Thread 7: AI Productivity Proof Gap
Platform
Link
Key Excerpt
“Board-level expectations shifted to tangible AI output, but 75% struggle to measure impact.” The thread then points to teams being asked for visible success cases that are hard to prove in real delivery workflows.
Why This Matches Ryva ICP
EM-level reporting pain where teams cannot show reliable project state and outcomes without manual interpretation across fragmented workflow signals.
Underlying Problem
Decision-makers demand proof from metrics that do not map cleanly to actual delivery outcomes.
Suggested Public Reply (Copy)
The measurement gap is usually a workflow gap. If teams cannot connect decision, implementation, review, and production outcome in one chain, AI impact will always look fuzzy and political.Suggested DM Idea (Copy)
If you want, I can share a minimal "decision-to-outcome" template that helps teams show AI impact without relying on vanity activity metrics.