Table 1.

Construct comparison: synthetic readiness, promotion fragility and pipeline thinning

DimensionSynthetic readinessPromotion fragilityPipeline thinning
Level of analysisIndividual (present state)Organisational (mid-term)Systemic (long-term)
Defining characteristicCompetent performance contingent on AI scaffolding; unable to explain process or detect AI errorsMismatch between demonstrated and required capability at point of promotionProgressive depletion of experienced senior practitioners across successive cohorts
Observable indicatorPerformance drops when AI tool is unavailable or produces incorrect outputIncreased failure rate or re-assignment in first 12 months of senior roleDeclining depth of internal expertise available to fill senior vacancies
Temporal scaleImmediate – detectable during AI-augmented roleShort-to-medium – detectable within 1–3 years of promotionLong-term – detectable across 5–10 year cohort progression
Adjacent constructAutomation bias (Parasuraman and Manzey, 2010)Peter Principle (Peter and Hull, 1969) – extended to AI contextKnowledge drain; succession gap
Source(s): Authors’ own

or Create an Account

Close subscription notice
Close access options