Here’s one example: let’s say an EPC software includes AI-powered functions that  analyze data from past projects to predict potential problems in ongoing projects, which allows managers to plan for those problems in advance and thereby avert or minimize negative impact on the project timeline. With human error eliminated, such systems offer a very high level of accuracy in addition to efficiency and speed and this is very useful in time-sensitive work environments like construction project management.

Another example: AI-driven EPC project management software can automatically ie without human oversight carry out routine time-consuming tasks that would otherwise require a lot of expensive man-hours. This frees up human managers to focus on tasks that do require human intelligence or action and which cannot be automated. Advanced AI models can even be trained to differentiate between the two so that if and when a deviation or crisis which requires human intervention does occur, the human manager is called in to take over, but not before.

A third example: let’s say an infra projects company starts using AI models – built in to their EPC software – to analyse their historical project data in an attempt to gain insights into schedule management. They factor in  all the variables that could impact the schedule and correlate them (but behind the scenes before their impact is seen on the project site) and take steps, based on those AI-driven insights, to take ‘proactive’ ie predictive action. This type of ‘proactive’ project management garners them visibly better results: less delay, more control, fewer surprises.

A fourth and final example: invoicing. Manual processing of project purchase orders and invoices is tedious and time-consuming. It involves a lot of checking and re-checking and cross-referencing (with other departments, with budgets, etc) as well as a great deal of meticulous monitoring to prevent or correct any discrepancies. With an EPC software a vast part of this process can be performed by AI, in a fraction of the time; in fact AI is the perfect tool for this kind of job, and indeed any such job that requires extreme attention to detail and adherence to process, and which is usually seen as onerous and thankless by human workers.

These examples are just the tip of the iceberg; we’ve only begun to scratch the surface of how AI can improve project delivery outcomes. But even so far, companies that have tried  AI-enhanced systems report very encouraging results – like dramatic drops in project delay and project costs, tangible improvements in efficiency and productivity, and intangible benefits like better relationships with vendors and stakeholders, more trust between partners, and so on.