Demand for Cloud, Data and Cybersecurity Skills Outranks AI

AI skills aren’t the only ones that enterprises are demanding. 

A survey published Tuesday of more than 750 senior technology leaders by Coursera and AWS found that three skills in particular – cloud, data and cybersecurity – ranked above AI skills in critical importance.

Some 95% of participants reported that cloud transformation is a key business goal over the next three years, while only 91% said the same for generative AI. 

AI is a “tool in your arsenal,” but having skills in the other domains accelerates the way enterprises can leverage the trendy new tech, said Mustafa Furniturewala, CTO of Coursera. “Having that domain expertise, having that skill set, actually augments the AI skill set really well.” 

Cloud, data and cybersecurity rank high for a few reasons, said Furniturewala:

• For one, the cloud data transformation isn’t yet complete, he noted. “We’re far from being in a mature state with that.”
• AI also accelerates the use of cloud technology, he noted. “A lot more people are able to build now. They’re able to use cloud and AI and data in ways that are a lot more accelerated.” 
• Plus, while AI is taking up a good deal of enterprises’ brain space, other trends exist, said Furniturewala. “Security attacks have gotten more sophisticated, and so the need for cybersecurity has gotten more important, irrespective of AI.” 

While all of the skills go hand-in-hand in the broader tech transformation, he said, enterprises still need to upskill their workforces to cope with rapid change. 

Leaders are dealing with two transformations, he said: One involves the technology itself, and the other involves the workforce that’s leveraging it. About 88% of leaders surveyed agreed that AI investments wouldn’t succeed without training, and 77% said training is essential in realizing their tech goals over the next 12 to 18 months. 

While 72% said they expect new hires to understand how to leverage AI, 74% recognized that new hires alone couldn’t fill all of the AI skill gaps. “Just doing the technology transformation without doing the upskilling transformation is not going to result in benefits to the organization,” said Furniturewala. 

So how can enterprises keep up? One way is providing workers the tools to experiment with the tech hands-on so that they “learn by doing,” said Furniturewala. Enterprises can implement the tech directly into relevant work, do practical skill assessments and provide risk-free sandboxes that allow employees to feel safe experimenting – and making mistakes. 

“Learning in the flow is extremely important,” he said. “The more you integrate AI in your actual workflows, the more you learn.” 

Assuaging fears of AI replacement may also make workforces feel more comfortable strengthening their tech skills, he said. “Automation is augmentation,” he said. “Despite increasing levels of automation, leaders recognize that human contributions remain irreplaceable.”