I just got access to the latest work data and it supports a lot of my own observations.
Randstad’s Workmonitor 2026 surveyed thousands of workers globally about AI adoption, workplace dynamics, and career concerns. The numbers back up what I’ve been seeing firsthand: we’re not just surviving the AI transition, we’re built for it.
We’re Less Worried About AI Than Gen Z Is
Here’s the core stat that genuinely surprised me: only 36% of Baby Boomers worry about AI displacing them. Meanwhile, 51% of Gen Z and 47% of Millennials are anxious about it.
We’re supposedly the ones threatened by technology, but in reality we’re the ones who aren’t panicking about it.
I think I know why. We’ve been through this before. Multiple times. From PCs to mobile to cloud; we all watched people predict the end of relevant skills with every new wave. and while the tools changed, most business problems stayed the same.
I’ve seen companies chase technology for its own sake - and I am occasionally guilty of the “shiny object syndrome” myself.
We’ve watched “transformational” initiatives fail because they optimized for execution (“just get it done”) without understanding strategy (“why are we doing this again?”). We know the difference between what sounds impressive in a demo and what actually works in practice.
This kind of pattern recognition is the skill AI makes most valuable, and we have decades of it.
Most of Us Want to Learn AI. We Just Can’t Find Practical Guidance
Here’s the stat that should kill the “resistant to change” narrative once and for all: 68% of professionals over 50 are actively seeking to build AI skills. 🤯
We’re not resistant. We’re motivated. The problem is most AI training is built for people who want to build AI, not use it. It’s either remedial (“what is AI?”) or highly technical (“here’s how to fine-tune a transformer model”). Nothing in between for those of us who need to apply this stuff to actual work.
I don’t need to understand how a neural network processes tokens. I need to know how to use AI to analyze market data faster than my competitors, draft strategic documents in minutes instead of days, and automate the 60% of my job that doesn’t require my expertise.
Two-thirds of us are looking for practical guidance. Most of us aren’t finding it.
The ROI Is Real: 27% Higher Retention for AI-Skilled Workers
Employees who developed AI skills showed 27% higher retention rates than those who didn’t.
Companies aren’t replacing us with AI. They’re investing in us when we learn to use it.
A 30-year-old with AI skills can execute faster. But they don’t know which problems are worth solving. They can’t spot when a technically correct solution will fail politically. They haven’t lived through enough market cycles to recognize patterns that data alone won’t reveal.
We have the judgment. AI gives us execution speed. The combination is more valuable than either alone—and the retention data proves it.
The Rest of the Data Backs Up What We Already Know
A few more stats worth noting:
76% of Baby Boomers show the highest authenticity at work (Gen Z: 68%, Millennials: 70%). We’re not pretending to be someone we’re not. We’ve earned the right to be ourselves.
78% of us rely on multigenerational perspectives—the highest of any generation. So much for being resistant to change or stuck in our ways.
95% of employers say multigenerational teams boost productivity. The business case for keeping experienced workers isn’t charitable. It’s competitive advantage.
72% of employers agree traditional career paths are outdated. We can pivot. We don’t have to retire. Strategic repositioning beats fighting ageism.
Where the Opportunity Is
1 in 5 workers think AI will have limited impact on their tasks. That’s a massive underestimation, and it creates opportunity for those of us who get it right. If 20% of your competitors think AI won’t affect them while you’re mastering it, your competitive position in 12 months looks pretty good.
47% believe AI benefits companies more than employees. They’re not wrong—if you wait for your company to upskill you. But if you develop AI capability independently, you control the leverage. I’m not waiting for permission or depending on company training budgets. I’m building my own toolkit.
Only 26% consider themselves “AI-ready.” Even among those actively learning AI skills, three-quarters don’t feel confident yet. We don’t need a computer science degree. We need clear guidance on which tools to use, how to use them, and what to use them for. That’s the confidence gap practical education solves.
What I Take From This
The Randstad data backs up everything I’ve been saying about experience and AI:
- Experience + AI creates an exponential advantage (not a liability)
- Most of us want to learn this stuff (68%), we just haven’t found practical guidance
- The business case is clear (27% higher retention for AI-skilled workers)
- The competitive window is open (20% of people think AI won’t matter to their work)
We’re not playing defense against obsolescence. We’re playing offense.
I’ve watched this pattern before: the professionals who combine deep expertise with new tools command premium positions. The ones who don’t end up competing on execution speed alone—exactly where technology commoditizes human labor.
This time isn’t different. The tool is just more powerful.
Where to Start
If you’re in the 68% who want to build AI skills but haven’t found practical guidance yet, here’s what I recommend:
Start with AI you can use today. ChatGPT for research and writing. Claude for complex reasoning. Industry-specific tools that solve problems you actually have.
Focus on application, not theory. You don’t need to know how AI works. You need to know what AI does well and what it doesn’t. Master the prompts that turn your expertise into AI-amplified output.
Build capability incrementally. Replace one manual process with AI this week. Automate one repetitive task next week. Use AI for one strategic decision the week after.
I’ve learned more by using AI for real work than I ever would have from courses or certifications. The professionals who wait for perfect understanding before starting will be lapped by those who learn through application.
The data says we’re ready. Now we just need to start.
