Building an AI-First Workforce Through Effective Upskilling Strategies - The Bedrock to your AI Strategy
- Beyond Team
- 16 minutes ago
- 2 min read
There’s a bit of a Wild West going on with AI right now.
Everyone’s experimenting - marketing with ChatGPT, HR with Co-Pilot, analytics teams with Gemini - and most of it’s happening without much coordination. Some of it’s brilliant. Some of it’s chaotic. And some of it, if we’re honest, is probably a GDPR nightmare waiting to happen.
It feels a lot like what happened when ERPs, data platforms, and BI tools first arrived. Everyone wanted in. Everyone built something. A few years later, we were left with over-engineered systems, conflicting versions of the truth, and a lot of very expensive shelfware.
AI is heading the same way — unless we deal with the people side first.
The uncomfortable truth
IBM found that while almost 90% of leaders say their teams need better AI skills, only 6% have actually started any serious upskilling. IBM Think
That’s not a small gap. It’s more like a canyon.
And it matters because without a workforce that understands AI, how it works, where it helps, and where it shouldn’t be used, all the investment in tools and platforms just adds another layer of digital clutter.
What upskilling really means for your AI strategy
AI upskilling isn’t about turning everyone into prompt engineers or data scientists. It’s about helping people feel capable and confident using the tools that are becoming part of everyday work.
That means:
Knowing when to use AI and when not to.
Asking the right questions and checking the answers make sense.
Understanding bias and data privacy risks.
Seeing AI as a colleague, not a replacement.
Gartner calls this building an “AI-first workforce” — but what it really means is creating a culture where people are comfortable learning as fast as technology changes.
The people part of strategy
It’s easy to get distracted by the tech side of AI strategy — platforms, models, governance, data infrastructure. But none of it works unless people know how to use it and trust it.
At Beyond, we’ve seen this play out too many times. The tech gets installed, the dashboards get built, and the business still can’t make decisions because no one understands what they’re looking at.
AI is no different. If people don’t have the skills, confidence, and context to use it well, it just becomes another expensive tool that doesn’t change anything.
The fix isn’t another platform. It’s people.
Get your teams learning, experimenting, and sharing what works. Keep it practical. Keep it human. And make AI part of how people think, not just something new they’re told to use.
AI strategy starts with people. The tools will keep changing; your people need to know how to keep up.
