How AI Is Transforming Careers and Other Trends in Jobs and Skills
The following contribution is from the World Economic Forum’s Jobs and the Future of Work section.
Author: Till Leopold, Head of Jobs, Wages and Job Creation, World Economic Forum
As AI transforms careers, entry-level positions could face increasing threats.
Our Impact
What is the World Economic Forum doing to drive action on jobs and the future of work?
Overview
Explore and monitor how Artificial Intelligence is impacting economies, industries, and global issues.
Are Entry-Level Jobs Dying?
For decades, entry-level positions have provided essential training for newcomers entering the workforce. From finance to journalism, junior staff have traditionally approached the grind as a rite of passage, as much as a development opportunity.
But as AI transforms the professional ladder, these early entry-level opportunities could be increasingly at risk, according to Bloomberg.
International Workers’ Day, on May 1, commemorates the labor movement’s struggle for workers’ rights. AI stands as one of the most significant challenges—and opportunities—facing the current job market.
Technological change, the green transition, economic uncertainty, geoeconomic fragmentation, and demographic shifts are transforming the labor market. Image: World Economic Forum
While 170 million new jobs are projected to be created this decade,
the rise of AI-based tools threatens to automate as many roles as it creates, especially for entry-level administrative positions.
Bloomberg concludes that AI could replace more than 50% of the tasks performed
by market research analysts (53%) and sales representatives (67%), compared to only 9% and 21% for their managerial counterparts, respectively.
Whether by narrowing entry-level positions or making jobs that previously required specialized skills more accessible, estimates suggest that AI could impact nearly 50 million US jobs in the coming years.
How AI might be closing the door to talent…
The Forum’s Future of Jobs Report 2025 reveals that 40% of employers anticipate reducing their workforce if AI can automate tasks.
Technology, in general, is projected to be the most disruptive force in the labor market, with trends in AI and information processing technology expected to create 11 million jobs while displacing another 9 million.
As entry-level positions shrink, salary expectations are also changing, with those who remain in the workforce expected to take on AI-enabled roles for less money. A recent survey revealed that 49% of Gen Z Americans seeking employment believe AI has diminished the value of their college education in the job market.
At the same time, US companies are expanding their operations in India, where skilled professionals can be recruited at significantly lower costs, notes Charter, further intensifying competition for office jobs.
However, this could create a talent pool problem, with significant implications for social mobility and equitable representation, according to Bloomberg.
…while opening new doors
The AI generation could democratize access to employment, facilitating the development of technical knowledge and skills that have historically excluded skilled workers, according to Charter.
Instead of completely eliminating entry-level opportunities, companies could leverage AI to train the next generation of senior professionals. From eliminating billable hours at law firms to a greater emphasis on apprenticeship programs, traditional structures could be redefined.
As the AI generation becomes more integrated into the workforce, companies will need to invest in significant training initiatives to prepare their employees for the AI-driven economy.
Following global macroeconomic trends, AI is poised to transform the traditional career ladder, potentially
putting entry-level jobs at risk. However, both employers and employees can prioritize the training, education, and level playing field that come with harnessing AI’s potential.
To boost employment amid ongoing economic restructuring, China plans to extend key unemployment insurance policies and job retention incentives until 2025.
President Donald Trump has signed an executive order directing the Departments of Labor, Education, and Commerce to focus on employment needs in emerging industries. The goal is to support more than one million apprenticeship programs annually to enhance job training in skilled trades.
With the digital and green transitions expected to transform the labor market, the European Commission has announced its «Skills Union» plan to secure the future of education and training systems across the bloc.
Youth employment in South Korea has experienced its most significant decline in over a decade. With a reduction of 98,000 in the number of workers aged 25 to 29 in the first quarter of 2025, this marks the country’s steepest drop in 12 years. Investors are showing confidence in regions with intensive use of AI, as a new study reveals that countries with more AI job openings experience lower returns on municipal bonds and increased tax revenue.
The AI Paradox and Qualification Requirements: The Competency-Based Hiring Revolution
The following contribution comes from the Institute for Employment Studies website and is authored by Nick Litsardopoulos, Research Economist (Fellow).
The impact of AI on qualification requirements presents an interesting paradox that varies significantly across sectors and jobs.
However, what seems similar across all industries and occupations is the need to become familiar with AI technologies and tools. The data reveals a complexity that could indicate the advances transforming hiring practices across the board.
The use of AI systems and process automation is impacting recruitment for both job seekers and hiring organizations. Advertisements from recruiters for AI agents are becoming increasingly common, as are AI tool advocates who are urging job seekers to use these tools more to increase their chances of being hired. It’s clear how someone’s chances of getting hired can improve if an AI agent reads a job application written by someone else.
In a recent interview with Bloomberg, Marc Benioff, CEO of Salesforce,
argued that his company’s AI agents already complete between 30% and 50% of the task, and that this figure will continue to increase.
If all these tasks at Salesforce, now performed by AI agents, were previously done by graduates in technology, marketing, or business administration, then perhaps there will be fewer jobs available for graduates than for recent graduates?
AI agents can already perform entry-level tasks that until recently were done by recent graduates.
30% Automated by 2030
According to McKinsey’s «A New Future of Work» report, 30% of current working hours could be automated by 2030, resulting in an estimated 12 million occupational transitions in Europe by 2030.
The report mentions that organizations plan to focus on retraining workers rather than hiring new ones. Therefore, skills-based development appears to be a key factor in the era of artificial intelligence tools, rather than traditional formal qualifications.
However, these increasingly sophisticated digital systems require higher skill levels to operate. A paradox arising from the spread of AI technologies across industries is that, as AI capabilities increase and allow tasks to be completed by lower-skilled employees, at the same time, AI tools become more capable and sophisticated, requiring more highly skilled employees.
Both More and Less Experience as a Result of AI
Recent evidence shows that while automation that lowers experience requirements allows less experienced workers to enter the workforce, automation that raises requirements increases the demand for more experienced workers.
We observe that the UK exhibits an exceptionally pragmatic stance regarding formal qualifications. Competency-based recruitment is gaining popularity across the UK, as employers increasingly focus on applicants’ skills and potential, rather than solely on their academic qualifications.
The UK has invested heavily in modern apprenticeship programs, creating viable pathways to skilled employment without traditional university routes.
This has been particularly successful in sectors such as engineering, information technology, and financial services. This cultural foundation may have created fertile ground for AI-driven changes to take root more easily than in highly skilled markets. Using data from the Adzuna intelligence portal, we examined the qualifications required in the overall UK labor market and in several key occupational sectors. In the UK overall, we observed that demand for Real Qualifications Framework (RQF) Level 6, i.e., a higher education (HE) degree, has decreased, as has demand for RQF Level 8, i.e., doctoral qualifications. However, demand for master’s degrees (Regional Qualifications Framework Level 7) increased during the same period, along with demand for RQF Levels 4-5, which cover vocational/higher education qualifications and lower-level higher education certificates or diplomas (rather than bachelor’s degrees), and RQF Level 2, which covers Grade 4 or higher GCSEs. Interestingly, Regional Qualifications Framework Levels 1 (most of the basic qualifications available in the UK) and 3 (the A Levels) also declined in the last 12 months analyzed.
Therefore, in the UK in general, the demand for qualifications is quite heterogeneous. However, when considering the evidence of a skills-based labor market—that is, the skills required for jobs in a labor market experiencing an increasingly rapid diffusion and application of AI tools and systems automation—the situation may not be so heterogeneous.
