Strategy And Planning

No coding skill can save you from AI? IBM talent chief says these 2 skills will matter most

October 5, 2026
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Employers appear to be placing greater emphasis on the ability to assess situations, question information and make decisions when there is no straightforward answer, while employees may still be focusing more heavily on technical capabilities. />For college students and young professionals entering the workforce, the first few years of a career have traditionally been about learning by doing. Junior employees handled routine assignments, made small decisions, learnt from mistakes and gradually developed the judgement needed to take on more complex responsibilities.<br><br><!– PROMOSLOT_M –>Artificial intelligence is beginning to disrupt that progression. As AI takes over more of the repetitive work that once served as training ground for entry-level employees, young workers face a new question: if machines are doing the work through which people traditionally gained experience, how do they build the skills that will make them valuable?<br><br><!– PROMOSLOT_M –><div class=” article-detail-ad-slot=”” captionrendered=”1″ data-src=”https://etimg.etb2bimg.com/photo/134683884.cms” height=”442″ loading=”eager” src=”https://hr.economictimes.indiatimes.com/images/default.jpg” width=”590″></img></p> </div> <p>According to Aparna Nair, IBM’s chief talent, leadership, and culture officer, two abilities could become particularly important: critical thinking and judgement, especially when dealing with uncertainty and ambiguity, she mentioned in an interaction with CNBC Make It.</p> <h2>AI may be taking away the traditional learning curve</h2> <p>Nair, speaking to CNBC Make It, said entry-level employees need to concentrate on developing critical thinking and judgement because some aspects of work are changing rapidly, while other capabilities remain distinctly human.</p> <p>The challenge is that AI is increasingly performing some of the tasks through which young employees previously built professional judgement.</p> <p>“Traditionally people were building judgment through actually doing the work,” Nair said. But with AI now performing some of that work, “that piece of work is no longer there.”</p> <p>That creates a paradox for early-career workers. They have access to powerful tools that can help them complete assignments faster, but relying on those tools too heavily could also deprive them of the experience needed to understand why a particular decision is right or wrong.</p> <p>Nair believes one way forward is to make AI itself part of the learning process, rather than simply allowing it to replace the work.</p> <p>“Actually validating the inputs of AI,” she said, can help employees develop their judgement.</p> <h2>IBM survey highlights a skills gap between employers and workers</h2> <p>The concern is reflected in IBM’s research. A September survey of 1,500 chief human resources officers and 8,800 employees worldwide found that employers and workers do not always view the importance of these skills in the same way.</p> <p>About 57% of CHROs surveyed identified critical thinking as an important skill in the AI era, compared with 49% of employees.</p> <p>The gap was even wider when it came to judgement under uncertainty and ambiguity. Around 48% of CHROs considered it important, while only 29% of employees did.</p> <p>The findings point to a potential disconnect in the workplace. Employers appear to be placing greater emphasis on the ability to assess situations, question information and make decisions when there is no straightforward answer, while employees may still be focusing more heavily on technical capabilities.</p> <h2>AI could erode the very skills workers need</h2> <p>There is another complication. AI may not merely change which skills workers need; excessive dependence on it could weaken some of those skills.</p> <p>According to the IBM survey, three in four concerned employees said AI had already begun eroding some of their skills. Critical thinking was among the abilities most frequently identified.</p> <p>That creates a difficult equation for young workers. The technology can help them produce more work, but using it as a substitute for thinking could leave them with less experience of solving problems independently.</p> <h2>Young workers need to question AI, not simply follow it</h2> <p>For an entry-level employee, developing critical thinking does not necessarily mean rejecting AI. It means treating AI-generated information as something to evaluate rather than automatically accept.</p> <p>A young employee using AI to draft an analysis, for instance, could ask: Are the assumptions correct? Is the information complete? What could the system have missed? Does the conclusion actually make sense in the context of the business?</p> <p>That process can turn AI from an answer-generating machine into an additional source of information that still requires human scrutiny.</p> <p>Nair also suggested that workers can strengthen these abilities by asking more questions, considering different perspectives, thinking several steps ahead and observing how experienced decision-makers approach problems.</p> <h2>How can freshers prove they have these skills?</h2> <p>The challenge for students and fresh graduates is not only developing critical thinking but also demonstrating it to prospective employers. Job interviews and take-home assessments also offer opportunities to demonstrate judgement.</p> <p>Instead of merely explaining what they produced, candidates can explain why they chose a particular approach, what they decided to handle themselves, where they used AI and how they verified its output.</p> <p>That distinction could become increasingly important as employers become more accustomed to AI-assisted applications and work.</p> <h2>Technical skills will change, but judgement remains valuable</h2> <p>The rise of AI does not mean technical skills are becoming irrelevant. Rather, the shelf life of some technical skills may become shorter as technology changes the tasks associated with them.</p> <p>The ability to determine whether information is reliable, identify a flawed assumption, understand context and make a decision when the answer is not obvious is harder to automate completely.</p> <p>For students and entry-level professionals, that makes the early years of a career particularly important. The goal may no longer be simply to complete as many tasks as possible. It is also to understand the work deeply enough to question the output of the tools being used to perform it.</p> <p>As Nair put it, workers need to remain in a mindset of “continuously shaping and building new skills.”</p> <p>For the generation entering workplaces increasingly populated by AI tools, that may be the most important career lesson of all: the advantage will not necessarily belong to those who can make AI do the most work, but to those who know when its work should be questioned. </p> <div> <div aria-label=

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