Are any skills safe? Why AI is forcing leaders to rethink talent value
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Are any skills safe? Why AI is forcing leaders to rethink talent value
Summary: No skills are truly ‘safe’ in an AI-driven economy - but the definition of valuable talent is changing rapidly.
As Artificial Intelligence (AI) continues to automate technical execution, organisations must shift their focus from ‘high skill’ roles to high-value contributions, redefining how talent is identified, developed and deployed.
What this article covers:
- Why traditional ‘high skill’ roles are becoming less secure.
- How AI is reshaping what valuable talent means.
- The risks of outdated workforce models.
- Four practical ways to futureproof your workforce strategy.
How is AI impacting skills?
When Aditya Agarwal, former CTO of Dropbox, shared this reflection after experimenting with Claude (a conversational Artificial Intelligence system created by Anthropic), it resonated far beyond the technology sector. It reflects a growing realisation across industries: no role - regardless of seniority or perceived skill level - is immune to the impact of AI.
Agarwal’s example reflects a much broader shift: work that once created competitive advantage is rapidly becoming commoditised.
Explore the Tech Talent Explorer and you’ll see how Software Engineers are already experiencing moderate exposure to AI. The focus is no longer on writing code line-by-line, but on architectural design, contextual decision-making and cross-functional collaboration.
At the same time, a second disruption is accelerating. We’re tracking acute talent shortages in skilled labour roles, with 69% of Engineering and Manufacturing organisations reporting ‘Moderate to Extreme’ skills shortages. In the US, it’s estimated that half a million new workers will be needed to sustain the construction industry in the next 12 months.
Together, these shifts are creating a more volatile talent market - where yesterday’s high demand skills can quickly shift focus, while critical roles remain persistently hard to fill.
This dual disruption is forcing organisations to confront a more fundamental question: What does high value talent look like in an AI-driven economy?
The breakdown of the ‘high skill’ hierarchy
For years, organisations have relied on a simple assumption: ‘high skill’ equals degree-led, knowledge-intensive work.
As Financial Times columnist Sarah O’Connor writes, “economists have contributed to this with their habit of describing certain jobs as high skilled, when what they actually mean is ‘jobs that require skills that the market currently values highly’.”
But that definition is becoming increasingly difficult to sustain. Roles once considered ‘safe’ are at the sharp end of disruption, as AI takes on more technical execution. At the same time, essential operational and trade roles are proving more resilient.
As organisations reorchestrate work, we’re seeing value shift towards individuals who can:
- Integrate multiple streams of knowledge.
- Apply judgement in complex, ambiguous or high-pressure situations.
- Translate insight into measurable outcomes – and take accountability for the results.
As Travis O’Rourke, President, Hays Canada, summarises, “high skill used to mean executing tasks to perfection. Now, it’s embodied by those with the ability to orchestrate human and machine intelligence to deliver meaningful outcomes.”
In other words, the premium is no longer on doing the work, but on defining and directing it.
Why legacy job models are a critical risk for leaders
For many organisations, the biggest challenge is not the automation of tasks - it’s the persistence of outdated workforce structures.
Job architectures, hiring criteria and career pathways are still largely designed around static role definitions. But in a market where technology is offloading more tasks, this creates a dangerous structural lag.
As Shane Little, Managing Director, Enterprise Solutions at Hays APAC notes, “the required skills of today are evolving before the ink on tomorrow’s job description has dried.”
For leaders, this is not just an operational efficiency – it’s a strategic risk. And the consequences are already visible:
- Hiring like-for-like roles that don’t reflect the scope of evolving responsibilities.
- Overlooking adjacent or transferable skills that could unlock value.
- Embedding obsolesce into your workforce strategy.
Four ways to futureproof your workforce strategy
To remain competitive, organisations need to move beyond incremental change and take a more systemic approach to talent.
1. Redesign roles for an AI-enabled workforce: Shift from rigid job descriptions to dynamic role architectures that evolve with technology. Focus on outcomes, not tasks - so roles remain relevant as AI capabilities advance.
2. Prioritise skills over credentials: Adopt a skills-first hiring approach to expand access to adjacent talent pools and increase organisational agility.
3. Reposition undervalued sectors: Industries facing acute shortages - particularly in engineering, manufacturing and infrastructure - must rethink how they attract and retain talent. Compete on purpose and progression, not just pay.
4. Build adaptability into the workforce: In an environment where demand signals are increasingly unpredictable, organisations must prioritise agility. Invest in continuous reskilling and internal mobility to respond faster to change.
High value will beat high skill
The question is no longer which skills are ‘safe’. Rather, the focus is shifting to whether your organisation is structured to rapidly align - and realign - with technological change, building a workforce capable of evolving in real time.
As Shane concludes, “universities are churning out graduates who are already behind, while corporate training programmes often lag industry needs.”
In an AI-driven era, competitive advantage will not come from what your people already know, but from how quickly they can adapt, integrate and create value in what they do next.