Recent data suggests that new employees using AI agents performed as well as employees with more than six months of experience. It appears that AI agents tend to enhance the skills of less experienced employees, helping them learn and perform tasks at a higher level than would be expected. Nevertheless, more experienced employees benefit the most from leveraging the capabilities of AI tools.
It is possible that hires with advanced vocational/higher education qualifications (i.e., Level 4-5 qualifications of the Regional Qualifications Framework) who use AI tools can perform (or at least are expected to perform) at the same level as employees with a bachelor’s degree (i.e., Level 6 of the Regional Qualifications Framework). Similar expectations could explain the declining demand for doctoral degrees and the increasing demand for master’s degrees, or the declining demand for A-level qualifications and the increasing demand for GCSEs. Indeed, there is a trend toward the disappearance of demand for some mid-level qualifications when the knowledge or experience gap can be bridged by using AI tools (e.g., AI agents).
Analyzing some of the major professional sectors, the demand for qualifications shows significant differences that are likely related to the specific skills requirements of each sector. For example, job postings for Education and Teaching positions show a higher demand for RQF level qualifications, and even higher demand for RQF level 7 qualifications, compared to the overall demand. This is likely directly related to the minimum requirements for teaching positions, which require a bachelor’s degree or higher. This demand could also be related to the increased demand for teachers in the UK.
The sales sector is one of the UK’s largest employers. Looking at changes in the demand for qualifications required in job offers, we see that Level 6 of the Real Qualifications Framework (i.e., a bachelor’s degree) has increased. In contrast, the demand for all other required qualifications has decreased (Level 1 of the Real Qualifications Framework has remained stable, but its share is negligible).
Recent changes in the demand for qualifications are most dramatic in the hospitality and catering sector. The difference in required qualifications reveals a notable increase in Regional Qualifications Framework (RQF) Level 2 qualifications (i.e., Grade 4 GCSEs or higher) and also in RQF Level 3 qualifications (i.e., A Levels), while there has been a notable decrease in the qualifications required for RQF Levels 4-5, 7, 8, and 1. Demand for RQF Level 6 qualifications (i.e., a Bachelor’s degree) has remained stable over the period. As in other sectors, higher qualifications appear to have given way to lower ones. It can be argued that the hospitality sector has a lower demand for employees with high-level qualifications.
If recent changes in skills demand are linked to advances in artificial intelligence and high technology, it may be interesting to analyze the situation in IT occupations. Analyzing job postings in this sector, we observe that demand for qualifications has increased for levels 6 and 8 of the Regional Qualifications Framework (RQF), but has decreased for all other qualifications, except for RQF level 1, which has remained unchanged but represents only 0.2% of the demand. Undoubtedly, the most sought-after qualification in IT job postings is RQF level 6.
The Apprenticeship Renaissance
A central aspect of Britain’s unique approach is the reinvention of apprenticeship, which has created robust alternatives to university education, precisely as AI makes them more viable.
The UK’s modern apprenticeship system has evolved far beyond traditional trades to encompass digital skills, financial services, and emerging technology sectors. These programs combine practical work experience with targeted training, producing immediately productive, AI-ready workers. Skills-based recruitment could gain traction across the UK as employers look to leverage British government apprenticeship programs.
Government investment in apprenticeship has been substantial, with initiatives encouraging employers to develop programs aligned with emerging skills needs. This has created pathways from high school graduation to university-equivalent qualifications, facilitating career progression without traditional university routes. The apprenticeship levy system incentivizes large employers to invest in training, creating a feedback loop that benefits both businesses and workers. The timing is crucial, given McKinsey’s analysis indicating that up to 30% of current working hours could be automated by 2030, and that Europe will require up to 12 million occupational transitions. The learning model seems particularly well-suited to the AI era, as it prioritizes continuous learning and practical application over theoretical knowledge.
Work Qualifications in Great Britain
The UK labor market presents a fascinating case study of how advances in artificial intelligence are transforming qualification requirements, revealing trends that are both aligned with and distinct from global trends. The resulting landscape is, in some ways, heterogeneous: a country already moving towards skills-based recruitment in some sectors, while in others, the demand for traditional university education has increased. It is likely that, as the implementation of AI reduces experience requirements in some sectors, allowing for the hiring of lower-skilled employees, in other sectors with higher experience requirements, AI technologies will increase the demand for expert employees.
Sectors with a high degree of in-person work and manual labor will find suitable employees among those without university degrees, while other sectors will continue to demand employees with undergraduate and postgraduate qualifications. The UK may be experiencing a demographic shift similar to that of the US, where the gap between manual and administrative jobs continues to widen, both in terms of demand and wages. As young people opt for studies that offer a pathway to higher-paying jobs in technology or engineering, other employment routes, such as internships, are likely to serve as entry points to lower-paying jobs in hospitality, caregiving, and other more manual or in-person roles.
AI at Work
The following contribution comes from the CNBC portal, which describes itself as follows: CNBC Make It is a financial wellness publication that offers practical advice and engaging storytelling.
Our goal is to help you be smarter and more successful with your money, work, and life.
Through our articles, newsletters, digital videos, TV shows, events, and online courses, we provide information and inspiration to help you navigate life’s biggest milestones, from landing your dream job to starting a business, investing in your future, and buying a home.
Author: Ernestine Siu. Ernestine Siu is a CNBC correspondent covering startups, venture capital, entrepreneurs, and how Generation Z and millennials earn and spend their money in the Asia-Pacific region and beyond.
The rise of artificial intelligence could make college degrees obsolete: Upgrade your AI skills or get left behind, says one expert.
Business professionals. A group of multiethnic businesspeople analyze data on a computer while working as a team in the office.
“Rapid skill change and knowledge turnover may mean that academic degrees become outdated more quickly,” according to PwC’s 2025 Global AI Jobs Barometer.
Employer demand for academic degrees is declining for all jobs, but more rapidly for jobs exposed to artificial intelligence, according to the 2025 AI Jobs Barometer report by the professional services firm PwC, published last week.
“AI helps people quickly develop and master specialized knowledge… which could diminish the relevance of formal qualifications,” according to the report, which analyzed nearly one billion job postings and thousands of financial reports from companies across six continents.
Technology is also driving a rapid turnover of the skills
and knowledge workers need to succeed, which could mean academic degrees become obsolete more quickly, the report added.
In fields exposed to AI, what matters more and more is what people can do today, not what they studied in the past.
PwC’s 2025 AI Jobs Barometer
Notably, the skills employers are seeking are changing 66% faster in occupations most exposed to AI, such as financial analyst, compared to those least exposed, such as physical therapist. This is up from 25% last year, according to PwC data.
“For workers, a greater emphasis on skills over academic degrees in hiring can help democratize opportunities, opening doors for those who lack the time or resources to obtain academic qualifications,” the report states. «In fields exposed to AI, what matters more and more is what people can do today, not what they studied in the past.»
Are degrees becoming obsolete?
Today, education is no longer limited to formal institutions or universities, as it can be learned using AI tools and LLMs (Large Language Models), Joe Atkinson, global head of AI at PwC, told CNBC Make It. To adapt and secure your career future in the changing job landscape, he suggested improving your AI skills from home.
“I think people’s ability to access vast amounts of knowledge is amplified in this age of AI,” Atkinson said. This is giving rise to a new kind of economy where “the bar is set higher for everyone, because access to knowledge will be greater.”
The reality is that we shouldn’t fear technology. We need to embrace it.
Joe Atkinson, Global Head of Artificial Intelligence, PwC
“AI models are developing capabilities at an incredible rate… I think anyone who isn’t uncomfortable feeling like they’re constantly trying to keep up is probably not paying attention,” he said. He suggested exploring different AI models, understanding the differences between them, learning how to boost LLMs, keeping up with tech blogs, and practicing using the tools as much as possible.
