Artificial Intelligence for Engineering Procurement & Construction
Artificial Intelligence or AI means using machines to help us work faster and better. AI leverages sophisticated software algorithms ‘trained’ over time to analyse huge amounts of data to either replace human effort or assist it, and thereby produce better outcomes and results. That is one way to think of AI. