Opening Scene
A guide who tried a route, hit an impassable crevasse field, and returns to camp to explain exactly what was found and why the team is trying something else builds trust for the next attempt, even though the news itself is disappointing. One who simply vanishes from the plan without explanation leaves the team wondering what happened, and whether they can trust whatever route gets proposed next. An organization that quietly discontinues a failed AI pilot without ever explaining why is doing the second thing, and it costs more than the failed pilot itself ever did.
In Plain English
Honest failure communication means specifically explaining what didn’t work, why, and what’s happening next — not spin, and not silence. Specific honesty about failure is what preserves credibility for the next initiative; silence or spin spends that credibility without anyone quite noticing at the time.
The Old Way
Before honest postmortems became normal practice, failed initiatives tended to simply disappear:
- Failed initiatives were often quietly dropped from mention entirely, with no acknowledgment that they’d happened at all.
- When failure was addressed, it was frequently reframed in vague, face-saving language that obscured what actually went wrong.
- The next initiative launched into an environment of accumulated, unaddressed skepticism left over from the last unexplained failure.
Explaining exactly what was found at the crevasse field is what keeps that skepticism from building up in the first place.
What’s Changing (and Why AI Is the Reason)
- Organizations increasingly treat honest postmortems on failed AI initiatives as a credibility-building practice, not a liability to avoid.
- This connects to the practice modeled in this content library’s dedicated data ethics case studies series, since publicly examinable failures, told honestly, are exactly the kind of material that series treats as valuable rather than embarrassing.
- Because AI failures — a model that didn’t perform, a use case that didn’t pan out — are common and often not clearly anyone’s fault, honest communication about them is becoming easier to normalize than it would be for a more obviously attributable failure.
The Metaphor, Fully Extended
| The Expedition | Change Management Concept |
|---|---|
| A guide explaining exactly what was found at the crevasse field | Leadership explaining specifically what didn’t work in a failed pilot |
| The route quietly dropped with no explanation | An initiative quietly discontinued with no communication |
| The team’s trust in the next proposed route | Employee trust in whatever initiative comes next |
| A postmortem shared honestly back at basecamp | A postmortem shared honestly across the organization |
For Beginners: What to Actually Do
- If an AI initiative you were part of quietly disappears, ask directly what happened to it.
- Share your own honest account of what didn’t work, even when it’s uncomfortable to do so.
- Notice whether failure explanations sound specific or vague, and trust the specific ones more.
For Practitioners and Leaders: The Deeper Layer
- Run and share honest postmortems on failed AI initiatives rather than letting them quietly disappear.
- Be specific about what didn’t work and why, rather than reaching for vague, face-saving language.
- Treat credibility built through honest failure communication as an asset for whatever initiative comes next.
Quick Recap
- Honest, specific communication about failure builds more trust than silence or spin.
- Quietly dropping failed initiatives without explanation erodes trust in whatever comes next.
- Honest postmortems are increasingly treated as a credibility-building practice.
- AI failures, being common and rarely anyone’s individual fault, are relatively easy to discuss honestly.
Where This Fits in the Series
Article 14 covered tailoring routes to different departments’ needs. Article 15 covers what happens when one of those routes genuinely doesn’t work, and how to communicate that honestly. Article 16 turns to a related, more forward-looking question: what actually keeps people climbing in the first place, and how incentives shape sustained effort.
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