“The most important thing is that AI skills are practical skills. They’re applied skills… you have to use the technology,” he stated. A commitment to self-learning in this era is becoming “the new safe bet. If you’re not able to do it, you’ll fall behind quickly.”
But ultimately, formal education isn’t just about acquiring knowledge and skills; “it’s about the whole person,” he concluded. It’s about how you think, how you interact, and how you critique. I believe those higher-order capabilities will be more valuable in the future, not less.
AI Is Destroying the Next Generation of Talent: In technology, job openings for recent graduates have already been cut in half.
The following article comes from the prestigious Fortune magazine website and is written by Beatrice Nolan, a technology reporter.
For many recent graduates, the first rung of the corporate ladder is becoming increasingly difficult to reach.
The first rung on the corporate ladder is disappearing for many recent graduates. Entry-level corporate jobs have dwindled, internship opportunities are drying up, and employers increasingly expect newcomers to arrive fully qualified. AI is accelerating the shift by automating tasks for young people, but experts warn that short-term savings could leave companies without the leaders they will need in the future.
Kenneth Kang, a computer science graduate, spent his first year after college applying for more than 2,500 jobs. He landed 10 interviews.
“It was devastating,” he told Fortune. “Honestly, I thought with a 3.98 GPA, letters of commendation, and some interesting past experience, I might be able to easily land a full-time job. But that wasn’t the case.”
Kang, a Portland, Oregon resident, finally landed a job at Adidas, where he had interned the previous summer, after more than 10 months of countless job applications. In fact, his experience is better than that of many of his fellow graduates; one of them, he said, has been looking for work for two years.
For many recent graduates, the first rung of the corporate ladder is becoming increasingly difficult to reach.
Entry-level positions, generally defined as those requiring no more than a year of prior full-time experience and offering hands-on training, are becoming increasingly scarce in many front-line employee sectors.
Job openings have dwindled, internships are becoming less permanent, and some employers now expect entry-level hires to incorporate skills that were previously taught internally.
Artificial intelligence is accelerating this trend by automating junior-level tasks and incentivizing companies to delay or reduce the hiring of professionals in the early stages of their careers.
Experts warn that while this may reduce costs in the short term, it could weaken the pool of leaders in the coming years. In the tech sector, hiring of recent graduates at the 15 largest companies has fallen by more than 50% since 2019, according to a report by the venture capital firm SignalFire. Before the pandemic, recent graduates accounted for 15% of hires at large tech companies; now, that figure has dropped to just 7%.
«I feel like the situation is getting worse over time,» Kang said.
«AI is taking over, which is creating limited job opportunities or simply pushing companies to seek out very high-level candidates. I find that very unfair.»
A Deficient Training Pathway
For the past few decades, career advancement within a company has been a relatively straightforward process. Graduates would start in an entry-level position, where companies would invest in training and development before continuous promotion.
Entry-level positions have been disappearing for some time now, as companies increasingly expect new employees to arrive with skills and experience that would previously have been acquired on the job.
However, as the drive toward AI efficiency further reduces entry-level positions, the recruitment market for recent graduates is becoming increasingly complex.
Companies are becoming more selective about who and where to hire as they try to integrate AI,
and entry-level positions are bearing the brunt of this impact, as the technology is particularly effective at automating tasks previously performed by junior workers, such as data cleaning, summarizing, and basic quality assurance.
According to data from Handshake, a job platform focused on Generation Z, job postings for entry-level positions at traditional companies fell by approximately 15% last year.
Internship conversion rates are also declining. In the 2023-24 period, only 62% of interns received full-time offers, bringing the overall conversion rate below 51%, the lowest in more than five years, according to the National Association of Colleges and Employers. Hybrid interns had even lower conversion rates than those who interned in person.
Leveraging Experience
One way to succeed in the age of AI is to leverage experience to work productively with more widespread AI tools. But if traditional career paths become obsolete, what will happen when companies run out of experts?
«I’m sure there will be a huge skills shortage,» said Stella Pachidi, senior lecturer in technology and work at King’s Business School. «I think the traditional ways we’ve seen people develop their expertise could easily disappear.»
Studies increasingly point to AI as one of the factors driving the shrinking job market,
especially for entry-level positions. In the US alone, in the first seven months of 2025, AI was cited as the cause of just over 10,000 job cuts, according to new data from the outplacement firm Challenger, Gray & Christmas. The firm ranks it among the top five reported causes of staff reductions this year.
These disruptions could cause problems in the future.
“If many companies are constantly cutting at the entry level, there’s a fear of losing the talent that will shape their future—the talent that will become managers, executives, and so on,” Tristan L. Botelho, associate professor of organizational behavior at the Yale School of Management, told Fortune.
“Everyone is focused on current efficiency and not necessarily on the future,” Pachidi added. How will their organizations fare? What kind of value will they create in the future? Will they have the experts?
Concerns about tomorrow’s talent
The looming skills gap is something that worries many executives, according to Nick South, managing director and senior partner at Boston Consulting Group.
While he views the disruption of entry-level jobs as a “short-term” problem and believes that AI will create new jobs in the long run, this brief disruption could be painful.
“Right now, for an individual, this is incredibly disruptive, and as a society, we need to help people retrain,” he said.
There’s also the question of how to prepare young people for an AI-driven world. Some argue that the rise of AI could completely rewrite the traditional career path from education to entry-level jobs.
“The middle ground of knowledge workers is likely to become less important,” said Rob Levin, senior partner at McKinsey and leader of QuantumBlack, McKinsey’s AI division. “And I’m concerned about how we’re going to incentivize people to specialize deeply and get companies to train their employees in the specialties they need. Will there be new vocational schools or something similar?”
At universities, both professors and students have realized that most of the work done in some university courses can be assisted, if not almost entirely automated, by AI.
AI’s Ability to Summarize Long Texts
Students were among the first to grasp ChatGPT’s ability to write essays and summarize long texts. But while students may see their academic workload significantly lightened by AI tools, professors told Fortune they were concerned about the prospect of a generation lacking critical skills and a traditional education.
An MIT study suggested that LLM (extensive language model) use can reduce neural interaction and impair learning in students, especially younger users (the researchers caution that the findings are preliminary and have not yet been peer-reviewed). The study also found that ChatGPT users, specifically, exhibited the lowest brain interaction and «consistently lower performance at the neural, linguistic, and behavioral levels.»
Graduates Taking Action
Eva Selenko, a professor of work psychology at Loughborough Business School, believes that education systems and the job market are more likely to adapt to an AI-driven talent generation than to adapt to it. “I think we need to educate people to use AI tools to the fullest extent of their knowledge,” he said. “I deeply sympathize with those graduates. On the other hand, they are exceptionally well-educated. They have initiative and creativity.”
Young job seekers are already taking on some of these responsibilities.
While job hunting, for example, Kang founded a startup to gain experience, as employers were demanding years of experience even for entry-level positions. He formed a group with other computer science graduates in similar situations to offer low-cost technology consulting to clients and thus enhance their resumes.
“I’m not just applying for jobs and biting my nails,” he said. “I’m here to do other things along the way.”
Fortune Brainstorm AI returns to San Francisco on December 8-9 to bring together some of the brightest minds we know—technologists, entrepreneurs, Fortune Global 500 executives, investors, policymakers, and media insiders—to explore and grapple with the most pressing questions about AI at another pivotal moment. Register here.
About the author
By Beatrice Nolan
Tech Reporter
Beatrice Nolan is a technology reporter on Fortune’s AI team, covering artificial intelligence and emerging technologies, as well as their impact on work, industry, and culture.
