The Future of Jobs: Technology and AI to Drive Divergent Change

Technology is predicted to be the most divergent driver of labor market change, with broadening digital access expected to create and displace more jobs than any other macro trend, according to the World Economic Forum (WEF).

About 170 million new jobs (equivalent to 14% of today’s employment) will be created this decade, according to the WEF’s ‘Future of Jobs Report 2025’. At the same time, 92 million roles will be displaced, creating a net employment increase of 78 million jobs.

Not surprisingly, artificial intelligence (AI) and information processing technology are expected to create 11 million jobs, while simultaneously displacing 9 million others, more than any other technology trend. Robotics and autonomous systems are expected to be the largest job displacer, with a net decline of five million jobs from 2025 to 2030.

However, there is good news about new emerging tech trends like AI. Three of the technology trends — broadening digital access, advancements in AI and information processing, and robotics and autonomous systems technologies — also feature prominently as drivers of the fastest-growing jobs.

Change is the new normal in employment trends.

The WEF report notes the shifting paradigm in the human-machine future of work. The interplay between humans, machines, and algorithms is redefining job roles across industries. Automation is expected to drive changes in people’s ways of working, with the proportional share of tasks performed solely or predominantly by humans expected to decline as technology becomes more versatile.

Survey respondents estimate that 47% of work tasks today are performed mainly by humans alone, with 22% performed mainly by technology (machines and algorithms), and 30% completed by a combination of both. By 2030, employers expect these proportions to be nearly evenly split across the three approaches.

The Human-Machine frontier.

Growth and decline drivers for jobs are based on several factors. Five factors will drive a net creation of 78 million jobs globally by 2030: technological changes, the green transition, demographic shifts, geoeconomic fragmentation, and economic uncertainty. Among these drivers, technological change is expected to have the biggest impact on jobs by 2030, creating and displacing them.

The largest growing category of jobs is farmworkers — 34 million additional jobs by 2030, adding to the 200 million farmworkers today. Delivery drivers, software developers, building construction workers, and shop salespersons complete the top five fastest-growing jobs.

The largest growing and declining jobs by 2030.

According to WEF, employers expect 39% of key skills required in the job market to change by 2030. This figure represents significant disruption but is down from 44% in 2023.

Technological skills are projected to grow in importance more rapidly than any other skill in the next five years. AI and big data are at the top of the list, followed by networks and cybersecurity, and technological literacy.

The job market is in flux.

Creative thinking and resilience, flexibility, and agility are also rising in importance, along with curiosity and lifelong learning. Other fast-rising skills are leadership and social influence, talent management, analytical thinking, and environmental stewardship.

These are the core skills to focus on in 2025.

Today’s core skills blend cognitive, self-efficacy, and engagement skills. Looking ahead to 2030, technology skills dominate the fastest-growing skills, driven by ongoing digital change.

The impact of AI is clear.

So, how will businesses respond to AI developments? The increased use of emerging technologies is prompting half of businesses to realign their organizations. Accelerated AI innovation is creating a strong demand for skilled talent, with over two-thirds of employers planning to hire for AI-specific roles, even as 40% foresee workforce adjustments in response to the technology’s adoption.

To learn more about the WEF’s Future of Jobs Report 2025, you can find the full report here.

FAQs:

Q: What is the predicted impact of technology on the job market?
A: Technology is expected to create and displace more jobs than any other macro trend, with 170 million new jobs and 92 million roles displaced by 2030.

Q: Which technology trend is expected to create the most jobs?
A: Artificial intelligence (AI) and information processing technology are expected to create 11 million jobs, while simultaneously displacing 9 million others.

Q: What are the fastest-growing jobs?
A: The largest growing category of jobs is farmworkers — 34 million additional jobs by 2030, adding to the 200 million farmworkers today. Delivery drivers, software developers, building construction workers, and shop salespersons complete the top five fastest-growing jobs.

Q: What skills are expected to grow in importance?
A: Technological skills are projected to grow in importance more rapidly than any other skill in the next five years, with AI and big data at the top of the list, followed by networks and cybersecurity, and technological literacy.

Over the next two decades, the market for humanoid robots is expected to reach $38 billion. To address this significant demand, particularly in industrial and manufacturing sectors, NVIDIA is releasing a collection of robot foundation models, data pipelines, and simulation frameworks to accelerate next-generation humanoid robot development efforts.

NVIDIA Isaac GR00T Blueprint for Synthetic Motion Generation

Announced by NVIDIA founder and CEO Jensen Huang today at the CES trade show, the NVIDIA Isaac GR00T Blueprint for synthetic motion generation helps developers generate exponentially large synthetic motion data to train their humanoids using imitation learning.

Imitation learning — a subset of robot learning — enables humanoids to acquire new skills by observing and mimicking expert human demonstrations. Collecting these extensive, high-quality datasets in the real world is tedious, time-consuming, and often prohibitively expensive. Implementing the Isaac GR00T blueprint for synthetic motion generation allows developers to easily generate exponentially large synthetic datasets from just a small number of human demonstrations.

Starting with the GR00T-Teleop workflow, users can tap into the Apple Vision Pro to capture human actions in a digital twin. These human actions are mimicked by a robot in simulation and recorded for use as ground truth.

