Workforce 2026: How to Prepare Your Team for AI

With AI, the biggest risk sits with people, not the technology. Some don't know how to use it. Others fear it will take their jobs. Both problems can be solved.

The facts

According to research by PwC and Gallup:

• Nearly 1 in 3 entry-level workers worry about AI's impact on the future of their jobs.
• 23% of employees don't even know whether their company has deployed AI.
• 87% have received no AI training at all according to Randstad, even though 55% want more training.

It's a people problem, not a technical one. The same fear comes back a floor up, in the question of what people are worth to a state and to a company once a machine does the work. I took that argument apart in the claim that power stops needing human labour.

Framework: 3 levels of readiness

AI READINESS LEVELS

Level 1: AI Awareness
Understands what AI is, sees the potential, isn't afraid of it.
Level 2: AI User
Uses AI in daily work, knows the tools, writes prompts.
Level 3: AI Champion
Identifies new use cases, trains others, shapes adoption.

The goal: everyone at Level 1, 70% at Level 2, 10-15% at Level 3. This model lines up with the Gartner AI Maturity Model.

Level 2 only starts to make sense once you know what you leave to the machine and what stays with a person.

How to build Level 1: Awareness

The first barrier is fear. You have to address it head-on:

• Communication from the top: The CEO says it plainly, "AI is here to help you, not replace you"
• Transparency: Which processes we're automating, and what that means for people
• Demo sessions: Show AI in action on real tasks
• Success stories: Who's already using it, and what they gained

A demo lands when the screen shows the work of these specific people. Their tasks, their Monday, their standards. That is what I built an AI training for journalists on, in a room where scepticism about the tool is part of the job.

WORK WITH ME

This is what I do hands-on: advising on AI strategy and building agents that survive the demo.

AI consulting AI implementation

How to build Level 2: Users

Hands-on training, not theory:

TRAINING PROGRAM

Week 1: AI basics, ethics, data security
Week 2: Company tools, hands-on workshops
Week 3: Prompt engineering for your specific role
Week 4: Practical project, solve a real problem

Tailor the training to the role. A marketer needs different skills than a financial analyst. The World Economic Forum forecasts that by 2030, 77% of employers will reskill their workforce on AI.

How to spot Champions

Champions aren't always the most technically skilled. They're the people who:

• Experiment with AI on their own time
• Share their discoveries with the team
• Ask "what if we..." questions
• Have their colleagues' respect

"One champion in a department is worth more than 10 hours of training. People learn best from colleagues they trust."

On an engineering team the path looks different. A champion will pull colleagues along on day-to-day tool use, but nobody settles what an agent may do on its own, unasked, over coffee. How to tell whether a team is ready for that conversation is in the post on readiness criteria for working with AI agents.

Changing your HR processes

AI calls for changes across the entire employee lifecycle:

Recruiting: You're hiring for "AI fluency" as a competency
Onboarding: AI training from day one
Performance: Are they using AI? Is it boosting productivity?
Development: Career paths that include AI skills
Role design: New positions, reworked descriptions for existing ones

On the leadership side the shift is just as big. It shows up as six new CTO roles.

What if someone doesn't want to?

There will be people like that. You have three options:

1. Understand the cause: Fear? No time? Bad past experiences?
2. Adjust your approach: Maybe they need a different training format
3. Business decision: If they still refuse even after support, that's a problem to solve

But most people want to grow. Just give them the space and the support.

The bottom line

A team that knows how to use AI and wants to will beat a company with the best technology and people who resist it. Every time. Fund the training before you buy another license. Start with your people.