AI is rewriting the rules of work; entry-level jobs are on the front lines.
The following contribution comes from Employer News (HR news for UK employers). Deel is the end-to-end payroll and HR platform for global teams. Designed for today’s world, Deel integrates human resource information systems (HRIS), payroll, compliance, benefits, performance, and device management into a single platform, backed by its own payroll infrastructure in more than 150 countries. Companies of all sizes use Deel to securely hire, pay, and manage all types of workers at scale. Learn more at deel.com.
Authorship by the team.
Two out of three organizations (66%) expect to slow down entry-level hiring.
Nine out of ten organizations (91%) report changes or shifts in roles.
Two out of three organizations (67%) are already investing in AI training programs.
A new IDC study, commissioned by Deel, reveals a rapidly changing workforce: two out of three organizations (66%) expect to slow down entry-level hiring, while nine out of ten (91%) report that roles are already changing or disappearing due to AI. The result? A widening skills gap and a growing challenge in developing the next generation of leaders.
But amid the disruption, the data also points to a clear path forward. The results show that organizations are not standing idly by: 67% are already investing in AI training programs to empower their employees and prepare their teams for the future. Companies that act now to update their skills, redesign roles, and reimagine how talent grows will be best positioned to thrive in an AI-driven economy.
Released today, the IDC report «AI at Work: The Role of AI in the Global Workforce» presents the results of a survey of 5,500 business leaders in 22 markets. It highlights how companies can address this transformation by balancing automation with human development.
«AI is no longer emerging; it’s a reality,» said Nick Catino, global policy director at Deel.
«It’s transforming how we work and operate. Entry-level jobs are changing, and so are the skills companies are looking for. Both workers and companies need to adapt quickly. It’s not about staying competitive, but about staying viable.»
From Disruption to Leadership: How Businesses Can Respond
Nearly all surveyed organizations (99%) have at least begun exploring and implementing AI, and almost 70% have moved beyond pilots and achieved full integration. However, with AI taking over repetitive, knowledge-based tasks, businesses face increasing challenges in talent development and leadership training.
71% report growing difficulties recruiting and training future leaders due to the loss of entry-level learning pathways.
69% say there are now fewer career development opportunities for junior employees.
Media, retail, healthcare, professional services, and logistics are the sectors most affected by the decline in hiring entry-level employees.
To stay ahead, leading organizations are redesigning roles, training their teams, and building a culture of continuous learning to maintain a balance between productivity and people development.
Workforce Restructuring and Redesign
The influence of AI on the global workforce is driving a widespread restructuring of roles, although its impact varies considerably around the world.
The study reveals that nine out of ten organizations (91%) have experienced job changes or displacements, and a third (34%) are undertaking a significant restructuring of their workforce to integrate AI. As automation takes over routine tasks, companies are reorienting human roles toward strategic oversight, managing AI systems, and creative problem-solving, indicating a fundamental redefinition of how work is done.
New Zealand (53%), Argentina (53%), and the US (50%) recorded the highest levels of job displacement, with positions being eliminated entirely due to AI.
In contrast, only 11% of Chinese organizations reported displacements, the lowest percentage among all surveyed markets. China is leading the way in job redesign (79%) rather than elimination, reflecting robust national training initiatives to adapt its workforce to the AI revolution. This reflects China’s national initiative to promote training through extensive government-subsidized training programs aimed at enhancing workforce capabilities across the country.
The momentum for AI training is growing, but accountability is lagging.
What are companies around the world doing to train their teams? Two-thirds of organizations are actively investing in AI-focused training programs, with Canada (77%), Brazil (76%), and Singapore (74%) leading the way. However, challenges remain:
57% cite low employee engagement in training,
51% face budget constraints, and
45% struggle to find expert trainers.
The responsibility for AI training remains unclear in many companies: only 3% have established cross-functional teams to coordinate initiatives, while 29% admit they don’t know who is responsible for the process.
New skills are paramount.
As traditional university degrees lose relevance (only 5% of surveyed organizations consider them essential for entry-level positions), companies are prioritizing practical skills.
The top three requirements for entry-level talent now include:
Technical certifications in AI tools or coding bootcamps (66%)
Problem-solving and critical thinking skills (59%)
Strong communication and collaboration skills (51%)
New employees are increasingly expected to be proficient in AI and technology tools, as well as demonstrate critical thinking and communication skills from day one. This is a dramatic shift from academic credentials to practical ability, as employers value agility, continuous learning, and human creativity in addition to technical fluency.
Barriers to AI Success: Integration, Talent, and Trust
Despite strong momentum, nearly half of organizations (48%) say legacy systems are slowing AI integration, while 43% cite a shortage of skilled AI talent as a major barrier.
To compete, half of employers are willing to pay AI specialists 25% to 100% more than comparable tech roles, with Asia Pacific markets like Korea (25%), India (22%), New Zealand (21%), and Australia (20%) leading the way in salary premiums.
In addition to higher compensation, companies are also relying on additional incentives, such as access to cutting-edge tools (49%) and well-defined career paths (43%), to attract and retain top AI talent. Access to cutting-edge tools and projects is crucial for AI professionals to remain relevant and motivated, fostering innovation and making employers more attractive in a competitive talent market.
Governance Gap
The study also reveals a significant gap in AI governance. Only 16% of companies report being very familiar with their local AI regulations, and fewer than one in four (24%) consider these regulations clear and supportive. China recorded the highest percentage of organizations unfamiliar with local AI regulations (57%), closely followed by India (53%) and Germany (53%).
Only 22% of organizations have formal internal policies governing employee use of AI. This regulatory uncertainty could stifle innovation and expose companies to ethical and compliance risks. “Artificial intelligence is transforming the global workforce at an unprecedented pace, outpacing any recent technological shift,” said Dr. Chris Marshall, vice president of AI for Asia Pacific at IDC. “The organizations that will thrive are those that combine automation with a human-centric vision: investing in training, redefining entry opportunities, and ensuring that governance and ethics evolve at the pace of innovation.”
Methodology: A total of 5,500 business leaders participated in this IDC research commissioned by Deel. They came from organizations of all sizes and included decision-makers who define business and digital strategies. The study covered 22 markets worldwide: Argentina, Australia, Brazil, Canada, Chile, China, Colombia, France, Germany, Hong Kong, India, Israel, Japan, South Korea, Mexico, the Netherlands, New Zealand, Singapore, Spain, Sweden, the United Kingdom, and the United States. The study covered a wide range of sectors, including banking, education, financial services, government, healthcare, hospitality, insurance, manufacturing, media, professional services, resource industries, retail, technology companies, telecommunications, transportation and logistics, and utilities. Data collection took place in September 2025.
Will AI Reduce Job Specialization?
The following contribution comes from Time magazine, which describes itself as follows: TIME is a global media brand with 100 years of unmatched trust and authority, reaching an audience of more than 100 million people worldwide across our platforms. Founded in 1923, TIME began as the first weekly news magazine: a summary of world events for busy people. Today, TIME includes a website, a magazine, and a social media presence of more than 51 million.
The article is by Jacob Clemente, a reporter for Charter (TIME) who covers artificial intelligence and work.
Donna Morris, Walmart’s chief human resources officer, recently predicted that office roles will become broader and more generalist thanks to AI. Instead of hiring specialists for each area of human resources, for example, companies could hire HR generalists who can use AI to fill their knowledge gaps and work across various specialties.
A significant recent working paper, authored by researchers at Stanford and Harvard Business Schools, explores a related idea by examining the extent to which genAI enables workers to perform tasks that lie within, near, or far from their area of expertise.
