{"id":12318,"date":"2026-09-25T07:46:18","date_gmt":"2026-09-25T07:46:18","guid":{"rendered":"https:\/\/www.evalion-shl.com\/?p=12318"},"modified":"2026-09-25T07:48:55","modified_gmt":"2026-09-25T07:48:55","slug":"ai-is-changing-work-do-you-know-what-your-people-can-do-next","status":"publish","type":"post","link":"https:\/\/www.evalion-shl.com\/en\/ai-is-changing-work-do-you-know-what-your-people-can-do-next\/","title":{"rendered":"AI is changing work. Do You Know What Your People Can Do Next?"},"content":{"rendered":"\t\t
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AI is changing jobs and skills faster than most organizations can respond, which means we need to stop looking only at what people have done before, and start understanding what they could do next<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Artificial Intelligence is more about people than technology<\/b><\/h2>

There is a lot of pressure on organizations to do something with AI right now. To invest. To transform. To redesign work. And, increasingly, to show a return on all of it.<\/p>

As <\/span>Lucy Beaumont, Global SVP of Product and Design at SHL<\/b>, points out, through her ongoing conversations with organizations on workforce-related issues, she has observed that discussions around Artificial Intelligence too often begin with technology rather than people.<\/span><\/p>

Work is not disappearing, but it is changing. And as jobs, individual tasks, and the skills organizations need continue to evolve, a fundamental question emerges: <\/span>Do we really understand the future potential of our employees?<\/b><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Data does not equal insights<\/strong><\/h2>

To understand people better, you need data \u2013 and most organizations I ask always say they have this in abundance, and spend lots of time collecting data, but they don\u2019t always know how it fits together, what they can trust, and how that data can help them make the best decisions about people. AI gives us the ability to infer skills, identify patterns and get a much broader view of the workforce at scale but there\u2019s a difference between data that helps leaders to understand their organization and the <\/span>data to base decisions about people\u2019s futures on<\/b>: Should an individual be promoted? Could they succeed in a different role? Where should they invest in their development? Do they have the potential to lead?<\/span><\/p>

When it comes to turning data into actionable insight, the organizations making the most progress start with the question they are trying to answer and then work backwards.<\/span><\/p>

What data do we need? Do we already have it? Where does it come from? Is it reliable enough to support this particular decision? <\/span><\/p>

Once goals are in place, it\u2019s much easier to see where data adds value and how it can be used most effectively.<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Past performance does not mean future potential<\/strong><\/h2>

Traditionally, past performance has been considered one of the predictors of future performance. But in a transforming work environment, where jobs are changing so rapidly and future roles may not even be predictable, does this approach still hold true?<\/span><\/p>

According to SHL, <\/span>assessing employees\u2019 future potential is by far the strongest predictor of their future performance.<\/b> Understanding this potential enables organizations to answer questions such as:<\/span><\/p>

Can this person learn? Can they adapt? Which of their skills could be applied in a different role? With the right development, what could they do in the future?<\/span><\/p>

This shift is already happening, particularly in early careers where organizations are more interested in finding people they know they can grow as the business changes. This aligns with more organizations transitioning to a <\/span>skills-based<\/b> approach and getting better and faster at <\/span>upskilling<\/b> and <\/span>reskilling<\/b> employees\u2013something expected from today\u2019s workers. Knowing someone has a skill is useful, but understanding what that means for a decision you need to make is much more valuable. And that\u2019s the difference between<\/span> talent data<\/b> and <\/span>talent intelligence<\/b>.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Before we hire someone new, do we know who we already have?<\/strong><\/h2>

One key benefit that talent intelligence brings is an understanding of the skills and potential of the talent that already works within the business. Imagine an organization is automating a lot of its customer service activity. At the same time, it has a growing need for cybersecurity talent. The obvious response might be to reduce one population and hire into another.\u00a0<\/span><\/p>

But what if some of those people already in the organization have the underlying capabilities to move?<\/b><\/p>

As Lucy Beaumont clarifies, this does not mean that every customer service employee can suddenly become a cybersecurity specialist. However, without <\/span>a clear view of the skills and skills gaps that exist within the organization,<\/b> combined with an understanding of the skills required for each role, it is impossible to know which employee moves could realistically take place. And that lack of insight can prove extremely costly.<\/span><\/p>

If we understand how jobs and skills are changing, then organizations can make more intelligent decisions <\/b>about whether to hire from within or undertake a more expensive external hiring process.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Source: AI Is Changing Work. Do You Know What Your People Can Do Next?<\/a><\/span><\/i><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

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