Companies are pouring millions into AI training programs. Yet 70% of digital transformations still fail.
The problem isn’t technical competency. It’s willingness to change.
I’ve watched this pattern repeat itself across Asia Pacific. Organizations send entire teams for data literacy training, roll out fancy e-learning platforms, allocate massive budgets for AI certifications. The World Economic Forum keeps predicting that more than half of all employees need reskilling—and companies keep responding with more training.
The results? Disappointing.
It’s not because people lack knowledge or skills. The real bottleneck is mindset.
The Expensive Myth of Skills-First Training
When new technologies emerge, leadership instinctively focuses on training. The logic seems sound: if people don’t know the tools, how can they succeed?
Here’s what I’ve observed across dozens of implementations: Teams that don’t know when, where, and most importantly WHY to apply their skills often stand still, despite their technical competence. Meanwhile, teams with less technical expertise but a mindset focused on change consistently outperform them.
The difference? One group waits until they’re told. The other starts experimenting immediately.
Three Mindset Shifts That Actually Matter
Through my work with data and technology teams, I’ve identified three critical shifts that determine success:
- From knowing what to do, to knowing what to accomplish – Moving from “what” to “why”—understanding the business outcome you’re trying to achieve, not just the technical steps to execute. Teams that grasp the purpose behind their tools find creative solutions that others miss.
- From certain success, to certain failure – Embracing experimentation means expecting most attempts won’t work perfectly. The fastest learners assume failure is part of the process and iterate quickly rather than seeking guaranteed outcomes.
- From stability to turbulence – Trading the comfort of expertise for the energy of growth. Instead of protecting what you already know, you actively seek out uncertainty and change as sources of competitive advantage.
This matters more than ever because AI is accelerating change across every industry. Tasks that required deep experience are being augmented or automated. The old model of “learn one new tool every few years” is dead.
A Real Example
Several years ago, I worked with two teams implementing the same analytics platform. Team A looked stronger—they had certified data engineers and formal technical training. Team B had one person with technical background and several curious business analysts.
Six months later, Team B was delivering 40% more business value.
Why? Team A focused on mastering the technical steps and features. Team B focused on the business outcomes they needed to achieve. Team A sought certain success and avoided experimentation. Team B embraced failure as part of rapid learning. Team A protected their expertise and waited for stability. Team B actively pursued growth opportunities.
The lesson: technical skills open the door, but mindset determines who walks through it.
What This Means for You
If you’re thinking about your own development, these same principles apply:
When faced with something new, do you wait until you feel “ready,” or are you willing to learn through action?
Do you view challenges as threats to your expertise, or opportunities to grow?
Are you holding onto the comfort of certainty, or building the muscle of adaptability?
These questions matter more than mastering the latest tool. In a world of constant technological change, the ability to keep learning—and to stay open whilst doing so—is the true differentiator.
The Practical Next Step
Instead of asking “What’s the next skill I need to learn?”, try asking:
“What mindset shift would help me maximise the skills I already have?”
That shift might be moving from knowing what to do, to knowing what to accomplish. Or shifting from seeking certain success, to embracing certain failure. Or evolving from craving stability, to thriving in turbulence.
The irony? Once these mindset shifts are in place, skills become easier to acquire. You’ll approach learning with energy instead of resistance.
The Bottom Line
AI will keep accelerating. Tools will change. Skill requirements will evolve.
But mindset—the ability to focus on outcomes over tasks, embrace failure as learning, and seek turbulence as opportunity—will remain the biggest differentiator of professional success.
So the next time you think about development, don’t just ask: “What skill do I need next?”
Ask instead: “How ready am I to change?”
Want to explore what genuine readiness for change looks like? Let’s talk.
