Future of Work Research: What WEF and McKinsey Tell Us

Why this research matters to you

Most of us read headlines about AI and jobs and get a mix of fear and hype. So I went to the source reports. The World Economic Forum and McKinsey Global Institute both survey a huge number of employers and model the labor market in detail. You do not have to agree with every number, but they show the direction clearly. And direction is what helps you plan your hiring, your bench or your career.

What the World Economic Forum found

The WEF Future of Jobs Report 2025 is based on a survey of more than 1,000 large employers worldwide. Here are the findings I think matter most.

More jobs created than lost, with big churn

The report expects about 170 million new jobs to be created by 2030 and about 92 million to be displaced, for a net gain of about 78 million. That churn equals about 22 percent of today's jobs. So the total number of jobs grows, but a lot of people will be changing what they do.

Skills are moving fast

Employers in the survey expect 39 percent of workers' core skills to change by 2030. Think about that for a minute. Even if your job title stays the same, a big part of what you need to know could be different.

Fastest growing and fastest declining roles

• Growing fastest: big data specialists, fintech engineers, and AI and machine learning specialists lead the list, followed by roles like software and applications developers and security management specialists.
• Declining fastest: clerical roles such as postal service clerks, bank tellers, data entry clerks, and cashiers and ticket clerks.

Plus, roughly four in ten employers in the survey expect to reduce headcount where AI can automate tasks, while most plan to upskill their current workforce. That combination tells you companies want to keep people who can adapt.

What McKinsey's research adds

McKinsey Global Institute looks at the same question from the task level. In Generative AI and the future of work in America, it estimated that activities accounting for up to 30 percent of hours worked in the US could be automated by 2030, and projected about 12 million additional occupational transitions.

The newer McKinsey report Agents, robots, and us goes further. It says current technologies could in theory automate activities covering about 57 percent of US work hours. But the authors are clear that this is technical potential, not a forecast of job losses. They also found that more than 70 percent of today's skills are used in both automatable and non automatable work, and that demand for AI fluency in US job postings grew nearly sevenfold in two years.

So the message from McKinsey is not "robots replace people." It is that work gets redesigned around people, AI agents and machines working together, and the value comes from how well companies redesign that work.

Reading these numbers the right way

One caution before you act on any of this. These reports are global or national averages built on employer surveys and models. Your city, your industry and your specific role can look very different. A data entry clerk at a hospital and a data entry clerk at a bank face different timelines. So use the research for direction, then check it against what you see in real job postings and real requisitions in your market. That is also what we do on the staffing side before we tell a client where demand is going.

Where the corporate world is heading

Put the two bodies of research together and a few patterns stand out.

1. Skills over titles. Companies will plan around skills because titles change slower than the work.
2. Continuous upskilling. Training becomes a normal part of the job, not a one time event.
3. Workflow redesign. The biggest gains come from rethinking whole processes, not adding AI to one step.
4. More demand for tech, data and security people. Someone has to build, secure and govern these systems.
5. Flexible talent models. Companies will mix full time staff, contractors and project teams to keep up with changing skills.

What companies can do with AI now

• Pick a few processes, not everything. Start where work is repetitive and data heavy, like reporting, testing, claims processing or document review.
• Pair AI with people who know the domain. An AI tool in revenue cycle or claims still needs someone who understands the business rules.
• Train your current team. The WEF findings suggest most employers prefer to upskill. Its often faster than hiring for every new skill.
• Bring in specialists for the gaps. Use contract or SOW teams for data, AI and security work while your team ramps up. Our consulting projects page explains how that can work.

What professionals can do

If you are an IT professional, the research gives you a clear to do list. Learn the AI tools in your field and use them on real work. Build skills that sit close to growing areas like data, cloud, security and AI. Add domain depth in an industry such as healthcare, finance or supply chain. And keep proof, certifications and project results, that you can show a hiring manager. Our article on IT certifications that add value is a good starting point.

What this means for staffing vendors

For vendors, this research says the requisitions will keep shifting. More data, AI, cloud and security roles. More hybrid roles where a BA or QA person is expected to use AI tools. Fewer purely clerical roles. Vendors who build benches around growing skills, and who can verify those skills, will be the ones primes and MSPs call first. See how we partner on our vendor partners page.

Written by

Israr Kazmi

Israr Kazmi is the founder of iCareTechno, the IT staffing, recruitment and consulting division of iCareBilling LLC in Chicago. He writes about hiring, vendor relationships and careers in IT.

More about the author