“Automate everything” is one of the most repeated phrases in the world of artificial intelligence. But while AI is fast, disciplined, and efficient, it still lacks common sense, empathy, and judgment. This article will help you clearly decide which tasks to delegate to the robot—and which ones still need a human head (and heart).

Quick practice: Pick one repetitive task in your company. Keep it in mind as your example while reading.

Two Sides of the AI Coin: Safe vs. Risky

Action tip: Place your selected task in the appropriate column. Surprised by where it landed? Adjust expectations before automating.

When AI Gets It Wrong

Some errors can’t be undone with a single click:

• Irreversible damage: Denying a credit to someone who qualifies, misinterpreting medical data.

• Black box problem: No one can explain why the algorithm failed.

• Bad press and fines: Negative headlines, user loss, regulatory sanctions.

• Hidden costs: Fixing a poorly launched system is far more expensive than pre-checking.

The 3‑2‑1 Rule Before Delegating to AI

Ask yourself:

1. Pain of failure: Will a mistake cause serious damage or just mild inconvenience?
2. Easy to undo: Can it be reversed easily like a “Ctrl + Z”?
3. Clear explanation: Can we track how the AI made its decision?

If all three answers are reassuring, AI can run unsupervised. If any create doubt, human oversight is a must.

Practice: Apply the 3-2-1 rule to your chosen task. Does it need human review?

Good AI Use: Everyday Examples

Supermarkets and bananas
A retail chain predicts how many bananas will sell tomorrow. If it gets it wrong, they offer discounts and avoid waste. Mistake = low cost, easy fix.

→ Use historical data to forecast inventory and track savings.

Photo-sorting app
An app tags “selfies,” “pets,” and “receipts.” If it mistakes a dog for a cat, the user corrects it. No harm done.

→ Try a prototype to classify internal images and test accuracy.

Poor AI Use (or Use with Caution)

Medical treatments without review
A hospital lets AI assign treatments with no human oversight. A mistake here can be fatal.

→ Health professionals should always have final say. AI suggests, not decides.

Automated layoffs
A company fires people based on a program tagging “low productivity” without considering context or health.

→ Use AI to detect warning signs—but always decide with human review.

How to Stay Safe

• Human pilot for critical decisions.

• Continuous monitoring: Complaints ↑ → review the model.

• Transparency: Tell users when AI is involved and how to appeal.

• Update your data: Old models = inaccurate results.

• Focus on value: Automate the tedious, preserve the human.

Three-Level Supervision Architecture

Level 1 – Assistant
AI suggests; human decides.
Example: Email draft generator.
→ Track time saved and acceptance rate.

Level 2 – Copilot
AI acts but alerts when confidence is low.
Example: Ticket routing with threshold.
→ Set a minimum threshold and trigger alerts.

Level 3 – Autopilot
AI operates solo; alerts only for anomalies.

Example: Auto-scaling cloud servers.

AI boosts speed for repetitive tasks. But when lives, rights, or reputations are at stake, human empathy remains irreplaceable. With the 3-2-1 rule, tiered supervision, and a clear dashboard, the robot serves humanity—not the other way around.

Natalia Mera

Software Project Management Specialist

@Natalia Mera