I once watched a hiring manager reject a strong resume because an algorithm ranked it low. She paused, shut the tool, and asked a human question instead.
The candidate got the interview.
That pause is the skill I want you to build: knowing when to trust people over predictions.
Here are 5 real cases where AI can do more harm than help — and what to do instead:
1. Sensitive personal data
☑ AI can mishandle health, religion, or sexual orientation info — triggering GDPR Article 9 violations.
→ Instead: anonymize data, use vetted models, get explicit consent, or keep workflows human.
️2. Mental health or grief support
☑ AI mimics empathy but misses crisis cues.
→ Instead: limit to low-stakes tasks like journaling prompts. Escalate to real clinicians when needed.
3. High-stakes legal, medical, or safety calls
☑ AI lacks domain judgment and accountability.
→ Instead: ensure expert oversight, rigorous audits, and clear documentation.
4. Moral or bias-sensitive decisions
☑ AI reflects past patterns — not lived realities.
→ Instead: co-design with affected communities and audit for bias.
5. Quick gut-check: ask these before using AI
☑ Would harm be irreversible?
☑ Does this involve legal/ethical risk?
☑ Can the AI explain itself in plain terms?
If no to any → pause. Human-in-the-loop wins.
When AI is fast, persuasive, and flawed… pause becomes a leadership skill.
Have you ever chosen not to use AI?
Drop your example or vote in the follow-up poll — it might save someone from a costly mistake.
I simplify talent acquisition for clients and job seekers—helping businesses find top talent quickly while connecting candidates with roles that align with their skills, goals, and aspirations.
5dIncendia Partners