The GR00T-Mimic workflow then multiplies the captured human demonstration into a larger synthetic motion dataset. Finally, the GR00T-Gen workflow, built on the NVIDIA Omniverse and NVIDIA Cosmos platforms, exponentially expands this dataset through domain randomization and 3D upscaling.

World Foundation Models Narrow the Sim-to-Real Gap

NVIDIA also announced Cosmos at CES, a platform featuring a family of open, pretrained world foundation models purpose-built for generating physics-aware videos and world states for physical AI development. It includes autoregressive and diffusion models in a variety of sizes and input data formats. The models were trained on 18 quadrillion tokens, including 2 million hours of autonomous driving, robotics, drone footage, and synthetic data.

In addition to helping generate large datasets, Cosmos can reduce the simulation-to-real gap by upscaling images from 3D to real. Combining Omniverse — a developer platform of application programming interfaces and microservices for building 3D applications and services — with Cosmos is critical, because it helps minimize potential hallucinations commonly associated with world models by providing crucial safeguards through its highly controllable, physically accurate simulations.

An Expanding Ecosystem

Collectively, NVIDIA Isaac GR00T, Omniverse, and Cosmos are helping physical AI and humanoid innovation take a giant leap forward. Major robotics companies have started adopting and demonstrated results with Isaac GR00T, including Boston Dynamics and Figure.

Humanoid software, hardware, and robot manufacturers can apply for early access to NVIDIA’s humanoid robot developer program.

Conclusion

The NVIDIA Isaac GR00T Blueprint for synthetic motion generation, along with the NVIDIA Omniverse and Cosmos platforms, is poised to revolutionize the development of next-generation humanoid robots. By generating large synthetic datasets and reducing the simulation-to-real gap, developers can accelerate their efforts to create more advanced and capable humanoids.

FAQs

Q: What is the expected market size for humanoid robots?
A: The market for humanoid robots is expected to reach $38 billion over the next two decades.

Q: What is imitation learning?
A: Imitation learning is a subset of robot learning that enables humanoids to acquire new skills by observing and mimicking expert human demonstrations.

Q: What is the GR00T-Teleop workflow?
A: The GR00T-Teleop workflow captures human actions in a digital twin using the Apple Vision Pro and records them for use as ground truth.

Q: What is Cosmos?
A: Cosmos is a platform featuring a family of open, pretrained world foundation models purpose-built for generating physics-aware videos and world states for physical AI development.

Nvidia’s Project Digits: A Linux-Powered PC with AI Supercomputer Power

A New Era in PC Performance

Nvidia’s Project Digits is a desktop with AI supercomputer power that runs DGX OS, a customized Ubuntu Linux 22.04 distro. This powerful machine is powered by MediaTek and Nvidia’s Grace Blackwell Superchip, a $3,000 personal AI that combines Nvidia’s Blackwell GPU with a 20-core Grace CPU built on the Arm architecture.

AI Performance and Specifications

Project DIGITS can deliver up to 1 petaflop of AI performance at FP4 precision and support 200-billion-parameter large language models. This impressive chip is designed to bridge the gap between the Linux operating system used by AI developers and Microsoft by using the Windows Subsystem for Linux (WSL).

Why Native Linux?

Why not use native Linux as the primary operating system on this new chip family? Linux, after all, already runs on the Grace Blackwell Superchip. Windows doesn’t. It’s that simple. Linux runs well with Nvidia chips, and recent benchmarks show that open-source Linux graphic drivers work with Nvidia GPUs as well as its proprietary drivers.

Canonical and Ubuntu

Canonical, Ubuntu Linux’s parent company, has long worked closely with Nvidia. Ubuntu already provides Blackwell drivers. Canonical claims, with reason, to offer the best-in-class integrations with Nvidia hardware. These next-generation PCs will be built for Linux.

MediaTek and the Partnership

MediaTek, known for its leadership in smartphone chips, is poised to play a crucial role in this new venture. The collaboration will allow MediaTek to sell the desktop CPU PC vendors. Rick Tsai, MediaTek’s vice chairman and CEO, expressed enthusiasm about the partnership: "Our collaboration with Nvidia on the GB10 Superchip aligns with MediaTek’s vision of helping make great technology accessible to anyone."

The Future of PC Performance

The first consumer products featuring this technology are expected to hit the market later this year. I’m looking forward to running Linux on it. Come on in! The operating system’s fine.

Conclusion

Nvidia’s Project Digits is a Linux-powered PC that combines AI supercomputer power with the efficiency of Arm-based architectures. With the collaboration between Nvidia, MediaTek, and Canonical, we can expect a new generation of AI-powered PCs with significantly enhanced capabilities.

FAQs

Q: What is the price of Project Digits?
A: Project Digits costs $3,000.

Q: What operating system does Project Digits run?
A: Project Digits runs DGX OS, a customized Ubuntu Linux 22.04 distro.

Q: What is the performance of Project Digits?
A: Project Digits can deliver up to 1 petaflop of AI performance at FP4 precision and support 200-billion-parameter large language models.

Q: Why does Project Digits use native Linux?
A: Project Digits uses native Linux because it’s the best choice for this chip family, allowing for efficient performance and seamless integration with Nvidia’s GPU expertise.