In the age of technological marvels, the modern workplace is in a dichotomy. On one hand, it is favorable that time-consuming tasks are now automated. But on the other hand, it raises a concern: what will workers do, and what does the future of work look like? 

With the advent of OpenAI’s ChatGPT and similar Large Language Models (LLM), these fears have been further amplified. But this happens almost every time a new technological phenomenon arises. In the early to late 90s, when computers were still new to the workplace, the Y2K phenomenon was widespread. People were worried that these machines would start acting on their own accord once the calendar year changed from 1999 to 2000.

While these concerns might seem more justified in the case of Artificial Intelligence (AI), people are often overlooking the larger perspective. What are the jobs that AI is taking over? Usually, it is mundane, repetitive tasks that add little to no value in skill development. Are these jobs something that humans want to spend their time doing? Are humans extracting any value from these jobs? More often than not, the answer is no. In the case of LLMs themselves, the responses they generate can work as a template in a lot of use cases, but they cannot recreate complex human thoughts and often fall short of authenticity.

The World Economic Forum echoes this sentiment. According to their findings, more than 75% of companies globally plan to adopt AI in one form or another. But this incorporation is not synonymous with downsizing but rather signifies a collaborative evolution. Let’s explore how and why this collaboration can usher welcoming changes to the workplace and how humans can future-proof their jobs.

Amplifying human potential

In the coming five years, the impact of technologies such as AI is expected to be a net positive. WEF’s ‘Future of Jobs’ report found that big data analytics, environmental management technologies, encryption, and cybersecurity are expected to be the biggest drivers of job growth in the coming years. While the report sees AI as a potential disruptor, it acknowledges that the jobs it takes over are only set to create job demand value elsewhere.

The goal of AI is not to replace but to elevate. For instance, in the manufacturing industry, AI could take over the repetitive daily tasks of sorting through inventory, figuring out what needs to be stocked, and conducting quality checks. This way, humans can invest their time in learning skills that can expand their abilities, work with technologies that once seemed foreign, and take on larger responsibilities. 

The human element

AI's capabilities in data processing and predictive analytics are undeniably impressive, yet it falls short in embodying human experience–empathy, contextual comprehension, and emotional intelligence. 

This raises the question: what can AI achieve without human involvement? For example, several automotive companies are adopting LLMs into their vehicles and systems. They use it to conduct routine checks and assist with on-road safety and predictive maintenance. But in this case, AI cannot fix any of the problems that it detects. To ensure that the challenges detected by AI are addressed, businesses will always need skilled human workers. 

Even when it comes to customer experience, AI is great at providing routine answers to customer queries. But for more complex scenarios where the customers are disappointed or want to express emotions, AI may prove limited or insufficient. Handling such demand nuanced decision-making and authentic interpersonal connection is something that AI simply cannot recreate. According to WEF, cognitive skills are growing in importance, reflecting the need for complex problem-solving skills in the workplace.

All forms of technology, including AI, can only work as long as humans operate and monitor it. This won’t necessarily change even as AI evolves. The only thing that might change is how much human intervention is required.

Rise of hybrid careers

If AI can take over jobs, there are always newer and more nuanced jobs that will crop up. For instance, as businesses across the globe focus more on sustainability in the coming years, there will be a higher demand for people skilled in domains such as ecotechnology. 

Technology literacy is the third-fastest growing core skill globally. Over 86% of businesses aim to adopt digital platforms and apps in the next five years and are, in turn, looking for people who can run, operate, and update these apps based on their requirements. There is a demand already for jobs surrounding AI, such as AI ethics, AI-driven supply chain management, process automation analysis, and AI-human interaction designing, to name a few.

The assumption that AI will take over all jobs undermines the ability of humans to constantly innovate and, in turn, create new arenas of professional growth. The fact that the job landscape today looks vastly different, even compared to a decade ago, is in itself a sign that things aren’t as bleak as they may seem.

Navigating the AI-enriched horizon

If things with AI aren’t that bad, why is the popular narrative suggesting otherwise? The simple answer is, timing. The economic conditions coupled with the aftermath of the pandemic has left people bracing themselves for the next big disruption. Add the popularity of LLMs into the mix, and you have what seems like the next catastrophe. But that’s far from the truth. At its best, something like generative AI is a new and highly skilled colleague that challenges people to upskill and expand their professional skill sets. 

But businesses have a responsibility here. Now, more than ever, they must focus on encouraging learning and development and providing facilities for their employees to upskill. By viewing AI as a catalyst for excellence, businesses can get the most out of their investments both in technology and human resources. Even as AI becomes more advanced, it will likely continue shaping sectoral shifts in employment. Organisations will need to guide and ensure that their employees feel and remain valuable amidst the transition.