PwC released its 2026 Global AI Jobs Barometer on June 15, and the headline finding is harder to ignore than most annual workforce reports: AI is not flattening the job market — it’s splitting it in two.

After analysing more than one billion job advertisements across 27 countries and six continents, PwC’s research team identified a clear divide forming between workers and companies that are learning to work with AI and those being left behind by it.

The Two-Track Market

PwC labels the divide as “professionalised” versus “democratised” roles.

Professionalised roles are positions where AI takes over the routine and mechanical work — processing, lookup, basic drafting — so that the human in the role can spend more time on judgment, creativity, and leadership. Think radiologists whose AI handles image triage, or recruiters whose AI manages screening and scheduling.

Democratised roles are positions where AI can now do most of what the human was doing — narrowing the advantage of experience and expertise. IT service managers and medical secretaries are cited as examples where the barrier to entry has dropped, and so has the compensation premium.

The gap between these two tracks is significant:

• Professionalised roles are growing at twice the rate of democratised roles in job availability
• Professionalised roles are seeing 42% faster salary growth than their democratised counterparts
• Jobs requiring specific AI skills are growing almost eight times faster (69% growth vs. 9% for the overall job market)
• The average wage premium for AI skills has risen to 62%

Companies Are Diverging Too

The barometer doesn’t just track individual roles — it also tracks what’s happening at the company level, and the divergence is just as stark.

Companies that are most capable of using AI are growing headcount 52% faster than the least AI-exposed companies (36%), and they’re growing wages 24% faster as well (24% vs. 17%).

In other words, the gap isn’t just about which workers get ahead — it’s about which organisations can attract and retain the best people, move faster than competitors, and build compounding advantages over time.

Entry-Level Is Where It Gets Interesting

One finding that deserves more attention: AI-exposed entry-level roles are now seven times more likely to require skills that used to be considered senior-level — things like judgment, leadership, and the ability to interpret and act on ambiguous information.

That’s a significant shift. Companies used to hire junior staff to do the legwork and learn the ropes. Now, AI is doing the legwork. Junior hires who can operate at a more senior cognitive level from day one are increasingly what employers want.

This creates an obvious pressure point: the pipeline of talent that used to come up through procedural roles and build experience over time is being disrupted. Organisations need to think differently about how they develop people, not just how they recruit them.

What This Means for Business

If you’re running a business and wondering why this matters, here’s the short version: the premium is shifting from task execution to judgment.

Every role in your organisation that involves interpreting data, making decisions, or advising clients is becoming more valuable — provided the person in that role can work effectively with AI. Every role that involves routine processing, data entry, or rule-based decision-making is facing compression in both compensation and demand.

That means two things for any serious business:

1. AI fluency is no longer optional for your team. Not “everyone needs to code,” but everyone who touches data, makes decisions, or communicates with clients needs to understand what AI can and can’t do, how to verify its outputs, and how to use it to do better work. That’s a training investment, not a technology investment.

2. The businesses winning in this environment aren’t just deploying AI — they’re building teams that can direct it. The barometer data makes clear that organisations leading on AI adoption are growing faster in both headcount and wages. They’re not replacing people wholesale; they’re attracting people who know how to work with AI, and those people are producing more.

The Skills That Actually Matter

According to the barometer, the skills driving the premium in professionalised roles are not technical in the traditional sense. Employers are increasingly asking for:

• Judgment and critical thinking — knowing when AI is wrong
• Communication and leadership — translating AI outputs into decisions and direction
• Domain expertise — the context AI can’t infer from data alone
• Data literacy — understanding what the numbers mean, not just how to pull them

Data literacy sits at the foundation of all of these. You can’t catch an AI error if you don’t understand what the data should look like. You can’t lead a team effectively if you can’t read a dashboard or challenge a model’s assumptions.

Where Enterprise DNA Fits

This is the research confirming what Enterprise DNA has been building toward for over a decade. The 220,000+ professionals who’ve come through EDNA’s platform didn’t just learn Power BI or Python — they built the ability to think clearly about data, ask better questions, and make better decisions with the information in front of them.

Those skills are now the premium. The barometer isn’t predicting that; it’s measuring it, across a billion job postings in 27 countries.

If you’re a business leader wondering how to build a team that benefits from AI rather than being pressured by it, the answer starts with data literacy and AI fluency. That’s not a coincidence — it’s the research.

Explore EDNA Learn’s data and AI training programs to see how your team can build the skills the barometer is rewarding.