizes human-AI collaboration, for example, a customer service job might be reimagined as “AI handles basic inquiries and paperwork; human agents focus on complex cases and empathetic connection with customers.” In fact, Accenture estimates that 65% of the time we currently spend on “language tasks” (reading, writing, communicating) could be transformed into more productive activity through AI augmentation . That implies huge efficiency gains if workers are trained to take advantage of AI.
Far from rendering humans obsolete, AI could make human qualities more essential. A striking finding from a 2025 Workday research report: 83% of workers believe AI will actually elevate the importance of uniquely human skills like creativity, empathy, and leadership . The logic is that as AI handles the straightforward or analytical parts of work, the relative value of human insight and interpersonal skills goes up. Indeed, the skills considered least likely to be automated – things like ethical judgment, emotional intelligence, and conflict resolution – are the very skills many organizations now say are the most valuable in employees . Let AI crunch data; humans will design better questions and interpret the nuances. Let AI draft the report; humans will add strategic context and empathetic storytelling. This vision is essentially saying: the future of work is humans and AI working in tandem, each focusing on what they do best. It’s a “centaur” model (to borrow a term from chess, where human–computer teams proved stronger than either alone) applied to every industry. As one tech CEO put it, “By embracing AI for good, we can elevate what makes us uniquely human, our creativity, our empathy, our ability to connect, and build a workplace where these skills drive success.”
Navigating the Transition: Challenges and Strategies
Even with a fundamentally hopeful outlook, we must navigate a potentially rocky transition. The benefits of AI will not be evenly distributed unless we make them so. Without conscious action, we risk exacerbating inequalities – between those who have the skills or capital to leverage AI and those who don’t, and between different demographic groups. A 2023 McKinsey report noted that AI’s automation effects might hit some workers harder than others: roles in office support, customer service, and food service (often lower-paying jobs) are among the most likely to be displaced, and these roles disproportionately employ women and underrepresented minorities . On the flip side, high-skill roles may be more augmented than automated in the near term , meaning well-educated workers could see productivity increases and wage premiums, widening the skill gap. This pattern isn’t new – globalization and past tech booms had similar effects – but AI could intensify it by reaching further into the middle class. Society will need safety nets and bridges: policies to support those displaced and help them retrain into new careers.
Policymakers and thought leaders are actively debating solutions. One bold idea gaining traction is the implementation of a universal basic income (UBI), a no-strings-attached regular payment to all individuals, meant to ensure basic livelihood even if traditional jobs are scarce. The logic is to decouple income from employment, at least partially, in an age where machines create tremendous wealth with less human labor. As a 2025 London School of Economics review notes, “a new social contract is needed to make sure technological progress and human welfare advance together, not at each other’s expense,” and UBI is a promising avenue to achieve that . Trials of UBI around the world (from Finland to Kenya to U.S. pilot programs) have shown it can reduce poverty and stress, though funding such a program at scale remains a challenge . UBI is not a panacea; critics argue it might disincentivize work or prove fiscally unsustainable. However, even tech luminaries in Silicon Valley have endorsed it as a potential buffer if AI truly upends the labor market. Whether through UBI or other means, what Dalio called for seems likely, a “new type of social contract” may be needed , one that might include shorter work weeks, re-skilling stipends, job transition programs, or profit-sharing models to ensure the AI dividends don’t just enrich a few.
For businesses and entrepreneurs, there is also a strategic imperative: adapt or fall behind. Just as companies that ignored the internet in the 2000s were left in the dust, organizations that ignore AI risk obsolescence. But embracing AI is not simply about automating for cost-cutting; it’s about reimagining work to amplify human creativity and insight. Smart companies are already reorganizing teams to maximize human-AI collaboration – for example, pairing domain experts with data scientists and AI specialists, or training all staff on basic AI tool use. They are also revisiting their hiring: instead of replacing departing employees with similar profiles, forward-looking firms are asking, “Can we hire someone with AI expertise, or someone with exceptional interpersonal skills, to complement what our algorithms do?” The future belongs to organizations that can harness the best of both worlds – the speed and scale of AI and the flexibility and empathy of humans.
From an individual perspective, everyone in the workforce can take proactive steps to thrive in the AI era. Here are a few strategies experts recommend, echoing the insights of tech visionaries and futurists:
- Embrace Lifelong Learning: Treat your career as a continuous learning journey. Update your skills regularly through online courses, workshops, and self-directed projects. Learning how to learn is itself a key skill – those who can rapidly pick up new tools (like the latest AI platform) will stay ahead . Don’t be afraid to venture outside your comfort zone; a marketing professional might learn some basics of data analytics, or a finance analyst might pick up some programming. Breadth can be as important as depth when roles are evolving.
- Leverage AI as Your Assistant, Not Your Enemy: Identify AI tools that can make your work more efficient or creative, and master them. Writers are using AI for brainstorming ideas and drafting content; programmers use AI to generate and debug code; salespeople use AI to prioritize leads or personalize outreach. By being the person in your team who is adept with these tools, you make yourself more valuable, not less . This might mean investing time to experiment with AI APIs, generative art programs, or whatever is emerging in your field. Remember that AI is a tool – just as spreadsheets didn’t eliminate accountants but made math faster, AI can handle grunt work and amplify your impact.