If genAI allows people to expand into other professional areas, the implications would extend beyond job specialization, encompassing job mobility, training, and recruitment. “For example, data scientists could move into another role and occupation within the same organization (e.g., marketing analyst, financial analyst) with far less training than they would need without genAI,” the researchers write.
What did they actually discover? Workers could successfully perform adjacent tasks with AI assistance, but they encountered a “genAI wall” when attempting certain tasks that were too far removed from their specialization.
This suggests that genAI could reduce job specialization, but only up to a point. Basic knowledge in your field is necessary to perform at an expert level, even with the support of genAI. Research supports the idea that expertise in the field, such as that gained from studying marketing, finance, law, or chemistry, remains valuable even when genAI takes over tasks previously performed by humans.
“We think genAI gives us a superpower, but the reality is that if it’s an area we don’t understand and don’t know much about, we’re simply working at the base of the model,” explains Iavor Bojinov, one of the authors of the article and an associate professor of Business Administration at Harvard Business School. “If there’s an obvious error, we might be able to detect it. But, generally, we can’t improve it.”
The Experiment
Researchers conducted an experiment with IG, a UK-based global commerce company, involving three groups of employees who wrote web articles for the company website:
Web analysts, who already do this as part of their job.
Marketing specialists, who perform different but related tasks.
Technology specialists, who are mostly software engineers and data scientists without relevant experience.
Article writing was divided into two tasks: creating a template with the article’s components (such as keywords and headings) and writing the article itself.
The researchers found that genAI balanced performance in creating the article template. Without genAI, web analysts, on average, performed this task significantly better than their marketing and technology colleagues, according to evaluators. With genAI, everyone performed comparablely.
But when it came to writing the article, the results were more disparate. With genAI’s help, marketing specialists wrote web articles on par with those of the web analysts. However, technology specialists lagged significantly behind marketing specialists.
The «genAI wall»
Why the different results when creating the template and when writing the article?
The researchers explain that creating the template is a conceptual task that requires more explicit knowledge. Starting with a topic, relevant headings, keywords, etc., are generated, following a clear template. GenAI tools like ChatGPT excel at this type of task.
On the other hand, writing the article itself is much less structured and requires the kind of knowledge and judgment that comes with experience. Starting with a template, an article must be written with coherent prose and marketing best practices. Without the relevant knowledge, one may lack the judgment needed to improve upon what genAI offers. For example, one of the data scientists stated that they removed certain keywords from the article produced by the AI tool because they «prefer clear and straightforward articles.»
This is where the researchers’ concept of the «genAI wall» comes into play. If you have experience in the relevant area, genAI can help you perform new tasks. That’s why marketing specialists could use genAI to achieve the same results as their web analyst colleagues.
When the Gap Isn’t Closed
But as you move away from your area of expertise, there are tasks where you eventually reach a «genAI wall»—a point where genAI doesn’t bridge the gap between you and an expert. This finding reflects what economist David Autor has written about AI and expertise: «AI can extend the reach of expertise by building stories on a solid foundation and a strong structure. Without this foundation, it constitutes a structural risk.»
Specialists vs. Generalists
We will need more research to determine the extent to which the results of this study are generally applicable. The experiment had a very small sample size and analyzed a specific set of marketing tasks. For example, would the results be the same if software engineers, product managers, and marketing professionals each developed a new product feature with the help of AI?
Even so, the study suggests that, at least in some areas, jobs could become less specialized. For example, in the future, there might be a need for only marketing experts who are proficient in AI, rather than for those specializing in search engine optimization (SEO) or email campaigns. This, of course, raises further questions, such as what is the appropriate level of specialization for workers and what all of this means for organizations.
Bojinov tells us that he personally believes domain knowledge will be «super vital,»
but within each domain, it may not be necessary to specialize so much. “I really don’t think you need people to be dedicated to SEO anymore. I think it would be better for them to be more generalists.”
That would give organizations a new degree of flexibility, as staff could be moved around according to business needs. “If you have a team very focused on SEO optimization, there may be times when you don’t need to write as many articles, but you have an important conference coming up and you need people to adapt and go work there,” Bojinov explains. In that case, you’ll need a team of marketing experts who can use genAI to address whatever marketing issues the company is facing at that time.
Where AI Isn’t So Useful
There will likely be areas of the economy where deep specialization will still pay off, such as research, where the frontiers of knowledge are being expanded, or in domains where AI isn’t as useful. But for many workers, the way forward may be to focus on becoming an expert in their area (such as HR, finance, operations, or software engineering, for example) and learn how to use AI to adapt to any task that arises.
AI isn’t eliminating all entry-level jobs, but it is changing the game, and job seekers need to step up their game
The following contribution comes from the Mediacorp website, which describes itself as follows:
We are Singapore’s national media network and largest content creator. We engage with 99% of the population weekly in four languages across our digital, television, radio, and social media platforms.
Our purpose:
We are dedicated to creating engaging and trustworthy content, connecting and inspiring our communities, and celebrating the meaningful moments of every day.
Author: Taufiq Zalizan, a team member
Experts say that AI isn’t eliminating all junior positions, but it is forcing recent graduates to step up their game and demonstrate the one thing machines still can’t replace: human judgment.
AI isn’t eliminating all entry-level jobs, but it is changing the game, and job seekers need to step up their game.
While AI isn’t eliminating entry-level jobs across the board, its impact is most visible in routine roles.
When her six-month public relations internship ended abruptly midway through, 23-year-old communications graduate K. Sudhiksha wasn’t entirely surprised.
Officially, she was told it was due to a company restructuring, but she suspected it had something to do with how artificial intelligence (AI) could perform her work.
«I spent most of my time running instructions in ChatGPT,» she told CNA TODAY, referring to the popular AI chatbot.
«We were all encouraged to do it. I could get my tasks done faster, but it also made me feel creatively limited.»
Ms. Sudhiksha, who joined the public relations firm in July hoping to learn how to write press releases and pitch news to the media, found that much of her work revolved around using AI tools to generate draft press releases and summarize weekly news coverage for clients.
While warned to carefully review the output generated by ChatGPT, she said the reliance on AI left her feeling empty, as she had hoped for a more hands-on, creative process that would allow her to develop her own thinking.
Three months into her internship, her position was terminated, Ms. Sudhiksha said.
Now unemployed, she admitted that her experience has left her pessimistic and frustrated, as she has to compete with machines: «I wish I had worked in public relations before the AI era.»
K Sudhiksha, 23, was halfway through a six-month internship at a public relations agency when her position was terminated. (Photo: CNA/Raj Nadarajan)
For Mr. Mitchell Yap, 25, a customer service specialist at a tech company, the impact of AI on job security has also been tangible. The company recently introduced a support bot designed to handle as many customer inquiries as possible before transferring them to a human agent.
«As the bot improves, my team now only handles the most complex or sensitive cases, but we can’t ignore that this also means the overall workload is decreasing.»
While he’s not overly anxious yet, Mr. Yap admits that each new bot update makes him and his colleagues wonder how long their roles will remain essential.
A growing concern among young workers and job seekers
The experiences of Ms. Sudhiksha and Mr. Yap reflect a growing concern among young workers and job seekers, including those who haven’t yet entered the workforce: Will AI take away the first jobs they’ve worked so hard for?
For some, the answer is yes. In the legal sector, for example, recruiters like Ms. Shulin Lee, managing director of the legal executive search firm Aslant Legal, have already seen how automation and AI are impacting the recruitment of entry-level staff.
In 2024, law firms prioritized hiring mid- to senior-level professionals. There were virtually no vacancies for young people with one or two years of experience, she said. It was one of the most difficult years for recruiting young people that I’ve seen in my 15 years of experience in recruitment.
While AI wasn’t the only factor driving the decline—cost and a lack of skills among Gen Z recruits also played a role—Ms. Lee recalled that partners at the firm told her that AI tools can now conduct due diligence on 200 contracts in two hours, reducing the need for young people.
According to data from Jobstreet by Seek, the number of entry-level positions in Singapore decreased by more than 25%
in the first half of 2025 compared to the same period in 2024, even though the total number of vacancies increased slightly, by 4%.
The data points to what Jobstreet calls a «recalibration» of the labor market. Many entry-level positions are being restructured as more companies adopt automation to handle routine tasks traditionally assigned to junior team members, said Ms. Yuh Yng Chook, head of sales for Asia and services for Asia-Pacific at Seek, owner of Jobstreet and Jobsdb.
Similarly, the human resources (HR) platform Remote surveyed 250 Singaporean employers in its Global Workforce Report 2025 and found that four out of five had reduced the number of entry-level hires at their companies due to AI.
18% of Singaporean companies reported eliminating positions or reducing their workforce because of AI, while another 18% had hired or reassigned positions specifically to support AI-related initiatives.
Even so, some experts emphasized that AI is not the only factor driving the decline in hiring activity. Mr. Lewis Garrad, partner and practice leader for Asia at the global consulting firm Mercer, stated that the slowdown in graduate hiring reflects both technological change and a more cautious business climate. “AI can support and complete certain tasks, but it rarely replaces an entire job,” he said, adding that companies are automating routine parts of work while rethinking roles in a context of slower growth and tighter budgets.
Mr. Chiew Chun Wee, regional policy and information officer for Asia Pacific at the Association of Certified Public Accountants (ACCA), agreed.
“The phrase ‘AI is coming for your jobs’ makes for compelling headlines, but the reality is much more nuanced,” he said.
According to Mr. Chiew, most organizations are testing tools for limited tasks, such as drafting written work, transcribing meeting minutes, and supporting research, without replacing entire roles.
Adoption also varies by size and sector, with smaller companies tending to be more agile in testing new applications, while larger ones develop in-house tools.
«The nuance lies in how AI reshapes work… Automating knowledge work is actually quite difficult,» said Mr. Chiew.
Processes are chaotic and rife with value judgments. Therefore, the future of work will not be about replacing people. It will be a combination of automation, increased staffing, and human judgment.
That’s why some experts believe companies cannot afford to stop hiring young people altogether. As Ms. Lee put it, «If you stop hiring young people now, you’ll be short of mid-level positions later on. The talent pool will dry up.»
Mr. Mitchell Yap works as a customer service specialist at a technology company on November 5, 2025.
WHERE ENTRY-LEVEL POSITIONS ARE DISAPPEARING
While AI isn’t eliminating entry-level positions across the board, its impact is most visible in routine roles.
Data from Jobstreet shows that in Singapore, entry-level sales positions have fallen by 61 percent and entry-level customer service positions by 45 percent, as chatbots, automated lead generation tools, and self-service systems take over tasks previously handled by new hires.
Ms. Gillian O’Brien, general manager of Remote Recruit at Remote, stated that similar declines are being seen in customer service, software development, sales development, and marketing content production. Remote Recruit is a product of the Remote brand.
«These are roles where most tasks, such as triaging IT issues, entry-level programming, building sales contact lists, and writing blog content, can be performed by AI,» she added.
Globally, this pattern mirrors that of Singapore: In the United States, a 2025 study by ADP Research, a global leader in labor market and employee performance research, and Stanford’s Digital Economy Lab, shows that employment among 22- to 25-year-olds in AI-exposed roles declined by 6% between the end of 2022 and July 2025.
Within this latter group, junior software developers saw a 20% drop, and customer service positions fell by 11%—precisely the roles easiest to automate.
The ripple effect is being felt far beyond frontline positions. Across all sectors, companies are reorganizing their operations in response to the growing impact of AI and automation.
At Amazon, for example, the company announced an overall reduction of approximately 14,000 corporate positions in October as part of its efforts to reduce levels of responsibility and increase accountability.
In a memo to employees, Beth Galetti, Amazon’s senior vice president of People Experience and Technology, called AI «the most transformative technology since the internet,» stating that it allows companies to innovate faster and that they must respond to it with more agile and efficient structures.
While she didn’t directly link the layoffs to AI, her comments reflect how large companies are reorganizing to remain competitive in an AI-driven economy.
Online for Physical Offices
In a palpable sign of the changing times in Singapore, Grade Solution Learning Centre closed its four physical branches and in 2021 went fully online with its AI-powered platform. Much of the routine work that previously required junior staff is now automated.
Co-founder Jerry Lee told CNA TODAY that, since moving entirely online, his company uses AI to write lesson outlines, edit captions and social media posts, generate ideas for marketing content scripts, and grade student work.
“Our platform can automatically grade more than 90% of open-ended questions accurately,” Mr. Lee stated.
He added that the transition to a virtual format, along with AI tools that have boosted the productivity of operations executives, has reduced the need to hire junior staff, which has now been reduced from three to one.
“Our online classroom model allows us to reduce hiring across all operations. We no longer need as many receptionists or managers in multiple physical locations as we did before.”
However, some roles still require a human touch, from curriculum developers and visual artists to instructors who can engage students and interpret how they learn, Mr. Lee stated.
AI Doesn’t Understand Everything
«AI speeds up the process, but it still doesn’t understand the nuances of exams or how students think. Experienced teachers are needed to interpret the data, refine the content, and maintain the human connection.»
In its Global Workforce Report 2025, HR platform Remote found that four out of five companies surveyed in Singapore had reduced the number of entry-level hires thanks to AI. (Photo: CNA/Ili Nadhirah Mansor) …see more
HOW YOUNG JOB SEEKERS NEED TO IMPROVE
Across all sectors, employers told CNA TODAY that AI isn’t so much about reducing staff as it is about raising expectations. New employees are now expected to be AI-savvy, data-savvy, and prepared to exercise sound judgment—even more so than before.
According to Jobstreet’s 2025 Recruitment, Compensation, and Benefits Report, more than half of the employers surveyed (54%) consider AI skills a key hiring factor, and nearly one in five consider them a top priority. A total of 887 employers and HR professionals in Singapore participated in the survey between September and October 2024.
However, technical fluency alone is not enough, as employers are looking for someone who can automate a process and apply human judgment to turn the result into valuable insights.
Mr. Wee Tee Hsien, CEO of Fujifilm Business Innovation Singapore, stated that while he continues to hire recent graduates, his entry-level positions now prioritize skills such as data analysis, workflow design, and process improvement. His core business is providing document solutions, digital IT services, and digital transformation support that help organizations streamline workflows and boost productivity.
He noted that while the number of entry-level positions has remained fairly stable in recent years, the company’s approach will change if necessary to adapt to evolving business needs and digital priorities.
For him, AI enhances employees’ potential rather than replacing them. For junior employees, this means using tools like GenAI, Copilot, or Power Platform to work smarter, not harder, he stated.
«It’s important for employees to have the ability to think critically, ask questions, and connect ideas. A growth mindset is key.»
