Companies are spending lavishly on AI training programs, but 70% of digital transformations still fail. The problem isn’t technical competency—it’s willingness to change. The difference comes down to three critical mindset shifts that skills training typically ignores.
In 2020, and again in 2025, the World Economic Forum predicted that more than 50% of all employees will need reskilling in the next 5 years. I’ve watched organizations respond by pouring millions into upskilling programs, including those aiming to build data and tech capabilities. Entire teams sent for data literacy training or dashboard design. Shiny new e-learning platforms rolled out with promises of transformation. Most recently, massive budgets are of course being allocated to AI certifications.
The results? Disappointing.
Despite significant and continued investment, most organizations still struggle to see meaningful returns from their training initiatives. McKinsey research shows that 70% of digital transformations fail to achieve their targets—and it’s not because people lack knowledge or skills.
The real bottleneck isn’t technical abilities. It’s mindset.
The expensive myth of skills-first training
When new technologies emerge, leadership instinctively focuses on training. After all, AI, automation, and data analytics are highly technical domains. The logic seems sound: if people don’t know the tools, how can they succeed?
But 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 separate winners from losers
Through my work with data and technology teams across Asia Pacific, I’ve identified three critical mindset shifts that determine success:
1. 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.
2. From certain success, to certain failure
Embracing the importance of 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.
3. 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 the pace of change across every industry. Tasks that required deep experience are being augmented or automated. Many jobs as we know them will disappear, while others will evolve and many new ones will arise. This shifts the premium toward capabilities machines can’t replicate: judgment, empathy, adaptability, and the ability to learn quickly. The old model of “learn one new tool every few years” is dead.
A case study in mindset over skills
Several years ago, I worked with two teams implementing the same analytics platform. On paper, 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 “what” – the technical steps and features. Team B focused on the “why” – the business outcomes they needed to achieve. Team A sought certain success and avoided experimentation. Team B embraced certain failure as part of rapid learning. Team A protected their expertise and waited for stability. Team B actively pursued turbulence and growth opportunities.
The lesson was clear: technical skills open the door, but mindset determines who walks through it.
What this means for your personal development
If you’re thinking about your own career development—whether as a leader or individual contributor—these same principles apply at a personal level:
- 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 while 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 maximize the skills I already have?”
That shift might be:
- Moving from knowing what to do, to knowing what to accomplish
- Shifting from seeking certain success, to embracing certain failure
- 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?”
References
- McKinsey & Company – “Common pitfalls in transformations: A conversation with Jon Garcia” (March 29, 2022) https://www.mckinsey.com/capabilities/transformation/our-insights/common-pitfalls-in-transformations-a-conversation-with-jon-garcia
- World Economic Forum – “The Future of Jobs Report 2020” https://www.weforum.org/reports/the-future-of-jobs-report-2020/
- World Economic Forum – “78 Million New Job Opportunities by 2030” (January 8, 2025) https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/