It is a question that lots of people in just about every industry are asking: will AI take over our jobs? The answer is kind of, yes, but the skiing industry demonstrates just how complex a question this is to address.
We’ll come back to skiing later. Let’s start with what we know.
AI technologies are fantastic at automating repetitive tasks. That word “fantastic” is used very deliberately, as repetitive tasks can be completed by AI faster than humans. AI technologies can also complete repetitive tasks without making mistakes, they can work 24 hours a day, and they don’t need holidays.
So, in our specialist area, the technology sector, roles that involve completing repetitive tasks are being replaced by AI. Repetitive programming tasks, data entry, and testing processes are examples.
AI technologies are also excellent at analysis, so those types of roles are also seeing dramatic change.
However, the question of AI taking over jobs can be looked at in two ways: replacing or augmenting.
Replacing vs Augmenting
Looking at AI technologies from a business perspective, people will still be required. The role of AI technologies is typically to augment the work of people. For example, an AI technology that takes over repetitive tasks might make some roles redundant, but it also frees up resources, enabling employees to focus on the more complex, innovative, and/or creative work that AI can’t do.
Therefore, some jobs might change or disappear, but others will become more in demand. The best approach is not to focus on the danger of AI replacing jobs. The focus should instead be on the augmenting effect of AI.
In most cases, this means enhancing existing skills and building new ones. For example, enhancing problem-solving skills to increase your abilities in areas where AI is not effective. Another example is to develop new AI skills so you can help your employer maximise the potential of new AI-driven technologies.
Arise the T-Shaped Professional
Another impact of AI on jobs in the technology sector is the growing importance of T-shaped professionals.
A T-shaped professional is someone who possesses both deep expertise in a specific field (the vertical bar of the T) and a broad understanding of related areas (the horizontal bar of the T). This depth and breadth of expertise combination make them highly versatile and adaptable in a world that is rapidly changing through AI, automation, and other digital technologies.
Our original question was: will AI take over our jobs? “Kind of, yes” was our original answer, but the T-shaped technology professional is significantly more insulated than most.
The Skiing Analogy
Today it is possible to join thousands of other recreational skiers high up on a mountain in a well-established ski resort staffed by an army of ski instructors, ski equipment rental shop assistants, chairlift engineers, après-ski bar tenders, etc, etc.
One hundred years ago, however, you couldn’t do this because the resorts didn’t exist, ski equipment was basic, and the chairlift hadn’t even been invented. New and often highly disruptive technologies made the creation of the recreational skiing industry possible. Take the automotive industry. Back in the early 20th century, this blog might have been concerned about the automobile taking over jobs. For those in the horse and cart industry, the answer was yes, as it was decimated by the automobile.
But a 30-year-old who may have got a job in the horse and cart industry 100ish years ago can today earn a living as a ski instructor – a job that didn’t even exist back when we all moved around by horse and cart.
Just like the impact the automobile had on jobs, there are jobs AI can do better than people, but there are also jobs it can’t do and jobs that don’t even exist yet.
Navigating the Impact of AI on Your Career
The summary is that AI is significantly impacting technology jobs, both positively and negatively. While many (if not all) routine tasks are being automated by AI technologies, leading to potential job displacement, AI also creates new opportunities. It enhances productivity in many roles too.
The net effect is a transformation of IT, digital, and technology work, with a greater emphasis on specialised AI skills as well as skills in areas where AI is not effective.
