Clare Kitching on linkedin

tgroenwals shared this post · Apr 21

The most dangerous phase of an AI program is right after the win.

The demo worked.
Stakeholders are excited.
Everyone wants to move on to the next shiny thing.

That’s when problems start if the long term hasn’t been factored in.

AI solutions succeed when they're safe & reliable.
That means:
→ Clear decisions on what it should and should not do
→ Humans who stay accountable
→ Time (& budget) set aside for fixes, tuning, and judgement calls
→ Acceptance that edge cases happen

AI requires an ongoing operating model, not a one off investment.

Fireworks get attention.
Lighthouses keep businesses off the rocks.
If no one owns the lighthouse, the light eventually goes out.

What part of AI delivery do you think leaders underestimate the most?

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Des Raj C. Honestly the dangerous moment is when a pilot proves just enough value to get scaled before anyone has defined failure. What gets monitored, who can pause it, when does a human step in, what’s the rollback path when the edge cases stop being edge cases. A lot of teams don’t fail because the model was weak, they fail because the operating discipline showed up too late. Apr 21 3 likes

Mike Reid The real risk starts when early wins make teams forget the need for long term ownership. Apr 21 5 likes