Capital projects are essential to global infrastructure and economic growth, but while demand is accelerating, rising investment is not guaranteed to produce better outcomes.
Across infrastructure, the scale of the challenge is becoming harder to ignore. Projects are becoming larger, more technical and more constrained, while owners and contractors face increasing pressure to deliver with greater certainty and to tighter budgets.
Many are turning to Al.
Al not only strengthens the data-driven nature of decision-making in capital projects, solving complex, nonlinear problems in engineering, procurement, construction and commissioning, but when combined with deep industry expertise and new ways of working, these technologies can create a significant opportunity to reduce costs and schedule overruns.
This matters because many major projects are still built around a single baseline schedule. That schedule may be built by experienced professionals and supported by years of project knowledge, but it is only one version of how the project could be delivered. On a complex capital project, there may be thousands, or even millions, of possible paths through the work. Choosing the right one directly impacts labour utilisation, equipment use, risk exposure, and revenue
generation.
Generative scheduling changes this. Instead of accepting one plan as the answer, project teams can quickly create, test and optimise multiple schedules. They can understand the cost and time implications of decisions before they are made. They can explore what happens if labour is increased, if procurement is delayed, if activities are resequenced or if a key milestone needs protecting. Most importantly, they can make decisions based on evidence rather than instinct alone.
Take McKinsey, who have collaborated with ALICE Technologies, to help clients quickly create, test, and optimise construction schedules. Together, they bring a fundamentally new approach to capital project planning on complex programs, helping owners and contractors improve how projects are planned and delivered.
The evidence in favour of Al is compelling.
On one project, a generative scheduling model for a major port-expansion project delivered over 15% schedule acceleration, which led to a f15m reduction in labour costs through improved utilisation and £6Om in accelerated revenue through earlier completion.
For a major electronics-manufacturing company, which was over three months behind schedule on its large-scale cell-manufacturing facility, it needed to explore ways to get its project back on track. An optimised schedule for the installation of over 1,000 pieces of equipment delivered six weeks of schedule acceleration and over £37m in impact through cost savings and revenue acceleration.
Finally, for a leading engineering, procurement, and construction player, building an elevated guideway for a public transit operator was over a year behind schedule and confronted with £6Om in identified risks. Using an advanced analytics engine, we were able to explore over 100 "what-if" scenarios and recovered the 13-month delay.
These are not theoretical improvements. They are practical examples of what happens when project teams interrogate the schedule differently. Al allows project schedulers to move from asking "are we on track?" to asking "what is the best route forward from where we are now?"
"We're building on more than five years of work across industries to improve how large capital projects are planned and executed," says Mark Pitcher, a partner in McKinsey's Capital Excellence Practice. "Building more robust, analytics-driven schedules is a critical opportunity for the industry, and one that can drive significant improvements in cost and schedule performance."
Together, McKinsey and ALICE have successfully introduced generative scheduling to more than 35 clients across capital-intensive industries, including infrastructure, data centres, energy, mining, and manufacturing, achieving schedule accelerations of up to 20% and significant cost savings.
"Generative scheduling creates a step change in capital project performance," says Erikhans Kok, senior partner and leader of McKinsey's Capital Excellence Practice. "When embedded within the right operating model and supported by strong project controls, it can help organisations make faster, more informed decisions."
This is where the industry's next major productivity gain will come from. Not from replacing human expertise, but from giving project teams the tools to apply that expertise at greater speed and scale. Experienced planners, schedulers and project leaders still make the decisions. Al just provides them with more options to compare, better information to assess and faster feedback on the impact of each choice.
ALICE enables scalable insight by ingesting BIM models and Po schedules to simulate millions of execution paths and identify the most efficient and resilient options. Deep scheduling and construction expertise allow contractors and owners alike to accurately model real-world project conditions to improve on-time delivery.
"Rethinking capital project planning and delivery is essential to address the stagnant performance in cost and schedule outcomes," says Martin Linder, senior partner and leader of McKinsey's Capital Excellence Practice.
"By leveraging advanced technology, data-driven decision-making, and collaborative planning, stakeholders can optimise project delivery, maximise value, and adapt to the increasing complexity of modern capital projects."
As capital projects grow more complex and the value of capital at stake continues to rise, the organisations that combine Al- and analytics-enabled tools with disciplined ways of working will be best positioned to deliver large-scale projects with greater certainty, on time and on Budget.
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