AI is transforming the skills needed in the workplace.
However, human skills remain fundamental.
The following contribution comes from the World Economic Forum’s «Jobs and the Future of Work» portal. It is authored by Karin Kimbrough, Chief Economist at LinkedIn.
Today, people are more than twice as likely to acquire AI skills than they were in 2018.
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According to a new report, AI is accelerating the pace of change in the workplace.
Today, people are more than twice as likely to acquire AI skills than they were in 2018. Paradoxically, this increased focus on technology also means a greater demand for human skills. In the workplace, things are changing, and that pace of change is accelerating.
Globally, more than 10% of workers employed today hold positions that didn’t exist in 2000 (in the US, the figure is approaching 20%).
As our recently published Workplace Change Report: AI Comes to Work reveals, for companies, leaders, and professionals, the work environment is virtually unrecognizable compared to just a generation ago.
From the growing influence of artificial intelligence on everyday tasks and new skills, to the creation of entirely new jobs, these trends are beginning to redefine today’s work environment.
A new study reveals that AI is placing greater emphasis on interpersonal skills at work.
As companies adapt to trends such as technological innovation and demographic shifts, leaders are empowering their teams to adapt and thrive in a constantly evolving environment. At the same time, professionals are responding to these changes, often updating their skills, retraining, or embarking on entirely new career paths.
The path will be very different for those entering the workforce today than it was 15 years ago. Professionals are likely to hold twice as many jobs throughout their careers compared to their predecessors: 20 jobs now versus 11 in 2010.
While these changes present unique challenges for businesses, such as talent retention and continuous training, they also create new opportunities for innovation and a dynamic labor market.
Let’s take a closer look at how work is changing in the emerging age of AI: AI skills are everywhere: Today, people are more than twice as likely to acquire AI skills than they were in 2018. Even occupations that were previously less likely to value AI skills—for example, recruiters, marketing professionals, salespeople, and healthcare professionals—are now seven times more likely to acquire them than they were just six years ago.
Furthermore, digital literacy (AI) skills are a key factor for job seekers: professionals who master AI will stay ahead of the competition and secure long-term career success.
Hiring managers know this, and more than half say they wouldn’t hire someone without these skills.
In fact, while only one in 500 job postings on LinkedIn mentions digital literacy, it’s no surprise that the demand for these skills has increased more than sixfold in the last year.
Workers are expanding their skills
Globally, today’s professionals are adding 40% more skills to their profiles than in 2018.
And it’s not just professionals: companies and leaders are beginning to understand the importance of training their teams in AI.
Digital literacy skills, such as process engineering and proficiency with tools like ChatGPT or Copilot, are equally important. Since 2023, the number of AI-related skills added by LinkedIn members has increased by 177%.
Interpersonal skills are becoming increasingly important
In roles that previously didn’t value human skills as highly, the importance of these specific skills has grown by 20% since 2018. As organizations understand the full potential of AI, they are also realizing its limitations: those tasks that require the unique human skills every business needs.
The current evolution of the work environment is prompting both managers and employees to rethink their working methods.
While the accelerated pace of change, compared to previous technological transformations, can be overwhelming, it also opens the door to significant opportunities for those who adapt proactively and develop new skills.
AI is changing who gets hired: what skills will keep you employed?
The following contribution comes from «The Conversation,» which defines itself as follows: The Conversation is a non-profit, advertising-free, and open-access editorial platform that provides media outlets and readers with informative articles and analyses written by the academic and research community.
Our team of editors, specialized journalists, supports and guides experts in conveying their knowledge to readers in clear, concise, and accessible language.
The author is Murugan Anandarajan, Professor of Decision Science and Management Information Systems, Drexel University.
The consulting firm Accenture recently laid off 11,000 employees while intensifying its efforts to train its staff in the use of artificial intelligence.
This reminds us that the same technology that drives efficiency is also redefining what it takes to keep a job.
