How does AI affect jobs?...

Artificial Intelligence (AI) is rapidly transforming the world of work. From factory floors to corporate offices, AI technologies are automating tasks, augmenting human capabilities, and even creating entirely new roles.
This dual nature – replacing some jobs while generating others – has sparked both excitement and concern across the globe.

In fact, the International Monetary Fund notes that AI will affect almost 40% of jobs worldwide, with some tasks performed by machines and others enhanced by AI assistance. As we stand on the brink of this technological revolution, it’s crucial to understand how AI is impacting jobs across industries and what it means for the future of work.

AI and Job Displacement: Automation Threats

One of the biggest worries about AI is its potential to displace workers through automation. Advanced algorithms and robots can now perform many routine or repetitive tasks faster and more cheaply than humans.

A widely cited analysis by Goldman Sachs estimated that generative AI could expose 300 million full-time jobs to automation globally, roughly 9% of the global workforce. Many of these at-risk jobs are in areas like data processing, administrative support, and routine manufacturing.

For example, decades of industrial robotics have already reshaped manufacturing by taking over assembly line work and displacing human workers in factories. In the United States alone, automation is estimated to have eliminated 1.7 million manufacturing jobs since 2000. Now, AI’s reach is extending into white-collar domains that were previously considered safe from automation.

AI software “bots” and machine learning models can analyze data, generate content, and interact with customers. This raises the threat of automation in clerical and service roles. Clerical and administrative jobs (like data entry clerks or payroll processors) are among the first in line to be automated by AI.

In customer service and retail, we already see AI making inroads: chatbots handle routine inquiries and self-checkout kiosks reduce the need for cashiers and bank tellers.

Projections show significant declines in these roles – for instance, bank teller employment is projected to shrink by 15% by 2033, and cashier jobs by about 11% in the same period. Even in sales and marketing, AI tools can perform tasks like product recommendations and basic copywriting.

A Bloomberg analysis found that AI could potentially replace over 50% of tasks performed by jobs such as market research analysts and sales representatives, while higher-level managerial tasks are far less automatable. In short, roles with highly repetitive or routine components are vulnerable to being taken over by intelligent machines.

Importantly, this wave of AI-driven automation is not just theoretical – it’s already underway. Companies have begun integrating AI to streamline operations, sometimes at the expense of entry-level employees.

Recent surveys found that about 23% of companies have already replaced some workers with ChatGPT or similar AI tools, and nearly half of businesses using such AI say it has directly taken over tasks previously done by employees.

There have even been cases of AI-related layoffs; for example, a spike in AI-driven job cuts was reported in early 2023 as firms adopted chatbots to handle work previously done by humans. The entry-level job market is feeling the squeeze: many routine duties that junior staff used to handle (data gathering, basic analysis, drafting reports, etc.) can now be automated, which means fewer “foot-in-the-door” opportunities for new graduates.

As AI continues to improve, experts warn that the scope of automation could expand. Some studies project that by the mid-2030s, nearly 50% of jobs could be at least partly automated if AI capabilities keep advancing at the current pace.

Yet, it’s important to remember that AI-driven job loss tends to happen task by task, rather than all at once. In many cases, AI automates certain duties within a job (for instance, generating routine reports), rather than eliminating the entire occupation outright.

This means workers in impacted roles may transition to focusing on higher-level or more human-centric aspects of their jobs, rather than simply being replaced overnight.

Economists often compare this to past technological shifts – while ATMs automated basic banking transactions, bank employees shifted toward relationship management and sales. Similarly, if AI handles the “busy work,” humans might concentrate on strategic, creative, or interpersonal tasks.

Nonetheless, the short-term disruption from AI is very real for many workers, and its effects are being felt across a wide range of industries.

AI as a Job Creator: New Roles and Opportunities

Despite the challenges, AI is not only a job-killer – it is also a powerful job creation engine. History has shown that major technological advances tend to create more jobs in the long run than they destroy, and AI appears poised to follow this pattern.

