There are $1 trillion reasons to have AI as a key skill in 2025

For anyone in a technology career, having at least foundational-level AI knowledge is going to be a must from 2025 onwards. The rapid integration of AI across industries—and the fact AI is stealing the majority of investment capital—means understanding how AI works and its limitations will be relevant for all career paths to stay relevant in the workforce.

The signs are all there. Here’s why you should have those AI skills on your resume.

1. Nearly half of companies are planning workforce reductions due to AI, but AI will likely create more jobs than it takes

The bad news that everyone saw coming since 1872 is that yes, AI is going to result in job losses. 40% of companies are planning workforce redundancies due to AI automation, according to the World Economic Forum (WEF)’s Future of Jobs Report 2025.  

Still, there’s good news. AI is expected to create 170 million new jobs globally even as it eliminates 92 million, which is a net increase of 78 million. According to the WEF, this is part of a plan by “half of employers to re-orient their business in response to AI.”

2. Companies are specifically looking to hire people with AI skills

According to the same WEF report, two-thirds of businesses are seeking to hire talent with specific AI skills. The three most in-demand skill sets right now? AI and big data expertise, networks and cybersecurity, and technological literacy, in that order.

3. Nine out of ten IT jobs will be altered by AI

92% of IT jobs will see a high or moderate level of transformation due to AI, according to research by the AI-Enabled ICT Workforce Consortium. The biggest changes will be seen in mid-level (40%) and entry-level (37%) technology jobs, as certain skills and capabilities are reduced in relevance due to AI. 

This level of impact is important, because in the past, tech professionals have been fairly comfortable knowing that AI knowledge was only expected from certain career paths like ML engineers or data scientists. The thought pattern was something like “I’m a team leader working in software development, so I don’t need to know about AI.”

However, the reality is now you need at least foundational AI knowledge as a software developer, project manager, cybersecurity specialist, or even a business analyst. This will help you stay competitive against others who have this skill set, and enable you to contribute meaningfully to projects that are likely to include AI-driven components.

According to Pluralsight’s Tech Forecast 2025 report, AI will disproportionately displace entry-level software developers, leading to a shortage of more skilled professionals further down the line.

4. Goldman Sachs is predicting $1 trillion in capex will be invested in AI in coming years

It’s simple logic that if all of the investment money is being spent on AI-related startups and corporate projects, then that’s where the jobs and skills are going to be. 

When Pluralsight attended Web Summit last November—one of the world’s largest tech conferences, and a hotspot for tech investment—more than half of all the startups were AI-focused, showing where the winds were heading. This has been the overwhelming trend at all tech conferences this year, from RSA Conference to AWS re:Invent.

5. AI was the most popular skill among tech learners in 2024

You can infer a lot from what other people are rushing to learn, and according to our research, the #1 skill tech professionals were rushing to learn was AI. Second was Python, which is considered the major code language for AI and ML.

6. Using AI Agent technology such as LangChain can automate significant portions of your busywork

There’s parts of your job that are worth automating away, like monitoring systems, following up with fixes, updating documentation, and generating reports. LangChain agents have the ability to do that, and in the process make you more efficient as a tech professional. At the end of the day, if you can significantly improve your output and reduce your effort, that’s going to make you a more valuable employee.

According to Pluralsight’s Tech Forecast report, the number of tech learners interested in LangChain increased by 167% in 2024 and now ranks in our top 200 searched terms.

7. Whether or not AI is a hype bubble doesn’t change the immediate hiring realities

There’s certainly an argument that AI, specifically generative AI, is consuming a lot of spend with too little benefit. That’s not surprising considering over 80% of AI projects fail, twice that of other projects. Even Goldman Sachs are questioning if the projected $1 billion in spend will pay off in terms of AI benefits and returns. 

However, for anyone working as a technology professional, whether the AI bubble bursts eventually doesn’t affect where companies are at in the present. Right now, companies are turning to AI-savvy specialists to answer their questions and lead their projects, as only 12% of professionals have significant experience working with AI. That means waiting around five years for the hype to potentially die down so you don’t have to learn about AI is probably not the most strategic career move.

8. AI projects are never finished, which means the jobs are there for the whole lifecycle of the AI

I’ve written a dedicated article on why AI projects are never complete and how deployment is just the beginning. A lot of organizations aren’t aware of this going in, which is one of the reasons AI projects fail in the first place. 

These projects require people across a wide range of tech disciplines to succeed—cybersecurity, data, cloud, and leadership. In fact, even the AI literacy of non-tech users is important to the success of these projects. That means knowing AI fundamentals is beneficial no matter your field.

9. If you’re an AI skeptic, being knowledgeable about AI actually gives you more of a say regarding implementation

There’s a big difference between saying “I don’t think we should adopt AI” and being able to point out where, when, and how AI should be used, along with its strengths and weaknesses. AI is not a cure-all, and being the one who knows all about it allows you to be part of the conversation that may stop your organization needlessly adopting it in the wrong use cases.

Conclusion: There’s a lot of reasons to learn about AI as a tech professional, and very little reason not to

There are so many benefits for learning AI—increased job stability and hiring opportunities, greater say in adoption, greater job efficiency. On the flip side, the biggest reason to not learn AI is having to put some time aside to learn it. Weighing the two up against each other, it seems like a clear-cut choice.

If you want to learn more about the particular AI skills and other trends and tools you need to get ahead, read Pluralsight’s Tech Forecast Report 2025. It’s based on expert predictions and research from over 50,000 tech learners and leaders, and is broken down into various tech domains to help you identify the areas to upskill that are relevant to you.