The capital infrastructure industry is ripe for disruption. According to a recent survey conducted by KPMG, more than two-thirds (69 percent) of capital construction projects are delivered late and over budget. At a time when countries such as the United States are investing heavily in new infrastructure projects as part of broad-sweeping government initiatives, costly delays and over-stretched budgets are becoming a real cause for concern. The days of overpromising and underdelivering are coming to a close, particularly for those looking to win new contracts for developing roads, bridges, transport networks and other vital infrastructure projects that are currently undergoing a boom.
There are countless reasons why a capital construction project may run into difficulties, but more often than not it’s down to lack of foresight or poor application of time and resources. Even environmental factors out of a project owner’s control (e.g., adverse weather, supply chain upset, natural disasters, etc.) can still be factored in and accounted for as part of an overall risk assessment, with any potential fallout tracked, monitored and effectively communicated with stakeholders.
This communication is key. According to the same survey by KPMG, approximately 91 percent of public-sector stakeholders now expect project delays and failures. For the most part, this frustration isn’t down to a project suffering an unavoidable delay, but a failure to communicate that delay and redefine the project parameters in a way that’s well received and understood.
None of this is down to negligence or an unwillingness to deliver capital projects effectively. Rather, it’s due to the sheer amount of data that needs to be crunched to generate the insights needed. If a project can leverage all data points and make better decisions based on accurate forecasts, it can generate the insights needed to keep expectations in check and course-correct when circumstances demand it. Many of the failures associated with capital construction project delivery are due to these course corrections coming far too late, leading to runaway budgets and missed deadlines.
According to KPMG’s 2023 Global Construction Survey, 87 percent of project owners say their projects are now coming under greater scrutiny, but only 40 percent are using tools such as robotic process automation (RPA) or artificial intelligence (AI). In the same survey, capital construction project handlers ranked improving the accuracy of estimates and mitigating risk among their largest priorities. Ultimately, the gap between stakeholder expectations and project delivery needs to close, and AI and cloud technology are the means to achieve it.
Capital construction is uniquely poised for major digital disruption. It’s a world still largely dominated by papers and spreadsheets, which means gathering data and sharing information with stakeholders is a far cry from the frictionless experience enjoyed by companies in other industries. If capital construction companies want to participate in initiatives such as the Infrastructure Investment and Jobs Act (IIJA) in the United States, which is allocating billions to revamp the country’s critical infrastructure, they will need to be able to demonstrate digital capabilities such as accurate reporting, analytics and forecasting to government agencies and townships so projects can be managed and delivered in a way that’s proactive, transparent and measurable.
By leveraging AI and cloud technology, directors of state agencies, city and town managers, and other Capital Improvement Project owners can unlock new opportunities for improved efficiency, cost savings and strategic decision-making. Here are just some of the use cases that AI and cloud technology could unlock for capital project management.
Predictive Maintenance and Drone Inspections
With the amount of investment involved in the development of new public infrastructure, maintenance has become a critical concern. Part of ensuring longevity and financial return on public infrastructure investment is making sure it’s built to last and maintained long into the future. For instance, as reported by The White House, more than 45,000 U.S. bridges as well as 1 in 5 miles of roads are in poor condition. The American Society of Civil Engineers also has given the United States a “C-” in rating the quality of its current infrastructure.
To circumvent these issues, maintenance needs to be proactive rather than reactive. By harnessing the power of AI and machine learning (ML), organizations can implement predictive maintenance strategies to proactively identify and address maintenance needs before they become critical issues. One emerging example is the use of drones in infrastructure inspection.
By combining high-resolution imagery, thermal imaging and AI algorithms, drones can detect structural weaknesses, identify potential maintenance requirements and collect valuable data for further analysis. This technology enables CIOs and CTOs to optimize maintenance schedules, reduce downtime and ensure the longevity of public infrastructures.
Time-Series Forecasting for Better Budget Management
Accurate forecasting is vital when making informed investment decisions in project capital management. Traditional forecasting methods often fall short of capturing complex patterns and trends within large datasets, and those using “pen and paper” or spreadsheet-based systems are out in the wilderness. However, AI offers advanced time-series forecasting techniques that provide real actionable insights.
For instance, AI models such as ARIMA (AutoRegressive Integrated Moving Average), SARIMA (Seasonal ARIMA) and LSTM (Long Short-Term Memory) can analyze historical data, identify underlying patterns, and generate accurate forecasts for future demand and traffic patterns. By leveraging these models, public project owners can make data-driven decisions regarding capital project investments, allowing for optimized allocation of resources, improved cost estimations and better alignment with market requirements.
Machine Learning to Rank Investment Priorities
ML algorithms have proven to be invaluable tools for analyzing vast amounts of historical data and identifying patterns and trends that might otherwise go unnoticed. When it comes to capital program delivery, ML can play a crucial role in determining investment priorities. By leveraging regression, decision trees and neural networks, ML algorithms can analyze historical data related to project performance, market trends and other relevant factors. This analysis helps project owners identify patterns, understand the impact of various variables on project success, and therefore inform investment priorities. ML-driven insights allow for more effective resource allocation, risk mitigation and increased profitability.
AI Simulation to Evaluate Investment Scenarios
When choosing to invest in a particular project, it’s vital to consider any potential roadblocks or eventualities that may lead to delays or a required increase in budget. AI-based simulation techniques provide a powerful tool to model and analyze investment scenarios, helping stakeholders make informed choices. Investment in a particular project should not be granted based on a single fixed sum, but rather a series of scenarios that take into account how that investment may be affected.
By utilizing AI simulation, project owners can simulate different investment scenarios, considering variables such as project timelines, costs, resource allocation and market conditions. This enables the identification of optimal strategies and the assessment of potential risks and benefits associated with each scenario. AI simulation empowers decision-makers to navigate complex investment landscapes, minimize uncertainties and drive project success.
The digital disruption of the capital infrastructure industry is inevitable. As the industry embraces AI and cloud technology, it will not only overcome challenges but also pave the way for a more-efficient and sustainable future. With the power of AI and cloud technology, project capital management will experience a paradigm shift, driving growth and enabling the delivery of successful projects in a way that’s timely, transparent and, above all, cost-effective.
The post How AI and Cloud Technology Are Driving Digital Disruption in Capital Infrastructure first appeared on Informed Infrastructure.