If AI Takes Over Employment, Shouldn’t the so-called “bullshit jobs” in corporations be the first to vanish?

Will AI Render Certain Jobs Obsolete First? Rethinking the Future of Work

As artificial intelligence continues to advance, a common question arises: if AI is poised to automate many jobs, shouldn’t the roles often labeled as “corporate ‘bullshit jobs'” be the first to go?

Many critique roles such as project managers, consultants, or similar positions that primarily involve creating presentations, responding to endless emails, and attending unproductive meetings. These positions are frequently dubbed unnecessary or redundant in today’s digital age. Given this perspective, one might assume that such administrative and corporate roles would diminish quickly with the rise of automation, while more tangible roles—such as housekeepers or factory workers—would endure longer.

However, this line of reasoning prompts a deeper inquiry: why do certain academic disciplines and qualifications—like humanities, languages, design, or even computer science—appear more vulnerable to automation? Conversely, why do fields such as economics, finance, or administrative management seem to offer a buffer against technological displacement?

The evolving landscape of work suggests that the future of employment isn’t solely determined by the nature of the tasks but also by economic, societal, and technological factors. Administrative and corporate functions might persist because they perform complex, nuanced decisions that AI has yet to master, or because businesses still value the human element in leadership and communication.

Meanwhile, disciplines often deemed “less practical” or more theoretical—like the humanities—are sometimes viewed as at higher risk due to their perceived lack of automation-friendly skills. Yet, history has shown that adaptability, interdisciplinary knowledge, and creative thinking are vital assets in navigating an AI-driven economy.

In conclusion, understanding which jobs are most susceptible to automation involves examining more than job descriptions. It requires a broader perspective on societal priorities, economic structures, and the evolving role of human intelligence in workplaces. The conversation about AI’s impact on employment is complex and ongoing—and it’s crucial to challenge assumptions to better prepare for the future.