The World Economic Forum’s latest analysis indicates that technological advancements (including AI) will create 170 million new jobs by 2030, while displacing about 92 million existing roles. This works out to a net gain of roughly 78 million jobs globally over the decade.

In other words, the future of work may see plenty of new opportunities – if workers have the skills to seize them.

Many of the new jobs emerging are those that either build or heavily leverage AI technologies. There is surging demand for roles like AI specialists, data scientists, machine learning engineers, and big data analysts. These occupations barely existed a decade ago but are now among the fastest-growing professions.

In fact, tech-focused roles dominate lists of jobs with the highest growth, reflecting how organizations across all sectors need talent to develop, implement, and manage AI systems.

Beyond the tech sector, entirely new categories of work are appearing to support the AI ecosystem. For example, we’ve seen a rise of positions such as AI model trainers, prompt engineers, AI ethicists, and explainability experts, which are roles dedicated to training AI systems, crafting AI inputs, addressing ethical concerns, and interpreting AI decisions.
Likewise, the gig economy around AI data is booming – think of all the data annotators and labelers who help train algorithms (a job that didn’t exist until recently).

Crucially, AI can also boost job growth in fields outside of tech by increasing productivity and lowering costs. Consider healthcare: AI tools can assist doctors by analyzing medical images or suggesting diagnoses, allowing medical staff to serve more patients – which can lead to hiring more healthcare workers to meet increased demand.
Rather than replacing doctors or nurses, AI acts as a force multiplier, helping them work more efficiently.

Indeed, roles in the care economy are projected to grow significantly in the coming years because of AI’s support. For example, the need for nurses, personal care aides, and elderly caregivers is rising as populations age, and AI provides supportive tools (like health-monitoring apps or robotic assistants) that enable these professionals to be more effective.
The net effect is higher demand for such human-centric roles, not less. The World Economic Forum found that health and education jobs (nurses, teachers, social workers, etc.) are likely to see strong growth through 2030, partly as AI augments these services.

Even in industries where AI is making inroads, it often creates new complementary jobs. For instance, the spread of automation in manufacturing increases the need for maintenance technicians and robotics engineers to install and oversee machines.

E-commerce growth fueled by AI logistics algorithms has spiked demand for warehouse workers and delivery drivers – roles that are among the largest growing job categories this decade.

In creative fields, generative AI can produce content or designs, but humans are still needed to direct the creative vision, edit and refine AI outputs, and market the products. This dynamic of AI working alongside humans can make workers more productive and companies more competitive, which often leads to business expansion and more hiring.

The global consulting firm PwC found evidence that industries adopting AI heavily actually see faster job growth and rising wages, as AI helps human workers deliver more value.

In essence, AI has the potential to “make people more valuable, not less,” even in jobs with many automatable tasks. When used wisely, AI can free workers from drudgery and empower them to focus on higher-impact work, spurring innovation and new business models that create additional employment.

Largest projected job growth and decline by 2030. This chart from the World Economic Forum’s Future of Jobs Report 2025 illustrates the occupations expected to see the greatest job gains and losses globally by 2030.

On the left, we see jobs in areas like agriculture, transportation, technology, and the care economy surging in demand. For example, farmworkers are projected to increase by tens of millions as the world invests in food security and green transitions, and delivery drivers and software developers also rank among the top growing roles.

On the right, the jobs expected to decline the most are largely those with routine, repetitive tasks that are ripe for automation. Roles such as data entry clerks, secretaries, bank tellers, and cashiers show some of the steepest drops, reflecting how digitalization and AI are streamlining clerical work and basic transactions.

It’s important to note that while some jobs will vanish, many of the workers in those roles will transition to new positions – often the growing jobs on the left side of the chart.

The key takeaway is that AI will fundamentally reshape the job mix in the economy. Overall employment is still expected to grow, but there will be clear winners and losers among occupations. This puts a spotlight on the need for reskilling and career transitions as the nature of work evolves.

Industry-Wide Impact: All Sectors Feeling the Change

AI’s influence on jobs is pervasive across virtually every industry. Early on, many assumed AI would only disrupt tech companies or highly digital businesses, but we now know the impact is much broader.
From manufacturing to healthcare, from finance to agriculture, no sector is completely immune to AI’s effects. However, the nature and extent of the impact do vary by industry:

• Manufacturing and Logistics: This sector has seen extensive automation for years, and AI is accelerating that trend. Robots and AI-guided machines handle assembly, welding, packing, and inventory management in factories and warehouses.
  This has reduced demand for some manual labor jobs on production lines. For instance, auto manufacturers now use AI-driven robots for tasks like painting and quality inspection, resulting in leaner production teams.

  At the same time, manufacturers are hiring more robotics engineers, AI system integrators, and maintenance technicians to keep these automated systems running. AI is also optimizing supply chains – predicting demand, managing inventory, and routing shipments – which boosts productivity and can lead to growth in roles like logistics coordinators and data analysts.
  So, while traditional assembly-line jobs decline, new technical and supervisory jobs are rising in their place.

• Finance and Banking: The finance industry is undergoing an AI-driven transformation in how it operates. Algorithmic trading systems have automated many stock market and forex trading jobs that once employed scores of analysts.
  Banks and insurance firms are using AI for fraud detection, risk assessment, and underwriting, automating tasks that used to require large back-office teams.

  For example, credit analysts and insurance underwriters are increasingly assisted or even replaced by AI models that can evaluate financial risk in seconds. In customer-facing services, banks have rolled out AI-powered chatbots to handle routine customer inquiries, reducing the need for large call center staffs.
  These efficiencies mean fewer traditional roles (like bank tellers or loan officers), but there is growing demand for financial tech developers, data scientists, and cybersecurity experts to build and secure these AI systems.

  Additionally, financial advisors and wealth managers are not obsolete; instead, they are using AI tools to better serve clients, focusing on complex advisory work while delegating number-crunching to algorithms. The finance sector is a prime example of AI augmenting high-skill jobs (making analysts and advisors more effective) even as it automates away some support roles.

• Retail and Customer Service: Automation in retail is changing the job landscape for clerks, cashiers, and sales representatives. We’ve seen an explosion of self-checkout machines and online shopping bots that diminish the need for checkout staff and salespeople in brick-and-mortar stores.
  Large retailers are experimenting with AI-driven just-walk-out shopping experiences with no human cashiers. This has contributed to a decline in traditional retail jobs, with cashier positions expected to continue falling.

  In call centers and customer support, AI chatbots and virtual assistants handle FAQ-type queries and basic troubleshooting, allowing one human agent to oversee multiple AI interactions at once. This means companies can serve more customers with fewer support staff, changing the employment calculus.
  However, customer service isn’t disappearing – it’s evolving.

  The nature of retail/customer service jobs is shifting toward roles like customer experience management, handling escalations (more complex issues that AIs can’t solve), and providing in-person services that remain in demand. Also, e-commerce growth (partly driven by AI recommendation engines) has created jobs in fulfillment centers, delivery, and digital marketing. So, while storefront roles decline, new jobs behind the scenes in e-commerce logistics are booming.

• Healthcare: AI’s impact on healthcare jobs is largely augmentative rather than replacing. AI is being used to analyze medical images (radiology), suggest treatment plans, transcribe medical notes, and even monitor patient vitals with smart devices.
  These technologies assist doctors, nurses, and technicians, helping them make faster and sometimes more accurate decisions.

  For example, an AI might flag early signs of a disease on an X-ray for a radiologist to review, saving time. This means doctors can treat more patients, and nurses can automate routine charting tasks to focus more on patient care.
  Far from cutting healthcare jobs, the demand for healthcare professionals is actually rising globally, thanks in part to aging populations and also because AI enables scaling up services.

  Nursing and other care roles are projected to grow significantly through the end of the decade. Rather than seeing AI as a threat, many view it as a tool that frees up medical staff for the empathetic, human-centric aspects of care that machines can’t handle.

  That said, some specialized roles like medical transcriptionists have seen declines (AI speech-to-text can do transcription), and eventually fields like diagnostic radiology or pathology could be transformed as AI takes on more analytical duties.
  The likely scenario is that healthcare workers will work alongside AI – with new roles emerging in healthcare IT, AI system management, and data analysis to support patient care.

• Education and Professional Services: Sectors like education, legal services, and consulting are also adapting to AI. In education, AI tutoring systems and automated grading software can reduce teachers’ workload on administrative tasks, but teachers are still needed to provide mentorship, critical feedback, and social-emotional support to students.
  Rather than replacing teachers, AI helps them personalize learning – for instance, by analyzing which concepts a student struggles with and suggesting targeted practice.

  This could change teachers’ roles somewhat (more facilitators than lecturers) but does not eliminate the need for educators. In fields like law, AI can draft routine contracts or do document review at high speed (e-discovery), reducing the hours junior lawyers or paralegals spend on drudge work.
  As a result, some entry-level legal jobs are fewer, but lawyers can focus more on complex analysis, courtroom strategy, and client interaction. New legal tech jobs (like legal AI specialists) are emerging as well.

  Similarly, in marketing and media, AI can generate basic content or ads, but human creatives then refine and elevate that content – and creative directors, editors, and marketing strategists remain in demand.
  Across professional sectors, AI is acting as a super-assistant: taking care of repetitive chores and enabling skilled professionals to do more in less time.

In summary, all industries are integrating AI in some form, and job profiles within those industries are shifting accordingly. The transformation extends beyond the tech sector itself.

Jobs that involve routine physical work or information processing are declining, whereas jobs that involve creative thinking, complex human interaction, or oversight of AI systems are growing.

The challenge for each industry is managing this transition – helping current workers move into new roles or upgrade their skills as their old roles evolve or disappear.

The Changing Skills Landscape: Adapting to an AI-Powered Workplace

As AI changes jobs, it also changes the skills needed to thrive in the workforce. In the AI era, there is a premium on both advanced technical skills and strong human-centric skills.

On the technical side, skills in AI, machine learning, data analysis, and digital literacy are increasingly important across many jobs.

Even roles that aren’t “in tech” now often require workers to comfortably use AI-driven tools or interpret data. Employers expect that by 2025, a whopping 39% of core skills needed across occupations will change due to technology and other trends.

In fact, the pace of skill change is accelerating – one estimate suggests nearly 40% of the skills workers use on the job will be different by 2030, up from a 34% change forecast just a few years prior.

This means that lifelong learning and upskilling have become essential. Workers can no longer rely on a static skillset acquired in early career; continuous training is the new normal to keep up with AI-driven changes.

Interestingly, even as demand for high-tech skills grows, employers are placing even greater emphasis on “human” skills that AI can’t easily replicate.

Critical thinking, creativity, problem-solving, communication, leadership, and emotional intelligence are all highly valued in an AI-rich workplace.

In a job market flooded with intelligent machines, what sets humans apart are things like creativity, adaptability, empathy, and strategic thinking. In fact, analyses of job postings show that 8 of the top 10 most-requested skills are non-technical attributes like teamwork, communication, and leadership.

These durable skills remain in demand precisely because AI lacks true creativity and emotional understanding.

For example, an AI can crunch numbers and even draft a report, but a human manager is needed to interpret the results, make judgment calls, motivate a team, and innovate new approaches.

Therefore, the ideal worker of the future is often described as a hybrid: tech-savvy enough to leverage AI tools, but also strong in interpersonal and cognitive abilities that machines don’t have.

Companies recognize the looming skills gap and are responding. A majority of employers (around 85%) report that they plan to increase investment in workforce upskilling and reskilling programs to meet the challenges of AI.

Upskilling can range from formal training courses in data science or AI, to on-the-job mentoring in using new software, to encouraging employees to pursue online certifications (for instance, in prompt engineering or AI ethics).

The push for upskilling is global: from advanced economies to developing ones, businesses and governments are launching initiatives to teach digital skills and help workers transition into new roles. We’ve seen efforts like coding bootcamps, digital literacy campaigns, and partnerships with online learning platforms (e.g., Coursera, which has reported surging enrollments in AI-related courses).
The rationale is clear – companies that fail to bridge the skills gap risk falling behind.