A New Career Ladder for AI
The following contribution comes from the Stanford Social Innovation Review (SSIR), an award-winning journal and website that addresses cross-sector solutions to global problems. SSIR is written by and for social change leaders from around the world and across all sectors of society: nonprofits, foundations, businesses, governments, and engaged citizens. SSIR’s mission is to advance, educate, and inspire the field of social innovation by seeking out, cultivating, and disseminating the best knowledge based on research and practice. Through print and online articles, webinars, conferences, podcasts, and more, SSIR connects research, theory, and practice across a wide range of topics, including human rights, impact investing, and nonprofit business models. SSIR is a publication of the Stanford Center for Philanthropy and Civil Society at Stanford University.
The author is Bruno V. Manno, a team member.
The changing nature of jobs means that workers need a new education and training infrastructure that adapts to their needs.
The increasing use of generative AI in the workplace presents a paradox for entry-level workers. The very tasks that once trained new employees, such as summarizing meetings, cleaning data, and drafting memos, are becoming increasingly automated. This means that entry-level jobs now require expertise that entry-level positions no longer provide.
AI has displaced the routine, low-risk tasks
that used to teach newcomers how to navigate complex organizations. Without these stepping stones, climbing the ladder of opportunity toward better job options becomes more difficult and, for many, impossible. This is not a temporary problem. AI is reshaping work, redefining important knowledge and skills, and how people are expected to acquire them.
The consequences extend from the start of an individual career to the broader American promise of economic and social mobility, encompassing both financial wealth and the social wealth that arises from the networks and relationships we build. Yet the same technology that complicates the first job can help us reinvent how expertise is gained, validated, and scaled. By using AI to expand, rather than restrict, access to education, training, and the accreditation of knowledge and skills, we can build a more robust career path for the middle class and beyond. A key aspect of achieving this is redesigning the infrastructure of education, training, and hiring.
In the words of Matt Sigelman, president of the Burning Glass Institute:
“AI doesn’t automate jobs. It automates tasks. Whether this frees up time to take on more valuable tasks, whether the new efficiencies unleash latent demand that actually creates opportunities, or whether employers decide to take advantage of the savings depends on a number of factors and unfolds over time… First and foremost, we need accessible infrastructure.”
The Shift in Entry-Level Jobs
Entry-level jobs traditionally serve two purposes: they facilitate the execution of work and provide training. As routine tasks, such as programming, basic analysis, and internal communication, are handled by AI, human roles start from a higher base. However, when that base presupposes fluency with workflows, norms, and tools that were once learned on the job, many newcomers are left behind.
This creates an experience gap: experience is needed to get a job,
and a job is needed to acquire the necessary experience. Education and training providers, such as high schools or universities, are rarely designed to keep pace with evolving workplace technology. Furthermore, employers have cut back on in-house training, and recruitment algorithms filter resumes for «proven contributors.» The lower rungs of the ladder, once plentiful, are now scarce.
AI is also reshaping the concept and value of experience. The scarcity is shifting from static knowledge (what is known) to dynamic capability (how to solve problems with tools, verify results, and apply context).
Employers increasingly value individuals who can collaborate with AI by defining problems, orchestrating data and models, verifying reliability, and communicating results.
This fosters a combination of analytical, social, and adaptive skills, which are rarely mastered solely in the classroom. The question is not so much what credentials one possesses, but what one can reliably do and whether that can be demonstrated. In this world, evidence trumps pedigree. Portfolios, projects, simulations, and performance tasks are becoming stronger indicators than course lists and traditional bachelor’s and college diplomas.
When used correctly, AI can democratize experience. It can help a university student analyze data, a retail employee generate functional code snippets, or a high school graduate produce professional-quality marketing assets. It reveals what analysts call latent expertise: capabilities that current credentials don’t capture. If employers look for that evidence, they’ll find more talent.
The Credential Dilemma
Employers struggle to move beyond diplomas and degrees without credible alternatives. Credentials are proliferating, but what do they mean? And how do we create a job market that truly recognizes knowledge and skills?
Credentials Engine has identified nearly 1.1 million unique credentials in the United States across 18 credential categories, from four types of credential providers:
Post-secondary education institutions, with nearly 350,500 degrees and certificates.
Massive open online course (MOOC) providers, with more than 13,000 certificates of completion, microcredentials, and online degrees from foreign universities.
Non-academic providers, with nearly 656,500 badges, certificates of completion, licenses, certifications, and apprenticeship programs.
Secondary schools, with over 56,100 diplomas from public and private secondary schools, alternative secondary school certificates, and high school equivalency diplomas.
Their report emphasizes the need to significantly improve transparency in the credential market to foster individual mobility and national economic growth.
For example,
How do accreditation practices overlap, including how certificates offered by higher education institutions are based on, or compared to, other certificates and degrees?
How are badges used to represent these and other credentials?
How do we categorize different accreditation programs in a way that accurately reflects the time required to complete them and their market value?
Another report by Credential Engine estimated that the total annual expenditure by educational institutions, employers, federal grant programs, states, and the military on these accreditation programs exceeds $2.1 trillion. This substantial expenditure underscores the importance of the accreditation marketplace and the need for more effective accountability and decision-making processes.
The annual spending on these accreditations also raises questions about their value and individual outcomes, especially which ones actually advance a career and lead to significant salary increases. An analysis by the Burning Glass Institute and the American Enterprise Institute indicates that “around 12% of certifications offer significant salary improvements that would not otherwise have been obtained, and only 18% of those who obtain them are likely to see salary increases that their peers do not enjoy.”
The Burning Glass Institute has created a Career Value Index Navigator, an online tool that provides information on outcomes such as salary increases and career advancements for virtually all certifications in the United States, as well as more than 20,000 other non-college credentials.
An Education and Training Infrastructure for the Age of AI
AI will not be achieved with larger budgets alone. One analysis summarizes the situation as follows: “…historically, job training has been a failure. Less than half of those trained with [business assistance] grants obtained employment, with no evidence that the jobs they obtained were well-paying. Similarly, studies on [job] training find minimal evidence of success.”
What is needed is a redesigned model that considers work as a primary learning space,
validates skills with evidence, and helps people continue to advance beyond their first job. Here are ten design principles for a reimagined education and training infrastructure for the age of AI.
Create hybrid institutions that remove barriers. Organizations operating in elementary and secondary schools, community colleges, other providers, and employers would allow students to progress through an integrated system rather than several disconnected systems.
For example, high school students currently represent 21% of total enrollments in community colleges.
This type of hybrid approach has been popularized by Jobs for the Future and other organizations under the name «the big blur,» which advocates blurring the dividing line between education and training, college, other training providers, and employers.
Make on-the-job learning the norm, not the exception. Structured, paid work experience should be central to initial career preparation. This would include apprenticeship programs for young people and adults, co-ops, clinical placements, and employer-integrated boot camps linked to recruitment pathways.
Whenever possible, programs such as apprenticeships should be organized with progressive accountability and compensation. For advanced positions, expand apprenticeship degree models that combine employment, mentorship, and academic credits so that learners earn a recognized credential while building practical mastery.
Create adjacent competencies to accelerate transitions. Most workers don’t start from scratch. Identify the knowledge and skills they can demonstrate for new job requirements and build education and training bridges that lead to them. Use targeted modules to convert prior experience into marketable capabilities in weeks or months, not years. Help entry-level workers find launchpad jobs: 73 positions, such as emergency medical technicians and power plant operators, that propel people into careers offering solid salaries, job security, and upward mobility. This shortens the time needed to acquire skills and reduces costs for students and employers.
Prioritize performance-based hiring. Replace resume indicators with job-relevant tasks, such as structured work samples, simulations, supervised trial projects, and standardized rubrics that can be combined with AI-assisted scoring where appropriate. For example, data analyst candidates should demonstrate they can cleanse confusing data, build a basic model, verify reliability, and explain trade-offs to a non-technical stakeholder. Performance builds confidence and expands access to non-traditional talent.