And Accenture isn’t the only one. IBM has already replaced hundreds of positions with AI systems
while simultaneously creating new jobs in sales and marketing. Amazon reduced staff even as it expanded the teams that develop and manage AI tools.
Across all sectors, from banks to hospitals to creative companies, both workers and managers are trying to understand which jobs will disappear, which will evolve, and which new ones will emerge.
I research and teach at Drexel University’s LeBow School of Business, where I study how technology is transforming work and decision-making. My students often ask me how to stay employable in the age of AI. Executives ask me how to build confidence in a technology that seems to be advancing faster than people can adapt. Ultimately, both groups are asking the same question: What skills are most important in an economy where machines learn?
To answer this question, I analyzed data from two surveys my colleagues and I conducted this summer.
In the first, the Data Integrity and AI Readiness Survey, we asked 550 companies nationwide how they use and invest in AI.
In the second, the College Hiring Outlook Survey, we analyzed how 470 employers viewed hiring entry-level staff, workforce development, and candidates’ AI skills. These studies show both sides of the coin: those who develop AI and those who learn to work with it.
AI is everywhere, but are people ready?
More than half of the organizations told us that AI now drives daily decision-making, but only 38% believe their employees are fully prepared to use it.
This gap is transforming today’s job market. AI isn’t just replacing workers; it’s revealing who is ready to work with it.
Our data also reveals a contradiction. While many companies now rely on AI internally, only 27% of recruiters are comfortable with candidates using AI tools for tasks such as writing resumes or researching salary ranges.
In other words, the very tools that companies rely on for business decisions still raise concerns when job seekers use them to advance their careers. Until this perspective changes, even skilled workers will continue to receive mixed messages about what «responsible use of AI» truly means.
The gap was most evident
In the Data Integrity and AI Readiness Survey, this readiness gap was most evident in operational and customer-facing roles, such as marketing and sales.
These are the same areas where automation is advancing rapidly, and layoffs often occur when technology evolves faster than people can adapt.
At the same time, we found that many employers have not updated their degree or credential requirements.
They continue to hire based on outdated resumes, while the jobs of the future demand AI proficiency. The issue is not that AI is replacing people, but that technology is evolving faster than most workers can adapt.
Fluency and confidence: The pillars of adaptability
Our research suggests that the skills most closely linked to adaptability share a core theme: what I call “human-AI fluency.” This involves the ability to work with intelligent systems, question their outcomes, and continue learning as things change.
In every company, the biggest challenges lie in scaling AI, ensuring compliance with ethical and regulatory standards, and connecting AI to real business objectives. These obstacles are not about programming, but about sound judgment.
Useful Information for Humans
In my classes, I emphasize that the future will favor those who can transform machine output into useful information for humans. I call it digital bilingualism: the ability to navigate fluently between human judgment and machine logic.
What management experts call «retraining»—or learning new skills to adapt to a new role or significant changes in a previous one—works best when people feel safe to learn.
In our Data Integrity and AI Readiness Survey, organizations with strong governance and high levels of trust were almost twice as likely to report improvements in performance and innovation. Data suggests that when people trust their leaders and systems, they are more willing to experiment and learn from mistakes.
In this way, trust transforms technology from something to fear into something to learn from, giving employees the confidence to adapt.
According to the University Hiring Outlook Survey, approximately 86% of employers now offer in-house training or intensive online courses; however, only 36% say that AI-related skills are important for entry-level positions. Most training still focuses on traditional skills rather than those needed for new AI jobs.
The most successful companies integrate learning into the work itself.
They create learning opportunities in real-world projects and encourage employees to experiment. I often remind leaders that the goal is not just to train people to use AI, but to help them think alongside it. This is how trust becomes the foundation for growth and how retraining helps retain employees. The New Rules of Hiring
In my opinion, leading AI companies aren’t just cutting jobs; they’re redefining them. To succeed, I believe companies will need to hire people who can combine technology with sound judgment, question what AI produces, explain it clearly, and turn it into business value.