In fact, 63% of employers say that skills gaps are a primary barrier to adopting new technologies. Without the right skills in their workforce, firms cannot fully implement AI and other innovations. This has made talent development a strategic priority.

For individual workers, the implication is to embrace continuous learning. Young people entering the job market are encouraged to build both strong technical foundations (like understanding how AI and data analytics work) and to cultivate their creative and social skills.

Mid-career workers, who might see parts of their job taken over by AI, are seeking retraining to pivot into emerging roles.

There’s also growing emphasis on STEM education and digital skills in schools worldwide, preparing the next generation for an AI-driven economy. And for those whose jobs are at high risk, learning new skills is often the ticket to moving into a more secure career path.

The encouraging news is that various studies suggest workers can be resilient and adaptable – given proper training, many can transition successfully.

For example, one study showed that AI tools can help less experienced workers become productive faster, indicating that humans plus AI can outperform either alone. Thus, the future belongs to those who collaborate with AI: acquiring the skills to use AI as a tool and focusing on the uniquely human talents that complement it.

Global Perspective: Inequality, Policy, and the Future of Work

The impact of AI on jobs is not uniform around the world. There are clear differences across countries and demographic groups, raising concerns about widening inequalities.

Advanced economies (like the U.S., Europe, Japan) are both the most aggressive adopters of AI and the most exposed to its disruptions.

IMF research found that about 60% of jobs in advanced economies could be impacted by AI in the coming years, compared to only 40% in emerging markets and 26% in low-income countries. This is because richer nations have more jobs in the formal sector and in digital or high-skilled occupations, which AI can penetrate.

In lower-income countries, more of the workforce is in manual labor, agriculture, or informal jobs that are less immediately affected by current AI technologies. However, this doesn’t mean emerging economies are safe from AI – instead, they might miss out on AI’s benefits initially (due to less infrastructure and talent to adopt it) and then face disruption later as AI tech matures.

There’s a risk that AI could exacerbate the gap between countries, with tech-savvy nations boosting productivity and wealth, while others lag behind.

To address this, global organizations emphasize the need for inclusive AI strategies, where developing nations invest in digital infrastructure and skills now to not be left behind.

Within countries, AI could also widen inequality if not managed carefully. Typically, higher-skilled and higher-income workers are better positioned to benefit from AI – they can leverage algorithms to become more productive and command even better pay.

In contrast, lower-skilled workers doing automatable tasks might see their jobs eroded or their wages stagnate.

For instance, an AI engineer or a manager who uses AI might enjoy higher productivity (and salary), whereas a routine office clerk might be made redundant. Over time, this dynamic could concentrate wealth and income even more at the top.
The IMF warns that in most scenarios AI is likely to worsen overall inequality, absent intervention.

We may see more polarized labor markets, where a segment of well-educated workers thrives alongside AI, while another segment of workers faces unemployment or shifts into lower-paying service gigs. There’s also a generational aspect – younger workers may adapt more easily to AI tools, whereas older workers might struggle to reskill, potentially leading to age-based divides.

And as noted earlier, even gender dynamics could shift: historically, automation hit male-dominated manufacturing jobs hardest, but AI might affect female-dominated clerical and white-collar jobs more if, say, secretarial and administrative roles are heavily automated.

These complexities mean that policymakers have a critical role to play in smoothing the transition.

Governments, educational institutions, and businesses will all need to collaborate on policies that help workers adjust to AI’s impact. A top priority is strengthening the social safety net – this includes unemployment benefits, retraining programs, and job placement services for those displaced by technology.

Ensuring that someone who loses a job to AI has the support and opportunity to learn new skills and find good work is key to preventing long-term joblessness or poverty.

The International Labour Organization (ILO) suggests that because most jobs will be transformed rather than fully eliminated, there is a window to proactively manage the transition. One positive finding from the ILO’s research is that globally only about 3% of jobs are in occupations at highest risk of complete automation by generative AI, whereas one in four workers may see some of their tasks changed by AI.

