Glass Canada • June 2025 • Beyond spreadsheets

Industrial AI can help rebuild construction and engineering, with the right digital building blocks.

In this environment of persistent economic uncertainty the construction industry is challenged to find ways to improve project performance by delivering projects in shorter timescales, on time and on budget, with minimal defects and re-work, while also meeting growing environmental, social and governance requirements. This is increasingly difficult, as companies face fierce competition and low project margins, sometimes as narrow as one to two percent. To keep projects profitable, businesses need to accurately estimate projects and manage costs (labour, equipment rental, materials, sub-contract package costs and overheads), cash flow and contract and project change, while monitoring actual and committed costs and tracking project progress.

AI trends in the construction and engineering industry include automated and autonomous equipment and robotics; smart design and BIM tools and virtual reality; asset performance management; and predictive maintenance using smart sensors and Internet of Things. Other case examples are drones to measure project progress and smart cameras and wearables to improve health and safety on the construction site. In addition, there are major AI improvement opportunities that will be realized in the core project and asset lifecycle processes. The term industrial AI is now being used to describe these AI use cases.

However, the majority of organizations are still at the beginning of their digital transformation journeys, and there is work to be done before organizations experience the real business benefits. Historically, the sector has lagged in digital adoption, relying on disjointed business systems and manual processes, such as spreadsheets, which compromise data accuracy and decisionmaking. Moving forward, industrial AI technology, coupled with the right digital backbone, can play a pivotal role in how data is captured, analyzed and used to optimize project outcomes.

For construction and engineering organizations to reap the full value of AI, a reliable digital foundation is required to ensure strong systems and quality data. A house cannot be built without a foundation, the same as an AI system will not be effective without a digital backbone. This is where that comprehensive ERP solution comes in. The transition to data-driven management will be vital for unlocking AI’s full potential.

When it comes to data and data analytics, AI has the potential to collect, process, and analyze large amounts of data from various sources, including ERP systems, to provide insights and predictions for construction projects, such as site conditions, project risks, forecast future project costs and margins and performance indicators. All of this is a great leap forward from the traditional use of spreadsheets.

Improved project financial control processes include project estimating, project budgeting and project forecasting. Automation and intelligent forecasting have great potential. Today, most companies manage these processes using non-integrated processes and with the use of many manual Excel spreadsheets.

If we have high-quality consistent data, AI can help identify project and business process anomalies and, with the use of AI agents, automate the required actions. This will allow management to focus on other tasks instead of spending too much time collecting data and documents and writing reports.

AI can use intelligent character recognition to scan and interpret documents, reducing manual data entry and improving accuracy. This is particularly valuable for handling large volumes of documents such as goods received notes on construction sites or perhaps reconciling bids.

AI can be used to improve risk management by identifying and evaluating risks and opportunities, helping managers take corrective actions promptly. This enhances the overall control and management of projects.

AI agents can analyze contract and project changes providing recommendations to mitigate potential issues and improve project outcomes. This helps in managing the financial and operational aspects of projects more effectively. AI agents can also analyze effects on the project margin and timeline based on the changes.

By automating repetitive and time-consuming tasks, AI agents can improve operational efficiency, reduce costs and enhance the overall productivity of construction and engineering companies.

Construction and engineering companies often have diverse businesses that do more than deliver design and construct projects. For example, their services may include manufacturing, asset management and rental of equipment and service or facilities management. There are also many AI opportunities that can be implemented for all functional areas of the business: asset management, service management, finance, inventory management and supply chain, human capital management, manufacturing, purchasing, health and safety and ESG.

For construction and engineering organizations, AI will increase overall efficiencies, standardize processes, enable greater project and business control and build resilience to optimize processes and improve decision-making. Ultimately, for industrial AI to deliver real value, it needs the support of comprehensive ERP that will allow construction and engineering organizations to safely take the first steps on their transformation journey.

Kenny Ingram is vice-president of construction and engineering at Institute for Fiscal Studies, a U.K.,-based economics research organization.