“You won’t lose your job to AI, but to someone who knows how to use AI” is bullshit

Will AI Replace Humans or Just Their Skills? Debunking the Myth

It’s a common belief that workers won’t lose their jobs to artificial intelligence but rather to those who know how to leverage AI effectively. However, this notion oversimplifies the evolving relationship between humans and AI, and it’s worth examining more critically.

AI represents a fundamental shift—not just an incremental technological advancement, but a transformation that impacts the very nature of intelligence itself. Unlike previous innovations that automated tasks, AI has the potential to supplant intellectual effort—the core of decision-making, reasoning, and problem-solving.

A key question persists: why do some assume that mastery in fields like Prompt Engineering will remain a safeguard against AI progress? Historically, technological capabilities tend to accelerate rapidly, and AI is no exception. It’s reasonable to ask whether AI will soon surpass human abilities in understanding and executing complex tasks.

In the near future, humans may need to define goals and formulate precise prompts to guide AI tools. But how long before AI systems can autonomously understand context, ask insightful questions, and retrieve relevant information, all surpassing human performance? The trajectory suggests that these advancements are on the horizon.

If such progress is imminent, then resistance hinges on an artificial plateau—the idea that the current capabilities of AI have reached a ceiling—yet this seems increasingly unlikely. The S-curve of AI development indicates a continuous, exponential progression, making it plausible that future AI will operate with minimal human oversight, effectively redefining who holds the “knowledge advantage.”

In essence, the debate isn’t about humans versus AI, but about how quickly AI systems will evolve to perform tasks that currently require human intelligence. Preparing for this shift means understanding that the real challenge lies in adapting to AI’s advancing capabilities—not just learning to use it better.