McKinsey and ALICE Cut Construction Timelines by 40% With Generative AI Scheduling

A partnership between McKinsey and ALICE Technologies is bringing generative AI scheduling to construction and infrastructure — and the early results are hard to argue with.

The platform analyzes project variables and generates multiple execution scenarios, giving contractors a way to stress-test schedules before a shovel hits the ground. It's already been deployed across 35+ clients.

The Numbers Are Real

Two early deployments stand out:

• Zachry Construction (San Antonio) used the platform to analyze highway construction schedules and cut 28 days from their timeline
• A McKinsey data center client reduced its construction schedule by 40% on a single project

These aren't marginal improvements — they're the kind of gains that reshape how capital-intensive projects are planned and funded.

What This Signals

ALICE CEO René Morkos framed it directly: "Generative scheduling is reshaping how complex capital projects are planned and delivered." The McKinsey partnership extends that capability into broader enterprise transformation work — connecting AI-driven scheduling to the operational and financial planning layers above it.

Key Takeaways

• Generative AI is entering capital project management — not as a chatbot, but as a planning engine that simulates outcomes at scale
• Schedule compression = cost compression: Cutting 28 days or 40% from a project timeline has direct financial consequences for owners, contractors, and lenders
• The pattern is repeating: Domain-specific AI layered onto proprietary project data outperforms generic tools — the same model we're seeing in finance, insurance, and professional services

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