2026 STATE OF THE INDUSTRY REPORT
The Governance Imperative: Cost, Schedule, and Risk Under Global Uncertainty
Organizations now have access to more data, tools, and visibility than ever, yet they struggle to translate the combination into reliable plans easily and accurately. This report documents the governance crisis driving the paradox.
- The full research report and analysis
- 220 professionals, 12 countries, nine sectors
- Insights for leaders and practitioners
- Free — one sign-up, full access
One sign-up, free access to the report and all 15 segment briefs.
Deep Dive Briefs
One full report and analysis.
15 segment briefs.
The full report offers insights and analysis into global cost, schedule, and risk trends, from AI to parametric modeling. 15 segment briefs provide deep dives into a single industry, region, and functions.
Access All Segment BriefsKey Insight: AI Adoption & Governance
78% of organizations surveyed restrict AI usage. 71% know that Shadow AI is deployed without their knowledge. Only 24% have documented AI policies.
15 Segment Briefs
- IT & Software Development
- Manufacturing
- Transportation & Logistics
- Healthcare & Pharmaceuticals
- Energy & Utilities
- Automotive Manufacturing
- Aerospace & Defense
- AI Adoption & Governance
- European Union
- United Kingdom
- North America
- Australasia
- Engineering & Tech Leaders
- Finance & Procurement Leaders
- Program & Ops Leaders
Executive Summary
The gap between knowing and doing is the defining condition of 2026.
Drawing on a February 2026 survey of 220 professionals across 12 countries and nine major sectors — 135 organizational leaders and 85 operational practitioners — this report documents a governance crisis at the center of modern planning.
External volatility — trade policy, regulatory requirements, energy markets — has compressed planning horizons and made re-estimation cycles more frequent. Organizations have not yet restructured their estimation and governance systems to match. They are simultaneously deploying AI into planning workflows without the policies, ownership, or integration to govern it.
Seven headline findings emerged from the data:
- Trade policy is the largest external planning variable — 47.3% of respondents cite it as the primary disruptor; practitioners feel the impact 9.2 points more than leaders.
- A confidence inversion separates leaders from practitioners — 20% of practitioners are “very confident” in their estimation processes, vs. only 11.9% of leaders.
- The AI governance framework is broken — 77.7% report data restrictions limiting AI; 70.9% report shadow AI is common; only 23.6% have documented AI policies.
- Cost and schedule volatility are now structural — 91.4% of plans require revision during execution; 65% report increasingly variable costs.
- Estimation remains under-automated — 40% of organizations operate at 0–25% automation; only 22.3% report fully integrated systems.
- AI investment correlates with outcomes — only when pursued aggressively — 51% of aggressive adopters see significant planning improvement vs. 11.1% of cautious adopters.
- A 48-point scale gap exists in estimation maturity — 60.5% of sub-$100M organizations sit at lowest automation, vs. 12.5% of $50B+ organizations.
Organizations have visibility into volatility, access to more data than ever, and growing exposure to AI tools. What they lack is a governance layer that connects visibility to decision-making, data quality to estimation, and AI capability to auditable outcomes.
Table of Contents
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The gap between knowing and doing is the defining condition of 2026.
Drawing on a February 2026 survey of 220 professionals across 12 countries and nine major sectors — 135 organizational leaders and 85 operational practitioners — this report documents a governance crisis at the center of modern planning.
External volatility — trade policy, regulatory requirements, energy markets — has compressed planning horizons and made re-estimation cycles more frequent. Organizations have not yet restructured their estimation and governance systems to match. They are simultaneously deploying AI into planning workflows without the policies, ownership, or integration to govern it.
Seven headline findings emerged from the data:
- Trade policy is the largest external planning variable — 47.3% of respondents cite it as the primary disruptor; practitioners feel the impact 9.2 points more than leaders.
- A confidence inversion separates leaders from practitioners — 20% of practitioners are “very confident” in their estimation processes, vs. only 11.9% of leaders.
- The AI governance framework is broken — 77.7% report data restrictions limiting AI; 70.9% report shadow AI is common; only 23.6% have documented AI policies.
- Cost and schedule volatility are now structural — 91.4% of plans require revision during execution; 65% report increasingly variable costs.
- Estimation remains under-automated — 40% of organizations operate at 0–25% automation; only 22.3% report fully integrated systems.
- AI investment correlates with outcomes — only when pursued aggressively — 51% of aggressive adopters see significant planning improvement vs. 11.1% of cautious adopters.
- A 48-point scale gap exists in estimation maturity — 60.5% of sub-$100M organizations sit at lowest automation, vs. 12.5% of $50B+ organizations.
Organizations have visibility into volatility, access to more data than ever, and growing exposure to AI tools. What they lack is a governance layer that connects visibility to decision-making, data quality to estimation, and AI capability to auditable outcomes.
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