Tagged with: #human-impact

Every AI business case counts the hours saved. Almost none counts the hours added: the reviewing, correcting, and supervising that AI outputs demand before anyone can rely on them. That oversight labour is real, regulation increasingly mandates it, and people absorb it silently on top of existing roles. BCG research published in March 2026 shows the consequence: a distinct mental fatigue attaching to heavy AI oversight loads, while workers using AI only to replace routine work report less burnout, not more. I argue this fatigue is a control cost Boards must price, and the remedy is governance, not resilience training.

As I discussed in my article on building and managing AI-capable teams, organisations face a critical challenge in acquiring the right talent for AI transformation. This reminds me of the early days of cloud adoption, when I advised enterprises on their migration strategies. Back then, I witnessed the same scramble for scarce talent, which led me to advocate strongly for upskilling existing teams rather than relying solely on external hiring.

As artificial intelligence (AI) advances into the workplace rapidly, one of the most pressing questions on everyone’s mind is, “If machines can do our jobs faster, more accurately, and at a lower cost, what happens to us?” It’s true that AI is beginning to redefine the very essence of work, raising concerns about the potential displacement of knowledge workers. However, I’d like to propose an alternative perspective—one where those same workers earn the same or more whilst working far fewer hours.