When we talk about skills and competencies, it's easy to get caught up in the excitement of AI. But let's pause for a moment. While AI can play a valuable role in building skills, applying it to competencies raises serious questions, ones organisations in high-risk sectors can't afford to ignore.
Skills vs Competencies: It's About Application
First, I'll continue to highlight the differences between these as it's terribly important they are not used interchangeably:
- Skills are straightforward: they're specific abilities, like learning to code or operate machinery, which can often be gained through training or practice. AI is already proving its worth here, offering tools and programs that teach and up-skill efficiently.
- Competencies, however, are about how those skills are applied in the real world. They encompass behaviours, decision-making, adaptability, and judgment, things that go beyond ticking boxes. Competencies ensure that individuals can not only do the job but excel in environments where stakes are high and precision is critical.
AI and the Growing Skills Gap
This week, the global conversation around AI has once again highlighted a growing problem: while we're investing heavily in up-skilling, the gap in real, practical expertise is widening.
- Google's Global AI Education Push: with $120 million invested in AI education, Google's efforts focus on equipping both workers and governments with the knowledge to navigate this technology responsibly. But it raises the question: where will this expertise come from, and how will we ensure it's applied effectively? (reuters.com)
- Microsoft's Skills Initiative in South Africa: Microsoft's plan to train 1 million South Africans in AI and cybersecurity by 2026 is another example of the global emphasis on up-skilling. But success will depend on more than certifications. It will require a competent workforce capable of applying AI insights in practical, impactful ways. (reuters.com)
What these initiatives reveal is a common issue: we're not just short on technical know-how. We're woefully short on professionals with real, practical business experience in AI, people who've tested these tools, achieved results, and can guide others to do the same.
Why AI in Competencies Is Risky
Here's the challenge: while AI is a powerful enabler of skills training, letting it assess competencies is fraught with risks:
- Bias in assessments: AI models are only as unbiased as the data they're trained on. If historical data reflects biases, AI-driven assessments will too, potentially disadvantaging certain groups or reinforcing stereotypes.
- Lack of context: competencies are deeply contextual. For example, the way someone leads a team during a crisis can't be reduced to patterns in data. AI struggles to account for nuance, ethics, and the human factors that are central to competency assessment.
- Fake competence: over-reliance on AI risks creating a façade of competence, an illusion based on algorithms rather than reality. This is dangerous in high-risk sectors, where fake assessments can lead to misplaced trust, increased risks, and catastrophic failures.
Why Competencies Are Human-Led
Competencies aren't just about performing tasks. They're about critical thinking, judgment, and decision-making in complex, real-world scenarios. These require human oversight, not algorithmic shortcuts.
Competency assessment should remain a human-led process.
This is where organisations must tread carefully. While AI can support learning and skills acquisition, competency assessment should remain a human-led process, informed by ethical frameworks and real-world insights.
How eSQEP Protects Competency Standards
At SQEPtech, we take these challenges seriously. Our approach is built on ensuring that organisations in high-risk sectors have a robust, human-centric method for competency management:
- Human-driven assessments: our platform provides tools to assess competencies through real-world evaluations, avoiding the risks associated with AI-led judgment.
- Uncovering genuine competence: eSQEP doesn't just measure skills. It evaluates how they're applied in context, ensuring organisations know who they can truly rely on.
- Supporting ethical AI use: while we leverage AI for efficiency and insights, we draw a firm line when it comes to decision-making around competencies.
The Bottom Line
AI is transforming how we learn and develop skills, and that's a good thing. But when it comes to competencies, the stakes are too high to risk fake assessments or biased algorithms. Competencies are about trust, context, and human judgment, qualities that no AI can replicate.
At SQEPtech, we help organisations navigate this balance, using AI where it adds value and ensuring that human oversight remains at the heart of competency management. Because in high-risk sectors, getting this right isn't optional. It's essential.
Originally published on LinkedIn.