The ‘Second Shift’ of the Digital Age: Are Humans Now Working for AI After Hours?

AI promised to lighten our workload — so why are so many people working harder than ever?
As automation creeps deeper into offices, classrooms, and customer service centers, a strange paradox is emerging: instead of freeing us, AI is quietly assigning us a second shift — one filled with reviewing, correcting, and managing machine output.

It’s invisible. It’s unpaid. And it’s growing.

Automation’s Hidden Side Effect: Invisible Labor

When AI generates a presentation, writes an email, or creates a report, it rarely gets everything right. That’s where humans come in — editing tone, fact-checking claims, translating context, and ensuring quality.

This subtle human oversight — often outside formal work hours — is known as "invisible AI labor."

In 2024, researchers from the University of Amsterdam coined it the "Second Shift of AI", comparing it to the unpaid domestic labor disproportionately performed by women.¹ It’s mental work, often cognitively taxing, but rarely recognized as “real work.”

The Rise of the AI Babysitter

Instead of replacing jobs, AI is creating new ones — like AI output reviewers, prompt engineers, or “model whisperers” who tweak queries to get usable results.

And for many knowledge workers, these new roles aren’t formal titles — they’re tacked on to existing responsibilities. That means extra hours spent:

• Fixing hallucinated facts in auto-generated reports
• Rewriting emails with the right cultural tone
• Manually QA-ing AI-generated code or translations

A 2023 survey by MIT Sloan found that 72% of professionals using AI spent more time editing than creating.² The irony? The more AI helps, the more humans are pulled in to supervise.

Who Gets Credit — and Who Gets Burned Out?

The second shift often happens off the clock — and under the radar. As companies celebrate efficiency gains from AI, they rarely acknowledge the emotional and intellectual labor of their workers behind the scenes.

Burnout is becoming a hidden cost of AI adoption, especially in industries like marketing, journalism, customer support, and education — where speed and output are prioritized over nuance and context.

And the credit? It often goes to the tool — not the person making it usable.

Conclusion: We Work for AI Now — Unless We Redesign the System

We were told AI would work for us. But in many industries, humans are now working for AI — cleaning up its mess, correcting its tone, and managing its learning curve.

To make AI truly empowering, we need to acknowledge, value, and redesign around human oversight. Because the second shift isn’t just a tech problem — it’s a labor one.