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eBook
The State of AI in Capital Project Decision-Making
AI is already part of how capital project decisions get made, and 96% of organizations plan to spend more on it. What most haven't done is build the connected data foundation AI depends on, or a clear way to make decisions with it.
This report breaks down where AI is used today in portfolio decision-making, what leaders want from it next, and where they draw the line.
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In the report: Forewords from two capital project leaders
Two AACE International leaders on why connected data and clear accountability matter as AI moves into capital project decisions.
CEO and Founder, Kaleido; President
Adoption alone won't close the gap
“We risk deploying technology at the presentation layer while leaving integration problems unresolved.”
PE, PSP, PMP, MCIArb, President
AI should accelerate analysis, not replace human insight
“AI's greatest contribution is enabling better-informed human judgment sooner.”
61%
of organizations are actively using AI in multiple areas or piloting it
81%
cite fragmented, inconsistently formatted data as their top challenge
42%
take more than a week to move from identifying a risk to making an informed decision about it
85%
say it's very or critically important that AI can explain how it reached a recommendation
96%
expect to increase their AI investment over the next two years
What the data shows
AI adoption scales with size and stakes
Active AI use clusters among the largest organizations and portfolios, those with more than 5,000 employees and portfolios exceeding $5B in value.
Fragmented data is holding decisions back
81% cite inconsistently formatted data as their top challenge, with 62% describing their overall approach to capital project decisions as "structured, but delayed".
Trust is conditional, not automatic
Respondents want AI to flag the risk, not sign off on the decision. Just 10% would act on AI recommendations without significant review, 85% say AI must explain how it reached a recommendation, and 83% say regulation shapes their AI strategy.
Inside the report
What capital project decision makers are saying about AI
“[AI] should support—not replace—human judgment, with clear explanations for recommendations and attention to customer impact and equity.”-
“If AI could do one thing to help my team make better decisions, it would be to analyze project and portfolio data in real time and provide predictive insights on risks, costs, schedules, and resource constraints.”
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“Our agency has so much data that it continues to be virtually impossible to input data from different systems and complete a full analysis. Data gaps are a significant problem for us and prohibits proactive approaches to identified risks.”
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“AI will enable us to quickly and broadly gather scope and requirements in a pace that's significantly faster than what we are capable of currently. It will also enable us to condense data and extract key metrics that previously would have taken analysts a significant workload burden and man-hours.”
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“AI could make capital-project decisions more proactive by combining project status, costs, contractor capacity, customer needs, asset condition, and prior outcomes to identify risks and prioritize investments earlier.”
One connected view, and AI that's grounded in it
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