The Proof Seeker

They want evidence, not enthusiasm. Accuracy, reliability, and control matter more than hype. They’ve seen tech overpromise before, and they’re not falling for it again. Their scrutiny protects teams from blind adoption. But without trust or proof, they’ll stay on the sidelines.

How to spot them

Signature behaviours:

Always asks for a demo – Won’t touch it until they’ve seen it work.
Over-analyses accuracy – Breaks down results, errors, and edge cases.
Slow to adopt – Waits for proof before even small trials.
Voices AI’s limits – Brings up flaws and risks in every discussion.
Cautious with input – Selective with data shared due to privacy concerns.

What this means for you:

• They protect the team from poor-quality tools and decisions.

• They flag issues others ignore, from security to accuracy.

• But they can stall progress and lower team confidence if their scepticism spreads.

• With the right approach, they become your most thoughtful advocate for trusted AI.

The challenges they create

⚠️ High bar for adoption – Needs full proof before trying anything new.
⚠️ Slow to trust – Hard to convince without detailed transparency.
⚠️ Privacy-first mindset – May avoid using AI entirely if data feels unsafe.
⚠️ Fixates on flaws – One error can turn into a full rejection.

What to do

Don’t sell, show

• Share verified case studies tied to real outcomes.

• Use live demos to walk through results and edge cases.

• Invite them to test AI in safe, controlled environments with real data.

Break down how AI works

• Explain step-by-step how decisions are made.

• Make limitations clear, don’t hide them.

• Share how errors are caught, corrected, and improved over time.

Let them test before they trust

• Pilot AI in low-risk tasks they can evaluate.

• Offer review checkpoints so they stay in control.

• Encourage side-by-side comparisons of AI vs human output.

Methods that use the profiles

More profiles to explore

Get all 42 patterns, 14 profiles and more in the HAP Behaviour Kit

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