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executive summary
The core finding: the dip is structural, not incidental
Organizations are aborting AI initiatives precisely when they should be redesigning workflows, measurement, and manager enablement.
What the data shows
The bottleneck is readiness, not the model
62%
of executives expect AI ROI within 3 months — against a 6–12 month reality
31%
of managers trust AI-generated assessments enough to act on them
6/7
deployments experienced a dip, with the depth driven by organizational readiness, not AI quality
38%
of organizations rank manager coaching as their #1 budget priority for 2026, ahead of AI tooling
The winning pattern
Redesign before scale and prove outcomes before expansion
Enterprises that cross the curve solve workflow pain first, redesign before automation, and measure productivity, trust, and performance, not activity
Four questions the research answers
01
Why do healthy AI initiatives often get cancelled too early?
02
Where HR teams lose productivity first?
03
What separates successful enterprise adopters from stalled pilots?
04
Why manager trust matters more than the quality of AI tools?
Download the research
Get the full 25 pages research report for free
The complete findings: the 7-stage J-curve, the 5-level maturity model, where each HR function loses productivity first, and a staged 180-day playbook.
Prepared by Evolve in partnership with Innotechnics
