AI skills are in demand, with a rapid increase in job postings listing skills like generative AI in 2024 compared to 2023. What types of skills are needed to be successful with AI? What should be the balance between so-called AI soft skills and AI technical skills?
Generally, soft skills are the bigger trend; however, it is likely there will always be a need for engineers and programmers. Yet in terms of accessing key organisation roles, soft skills plays a big role in establishing who works with AI.
These trends have been picked up by Sara Gutierrez, Chief Science Officer at SHL. Gutierrez certainly sees AI skills as a twofold phenomenon: those with technical skills and those with soft skills.
Those soft skills, Gutierrez thinks, 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 is happening, Gutierrez deciphers: “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. 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.”
To create the more well-rounded employee, Gutierrez foresees: “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.”
In other words, 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 also acknowledges that it will always be important to have the skills needed to further develop and integrate generative AI.
Here Gutierrez considers: “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. These might include things like looking for somebody who has proficiency in specific tools.”
As to what this entails, Gutierrez puts forward: “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. That could include very specific AI skills like feature engineering, various statistical modelling techniques, etc.”
Clarifying this further, Gutierrez adds: “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. 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.”