- Cultivate Uniquely Human Skills: Double down on the skills AI can’t easily replicate. These include empathy, communication, leadership, teamwork, creativity, and critical thinking. In an AI-rich workplace, your ability to build trust with a client, motivate a team, or come up with an out-of-the-box strategy will set you apart. As one workforce study found, skills like relationship-building, ethical judgment, and conflict resolution are seen as critical for success in an AI-driven economy . Such skills are harder to quantify on a resume, but they shine through in interviews and on the job. Look for opportunities to develop them – whether through public speaking (to hone communication), volunteering or mentoring (to build empathy), or simply soliciting feedback and self-reflection to improve your emotional intelligence.
- Stay Agile and Open to Change: The career ladder of the past (a linear climb in one field) may give way to a “career lattice” – lateral moves, periodic career changes, and hybrid roles. Be open to pivoting as your industry changes. If AI threatens to automate many tasks of your current role, proactively seek the next iteration of your role. For instance, some graphic designers are learning AI image generation tools and rebranding as “AI-assisted designers” rather than competing with algorithms . Many journalists now use AI for research or even to generate basic articles, focusing their energy on high-level analysis and investigative pieces. Don’t cling to a static job description – think in terms of your talents and how they can be applied in new ways.
- Focus on the Big Picture (Problem-Solving and Strategy): AI can provide data and options, but humans still excel at defining which problems should be solved and why. Developing your strategic thinking will make you the person who can see the forest when everyone else sees trees. This might involve learning about domains outside your specialty, understanding business fundamentals, or improving your decision-making frameworks. As AI handles micro-tasks, humans will add most value in macro-judgments. For entrepreneurs especially, the ability to envision how to use AI to create value – identifying unmet needs and imagining new solutions – will be gold. Entirely new business models will emerge from creative applications of AI (just as the internet gave us companies like Uber or Airbnb that reimagined existing services). Train yourself to ask, “How can AI X be used to solve problem Y in my community or market?” The answers could be the seeds of a new venture.
A New Age of Work: Threat or Renaissance?
Standing at this crossroads, it’s clear that AI will fundamentally reshape the future of work. But whether that future is one of widespread prosperity or deepening inequality depends largely on human choices – in business strategy, in government policy, and in individual mindset. Yuval Noah Harari’s warning of an AI-induced “useless class” is a provocative cautionary tale , but it is not an inevitable destiny. It’s a call-to-action to ensure we don’t let millions of people fall by the wayside. We must remember that technology’s impact is not deterministic; it’s guided by how we deploy it. AI might end the era of some jobs, but it could also liberate us from work we hated and open up time and resources to focus on what we find meaningful. As one tech optimist noted, the narrative around AI doesn’t have to center on fear – “we see it as an incredible opportunity… to build a future that prioritizes skills like empathy, ingenuity, and our shared humanity.” In this telling, AI is less a terminator of jobs and more a transformer – terminating tasks that bog us down, while helping us redefine work itself toward something more creative and human-centric.
Getting to that hopeful outcome will require intentional effort. It will require leadership with vision – in companies, to invest in people even as they invest in technology; and in governments, to update education and social support for a new reality. It will require that we, the workforce, embrace change rather than resist it, much as uncomfortable as it can be. And it will demand a willingness to experiment with new ideas (like UBI or novel education models) to ensure no one is left behind. In short, the age of AI could be a perilous time of displacement or the dawn of a new renaissance of human potential. The deciding factor is not AI’s code, but our collective wisdom in wielding it.
As we navigate this transition, perhaps the most important thing to hold onto is the essence of what work provides beyond a paycheck: purpose, connection, growth. If AI takes over mundane tasks, we have an opportunity to reorient work around these human needs. We may find ourselves with more time to solve hard problems, to care for each other, to chase curiosity, or to simply live our lives outside of work. The optimists dare to envision a future where technological abundance gives rise not to idleness, but to a flourishing of human creativity and well-being. The road to get there is undoubtedly challenging – but it is a future worth striving for.
In the words of an ancient proverb often cited in times of great change: “The best time to plant a tree was 20 years ago. The second-best time is now.” The AI revolution has already begun; the best time to prepare was yesterday, but the next best is today. By understanding the forces at play and actively shaping them, we can ensure that AI augments humanity rather than diminishes it. The story of work has always been one of adaptation. This chapter may be the most dramatic yet – but with wisdom and will, it can also be one of our finest, unleashing human talent as never before.
Sources:
- Harari, Yuval Noah. The Guardian, AI’s threat of a “useless class”
- Goldman Sachs Economic Report, Generative AI’s impact on jobs and productivity
- World Economic Forum, Future of Jobs Report 2023, Emerging vs. declining roles, and AI adoption outlook
- Chicago Booth Review (2023), Synthesis of AI labor market studies and historical data
- Dalio, Ray (2023 interview), Perspective on productivity vs. inequality from AI (Moonshots Podcast)
- Brynjolfsson et al. (2023), Study on AI assistance boosting customer support productivity
- Noy & Zhang (2023), Experiment on ChatGPT improving writing efficiency and quality
- Accenture Analysis via WEF, 40% of work hours impacted by LLMs, need for reskilling and task redesign
- Workday Research (2025), Survey finding AI increases focus on meaningful work and human skills
- LSE Business Review (2025), Discussion of UBI as social contract in AI era