Ongoing support and post-placement mobility. Job placement is a milestone, not the goal. Many displaced workers first need a «lifeline» job—a stabilizing stepping stone that can become a stepping stone. Budget and plan for post-placement support such as coaching, peer groups, on-the-job projects, tuition or training stipends, and salary milestones that enable individuals to move from a «lifeline» to a «ladder.» Measure and fund programs based on mobility, not just initial placement.
Portable, machine-readable credentials with attached proof of qualification.
Each credential should be modular and easy for employers to integrate into their hiring systems. Whenever possible, attach verified artifacts, such as code repositories, dashboards, clinical assessments, and supervisor ratings with clear proficiency levels. The T3 Innovation Network, supported by the U.S. Chamber of Commerce, is an example of this, as is the Western Governors University Portfolio of Achievements. Portability allows workers to carry a skills history across platforms and employers.
Quality signals and accountability from the start. Use evidence-based tools, such as the credential value indices mentioned above, to distinguish genuine signals from noise. Public and employer funding should follow providers who can demonstrate value in the labor market, such as platform job placements, pay increases, promotion rates, and retention. Demand transparent reporting of outcomes for providers and employers, including the creation of a skills-first approach to hiring. Then, continue scaling up what works and fixing what doesn’t.
A modernized, learning-aligned safety net:
Update unemployment insurance and related benefits to encourage rapid skills upskilling during job searching. Implement portable learning accounts and invest in regional learning and work hubs that include the hybrid institutions described above. These hubs should allow people to access broadband, AI tools, mentors, and employer-supported programs all in one place.
Collaborations with employers to redesign entry-level roles:
Ask employers to restructure entry-level roles to teach and produce. These restructured roles should include projects that incorporate learning and mentoring time and should have clear career ladders linked to demonstrated skills. Apprenticeship and professional certification models provide the framework, with HR departments, business units, and educators working toward co-ownership of job design and outcomes.
Data infrastructure that prioritizes skills, not just work time.
Creating interoperable maps between job tasks, competencies, and learning outcomes so that curricula, including apprenticeship rotations, align with actual job requirements.
Sharing outcomes data with providers to continuously improve career paths.
In short, a sustainable education and training model in the age of AI links learning to real work, validates what people can do, and sustains advancement beyond the first job. As Ryan Craig argues in Apprenticeship Nation, apprenticeships are the clearest and most scalable way to realize that model. Why it matters now.
AI is already here and is changing the way we work.
This raises a simple question: Will it eliminate the first rungs of the career ladder or help us build new ones? We can choose the latter by combining credible quality indicators, such as a credential value index and similar tools, with performance-based hiring; expanding community-based programs that pool and leverage adjacent skills; and funding post-placement support that enables people to advance after their first job. Taken together, a skills-first approach moves from rhetoric to reality. Workers gain verifiable certificates of competence, and employers hire with confidence from a broader pool.
The stakes are high. If we implement AI only to decouple tasks and reduce staff, the advantage will be concentrated. But if we design roles so that AI augments human capabilities, more people will be doing relevant work sooner.
This creates a job market that recognizes skills, a training system that values what people already know, and a culture that makes the value of hard work visible. This is how we replace the disappearing entry-level job with a better starting point and transform disruption into a fairer and faster ladder to opportunity.
Photo by Bruno Manno. Bruno V. Manno is a senior advisor at the Progressive Policy Institute, where he directs its Pathways to Opportunity What Works Lab. He was U.S. Assistant Secretary of Education for Policy.
How Artificial Intelligence Will Change the World
The following contribution comes from the Nexford University website, which describes itself as follows: Built from the ground up. Based on 100 years of experience in what worked and what didn’t. Nexford had no legacy systems holding us back. No outdated traditions. That gave us the freedom to design a university that truly meets the demands of today’s world. Affordable, flexible, technology-driven, rapidly evolving, and shaped by AI.
Authorship by the team.
You’d be living in a remote place if you didn’t know how artificial intelligence will affect jobs between 2026 and 2030. AI like ChatGPT seems to be grabbing headlines right now. Google has introduced new AI software for creating presentations, analyzing and entering data, and writing content, and there are many more AI tools like Gamma and Numerous AI.
Those who resist, instead of seizing the opportunity, will miss out on opportunities to land in-demand jobs in the next six years and enjoy career growth. AI will take some jobs, but it will create new ones! Here are the jobs most likely to be affected by artificial intelligence between 2026 and 2030:
How artificial intelligence will change the world
Will AI help the world or harm it? As with any controversial topic, there will always be those for and those against. Artificial intelligence is no exception. In fact, as new AI tools are introduced and news about them multiplies, the divide between the two sides will also grow.
Many positive changes in society
Many market analysts claim that AI has the potential to generate numerous positive changes in society, such as increased productivity, better healthcare, and greater access to education. But we must adapt immediately.
Others, especially those who work in repetitive manual labor, will say that AI and robotics are a disruptive force and that, as far as the future of work is concerned, they only serve to steal jobs.
But robots and AI technologies can and will create a host of new jobs, help solve complex problems, and make our daily lives easier and more comfortable.
The final verdict is still pending, but the trend leans more toward AI as a positive rather than a negative force.
AI’s Impact on GDP
How will AI affect employment and the economy? The McKinsey Global Institute states that, with the average global level of adoption and absorption, and the advances in AI implied by its simulation, AI has the profound impact of generating approximately $13 trillion in additional global economic activity in the foreseeable future and by 2030, representing a cumulative GDP roughly 16% higher compared to today.
This equates to an additional 1.2% annual GDP growth.
If this materializes, this impact would be comparable to that of other widely used technologies throughout history. This will stem primarily from the replacement of labor with automation and increased innovation in products and services.
The same report goes on to state that, by 2030, the average simulation shows that around 70% of companies will have embraced the AI revolution and at least one type of AI technology, but that less than half will have fully absorbed all five categories.
Forbes asserts that AI has the potential to be one of the most disruptive technologies we will ever develop in global economies.
How will artificial intelligence affect society and the future? Forbes states that the future of AI offers endless possibilities and applications that will greatly simplify our lives. It will contribute to positively shaping the future and destiny of humanity, while Bernard Marr & Co. states that the transformative impact of artificial intelligence on our society will have profound economic, legal, political, and regulatory implications across all types of jobs and industries, which we must discuss and prepare for.
Other experts assert that AI has the potential to generate numerous positive changes in society, both now and in the future, including increased productivity, improved healthcare, and greater access to education.
AI-powered technologies can also help solve complex problems and make our daily lives easier and more convenient.
Will AI replace people’s jobs and careers?
How will AI affect employment? How many jobs will AI replace by 2030?
Artificial intelligence (AI) could replace the equivalent of 300 million full-time jobs,
according to a report by the investment bank Goldman Sachs. It could replace a quarter of work tasks in the US and Europe, but it could also mean new jobs and a productivity boom. And, over time, it could increase the total annual value of goods and services produced globally by 7%. The report also predicts that two-thirds of jobs in the US and Europe are exposed to some degree of automation through AI, and that around a quarter of all jobs could be performed entirely by AI.
Researchers from the University of Pennsylvania and OpenAI
found that some skilled administrative workers, earning up to $80,000 a year, are the most likely to be affected by workforce automation.
Forbes also states that, according to a report by MIT and Boston University, AI will replace up to two million manufacturing workers by 2026.
A study by the McKinsey Global Institute reports that, by 2030, at least 14% of employees worldwide could be forced to change careers due to advances in digitalization, robotics, and AI.