This implies that if we act swiftly, we can adapt jobs around AI (through retraining and reorganizing work) instead of expecting mass unemployment.

Policy measures like encouraging apprenticeships, vocational training in tech skills, digital literacy programs, and even lifelong learning accounts (so workers can fund their continual education) are being explored in many countries.
For example, the European Union has launched initiatives focusing on a “skills agenda” to prepare workers for the digital and AI-driven economy.

Another policy angle is regulating AI’s deployment to avoid reckless job disruption. Some have proposed incentives for companies that retrain or redeploy workers rather than laying them off when automating tasks.
Public investment in job creation – such as in the green economy or care sectors – can also offset AI-driven losses by providing new employment avenues (as seen with care jobs and green energy jobs rising).

Education systems are being rethought to emphasize flexibility, STEM, and critical thinking from an early age, so the future workforce is AI-ready. In addition, there’s discussion of more radical ideas like universal basic income (UBI) as a cushion for a future where job instability might increase – though UBI remains controversial and not widely implemented, it reflects the level of concern about AI’s potential to upend traditional employment.

The IMF Managing Director, Kristalina Georgieva, stresses that a “careful balance of policies” is needed to leverage AI’s benefits while protecting people.

This includes not only training and safety nets but also strong labor market institutions – ensuring workers have a voice in how AI is adopted, updating labor laws to account for AI (for instance, gig work facilitated by AI algorithms), and maintaining ethical guidelines so that AI is used in fair ways.

Finally, it’s worth noting that AI itself can become part of the solution. Just as AI is disrupting jobs, it can also be used to help workers and policymakers respond. AI tools can assist in job matching (pairing people to new jobs or training programs more efficiently), provide personalized learning platforms, and forecast labor market trends so that education and training can target future skill needs.

Some governments are using AI to analyze which regions or industries are most at risk from automation, then directing funds accordingly to those areas.

In short, while AI poses challenges, it can also be an ally in crafting a future of work that is more productive and hopefully more humane – if we make the right choices. The era of AI is upon us, and with thoughtful action, it can be steered toward broad-based prosperity rather than inequality.

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The Risks of Using AI

AI and data security issues

AI’s impact on jobs is profound and multifaceted. It is eliminating certain roles, dramatically altering many others, and at the same time creating new opportunities for those with the right skills.
In every industry, the balance between humans and machines is shifting: AI performs more of the repetitive grind, while humans are pushed to focus on higher-level functions.

This transition can be unsettling – for individual workers whose livelihoods are threatened, and for societies grappling with how to ensure no one is left behind. Yet, the story of AI and jobs is not simply one of dystopian replacement. It’s also a story of augmentation and innovation.
With AI handling routine tasks, people have the chance to engage in more meaningful and creative work than before.

And as AI spurs economic growth (potentially adding 7% to global GDP in the coming years according to some estimates), this growth can translate into job creation in fields we can’t even imagine today.

The net outcome – whether AI leads to mass unemployment or an age of abundance – will depend on how we manage the transition. Investing in people is paramount.

This means equipping workers with the skills to work alongside AI, redesigning education to be forward-looking, and supporting those who are disrupted.

Companies must act as responsible stakeholders, embracing AI in ways that enhance their workforce rather than just cutting costs. Governments must craft policies that encourage innovation but also provide safeguards and training for workers.

International cooperation may be required too, to help developing nations adopt AI beneficially and prevent a widening global digital divide.

In the end, AI is a tool – a very powerful one – and its impact on jobs will be what we collectively make of it. As one report put it, “the AI era is upon us, and it is still within our power to ensure it brings prosperity for all”.

If we rise to the challenge, we can harness AI to unlock human potential, creating a future of work that is not only more efficient but also more rewarding and humane.

The transition may not be easy, but with proactive effort, workers of today can become the innovators of tomorrow in an AI-driven world. The impact of AI on jobs is massive – but with the right vision and preparation, it can be a catalyst for new opportunities and a better working life for millions.