In the past two years, generative AI has not just disrupted how people work in tech, but also their ability to remain employed. For the most of the tech workforce, it’s been a case of adapt or die. The massive number of layoffs that have occurred, provide the evidence to back up this train of thought. AI has replaced many junior roles already and some stay that this trend is likely to continue as AI moves up the ranks and advances its capabilities.

This is of course assuming that AI doesn’t make mistakes, ever. And that development continues as it is, largely unregulated, often unchecked. Sure, there are discussions about governance and ethics, but they’re not slowing development in any way. AI may be getting smarter, use cases may be expanding, and mid-range employees might be feeling the heat, but they shouldn’t write off their expertise just yet.

While the general trend of the large two years shows massive layoffs, that trend is starting to reverse, with industry reports showing a turnaround in the number of vacancies and people being hired in the tech industry.

AI has gotten ahead and now companies are trying to catch up. They are realizing that they need skilled people to help manage AI integrations, trouble shoot problems, oversee cybersecurity, and be the safety stop to check that AI is delivering accurate and relevant data. Not to mention the need for people with technical expertise that can give input into AI governance and help to formulate ethics that will help to protect people’s privacy and data.

With all this talk of adapt or die, companies shouldn’t lose sight of the value of technical expertise. AI might be able to process massive data sets much faster than a human, but it doesn’t yet understand the nuance of decision science. Probably because as humans, decision making is never a linear process.

There are so many factors that influence even the simplest of decisions – like whether to have a bacon and cheese burger or tacos for supper. With this in mind, how does a developer write the rules for decision making so that AI can consistently make better decisions. Leave one factor out and the decision-making process is altered. Trying to create a consistent process is highly challenging especially as machine learning is still very far behind humans when it comes to grasping nuance, context or emotion.  Heck, even most psychologists won’t be bold enough to claim they understand it all.

The point is, that as long as AI is being used for human application and there is human decision making involved, companies will still need humans and their tech skills. These skills may evolve alongside tech advancements, but they will be far from obsolete. Advancement is due to human innovation, let’s not forget that. Tech skills in software development, robotics and data science still hold value and companies are starting to realise this. Tech expertise has shaped the world we live in today. They’re not going to be left behind.