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AI skills are two fold, and we need different employees for both

You have the heart of AI skills. Many employers are looking for those regardless of role.

What does the future of AI promise? Image by Tim Sandle.
What does the future of AI promise? Image by Tim Sandle.

With considerable business talk around what skills are needed to be successful with AI, it is often challenging for leaders to decipher between AI soft skills and AI technical skills.

While soft skills are the big trend right at the moment, there will always be a need for engineers and programmers. However, soft skills will play a big role in establishing who works with AI.

Sara Gutierrez, Chief Science Officer at SHL, sees AI skills as a twofold phenomenon: those with technical skills and those with soft skills, as she explains to Digital Journal.

According to Gutierrez those soft skills are going to propel employees to greater heights: You have the heart of AI skills. Many employers are looking for those regardless of role. We’re not currently to the point where every job seeker needs to have those very specific AI skills.”

As to what the current trajectory is, Gutierrez acknowledges: “Instead, we’re going to see employers looking for job seekers who have more human universal skills that can be transferred from job to job. Skills that are broader competencies around problem solving.”

Yet there is also a growing business demand, which Gutierrez conceptualises as: “AI often involves tackling complex real world problems and employers are likely to value those candidates who can demonstrate strong problem solving abilities, critical thinking skills, and the ability to approach challenges creatively.”

In terms of the importance of training and assessment, Gutierrez observes: “Going side by side with those other competencies or skills that are compatible with AI, and that will really allow those technical skills to come together with some of these more human skills, would be the ability to learn.”

This requires a flexible approach to training, says Gutierrez: “Agile learners, who can quickly embrace new technologies and ideas, and adapt those seamlessly to the different AI tools or methodologies that might be coming from more of those technical skilled employees.”

However, Gutierrez acknowledges that it will always be important to have the skills needed to further develop and integrate generative AI. Here she notes: “AI skills could be those more technical skills that employers may be looking for. Skills that really reflect the technology of artificial intelligence, machine learning, data analysis.”

As to hat this entails: “These might include things like looking for somebody who has proficiency in specific tools. Other AI skills might be around data analysis or interpretation. So often, AI relies on large datasets you’ve got to use for training and inference, so employers may seek candidates who are proficient in data analysis.”

More specifically, Gutierrez states: “That could include very specific AI skills like feature engineering, various statistical modelling techniques, etc. More AI skills might be an understanding of algorithms and how you can apply those through machine learning. Whether that’s supervised or unsupervised learning models.”

Summing up the advantages, Gutierrez finds: “Being able to select the appropriate algorithm is going to be important if you’re working in building AI, tools and technology. Then of course, programming,  because programming is critical for really any kind of AI development.”

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Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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