Crossover-month projection

AI productivity gain meets compounding debt cost.

Research shows AI-generated code adds 30-41% to technical debt within 90 days. The headline gain holds; the debt compounds. This projection runs both forward to find the crossover month, when monthly debt cost overtakes monthly productivity gain, and tots up the cumulative net.

your team & adoption

Team size (devs)

Fully-loaded salary ($K)

AI adoption %

40%

% of code being AI-generated/AI-suggested. Stripe avg 2026: ~40-50%.

Productivity gain %

18%

Net velocity gain from AI usage. McKinsey range: 12-25%.

Annual debt growth %

35%

Research range 30-41% in first 90 days. Calibrated to 35% default.

Projection horizon (months)

24
CROSSOVER IN YEAR 2

Debt overtakes gain after year one.

Crossover at month 18 (1.5 years).

Monthly productivity gain

$15,300

from AI adoption

Debt cost @ month 24

$23,071

compounded

Net over 24mo

+$121,593

net positive

monthly gain vs accumulated debt

month 0crossover month 18month 24
productivity gaindebt cost (compounded)

Productivity gain = base_team_cost × ai_adoption × gain_pct (held constant). Debt cost = base_team_cost × ai_adoption × ((1+monthly_growth)^month − 1) × 0.33 (research-backed coefficient for AI debt translating to maintenance hours). Compounded monthly using the annual growth rate. Crossover marked where monthly gain falls below monthly debt cost.

How the projection works

The base monthly team cost is fixed: team_size × (fully_loaded_salary / 12). Productivity gain is also fixed monthly: base × ai_adoption × gain_pct (the per-month dollar gain from AI usage at the adoption level).

Debt cost compounds. Each month, the accumulated debt fraction grows at the monthly equivalent of the annual debt-growth rate: monthly_growth = (1 + annual_growth)^(1/12) − 1. Monthly debt cost = base × ai_adoption × ((1 + monthly_growth)^month − 1) × 0.33, where 0.33 reflects the published research coefficient translating accumulated debt into maintenance hours.

Crossover month = first month where monthly debt cost > monthly productivity gain. From that point, AI adoption is net-negative on a monthly basis. Cumulative net = sum of (gain − debt) across the horizon.

Default values: 35% annual debt growth (midpoint of published 30-41% range), 18% productivity gain (midpoint of McKinsey 12-25% range), 40% AI adoption (typical 2026 team), 24-month horizon. Treat the projection as scenario-modelling, not a binding forecast, your codebase's coupling and refactor discipline materially affect the debt-growth coefficient.

Updated 2026-04-27