At companies that are implementing AI most effectively, hiring is no longer based solely on resumes. What matters is how people apply qualities like curiosity and judgment to intelligent tools. I believe these trends are giving rise to new hybrid roles, such as AI translators, who help decision-makers understand the meaning of the information AI provides and how to act accordingly, and digital coaches, who teach teams how to work alongside intelligent systems. Each of these roles connects human judgment with artificial intelligence, demonstrating how the jobs of the future will combine technical skills with human intuition.
That combination of judgment and adaptability is the new competitive advantage. The future will reward not only the most technically skilled workers, but also those who can turn intelligence—human or artificial—into real value.
The Great Skills Transformation: How AI Is Transforming 70% of Jobs by 2030
The following contribution comes from the website of Bernard Marr, a world-renowned futurist, influencer, and thought leader in the fields of business and technology, passionate about using technology for the good of humanity. He is the author of more than 20 books, many of them bestsellers and award winners, writes a regular column for Forbes, and advises and trains many of the world’s most recognized organizations.
Bernard Marr is the author of the article.
In my recent conversation with Aneesh Raman, Director of Economic Opportunities at LinkedIn, he shared a statistic that should grab everyone’s attention: by 2030, 70% of the skills required for the average job will have changed.
Let’s reflect on this. 70%. As Raman puts it: «By 2030, virtually everyone who has a job will be in a new one, because the skills required for each position will change radically.»
This isn’t just a gradual shift in how we work. We’re witnessing nothing less than a complete reinvention of the labor market, one that could finally fix what has been failing for ages.
Why the Labor Market Has Always Been Broken
The traditional labor market has been fundamentally flawed from its inception. “The labor market is one of the least transparent, least dynamic, and least equitable markets that humanity has ever created,” Raman told me.
During our goods-based economy, it was “explicitly exploitative,” necessitating laws to prevent child labor and unsafe working conditions.
Even in our current knowledge economy, the labor market has been “implicitly career-biased.
Do you have the right degree from the right university?
Do you have the right connections?
Do you have the right position at the right prestigious company?”
These signals boil down to guesswork about who might be a good fit for a job, rather than a direct assessment of skills.
AI is about to make this flawed system unsustainable.
Why? Because AI forces us to think of jobs not as titles, but as sets of tasks that require specific skills. And as those tasks change, we need to better understand the skills people possess and the skills that jobs require.
The Four Phases of Economic Transformation
According to Raman, we are going through four distinct phases as AI transforms work:
«The first phase is disruption, and we’re seeing that in terms of AI adoption, with people using AI tools at work,» he explained.
The next phase is job transformation: that 70% skills shift mentioned earlier.
The third phase involves the creation of entirely new roles. Raman reminded me that «10% of all jobs in the world today didn’t exist at the beginning of the century.» Data scientists and social media managers simply weren’t job titles when the knowledge economy was taking shape.
Finally, we’ve arrived at a new economic paradigm. Raman calls it “the innovation economy,” where creativity, imagination, and human innovation capabilities become fundamental to value creation.
The Paradox of Expertise
Imagine trying to find a world-class conductor who can also build violins from scratch. That’s often what companies are looking for when searching for AI directors: technical experts who also excel at business transformation at the corporate level.
This search for the ideal candidate often ends in one of two compromises: hiring technical experts who understand neural networks but struggle with organizational change, or selecting business leaders who can’t gain the trust of AI teams because they lack technical expertise.
One tech company I advised hired a renowned machine learning researcher as its Chief Intelligence Officer (CAIO). While she was brilliant at developing algorithms, she struggled to translate her technical skills into business value. The company’s AI initiatives became increasingly academic and disconnected from market needs.
On the other hand, a retail company appointed a seasoned business executive to the position. He excelled at stakeholder management but lacked the technical expertise to evaluate vendors’ increasingly outlandish claims about AI, leading to several costly mistakes.
This paradox of experience creates an impossible standard that predisposes even the most talented leaders to failure.
The Three-Category Analysis for Your Job
While this transformation may seem overwh
