AI Workplaces: Why Is it Impossible for Now?

AI technology has come a long way since its initial surge in 2021 as more companies and industries leverage on it to automate workplaces.

Yet despite AI firms' promises of more powerful and more advanced generative AI soon, the goal of an AI-led workplace remains an impossible dream for now.

Here are some reasons why:

Gen AI Integration Remains a Costly Venture

While using generative AI seems ideal on paper to solve workplace inefficiency and reduce redundant roles, many companies have soon found out about the technology's current flaws and weaknesses.

Unlike actual human workers, AIs are more apt to "hallucinate" facts and information, affecting their capabilities to produce accurate and exact results.

Training the technology to be more precise and effective would require companies to shelve millions, if not billions of dollars, for AI to become applicable to various tasks.

This is not to mention the necessary hardware and resources needed to power all computers processing the AI's task,

All of these combined would cost companies and the entire industry more investments, much more than just employing human workers more reliably to produce similar results.

A Massachusetts Institute of Technology study even highlighted the mounting expenses the industry will have to

AI Still Needs Human Assistance

Due to the technology's current limitations, most AI models still require constant monitoring from human supervisors to ensure the technology is working efficiently.

According to The Wall Street Journal, AI firms are having a hard time marketing their new AI products due to their current limitations and "hallucination" tendencies.

In some cases, the AI requires constant correction as most data stored in the machine are outdated and would require an update from its service provider to fix the issue.

That said, companies are still able to take advantage of these less-than-perfect AI machines as industries hire people already familiar with generative AI over those who would still require extensive training.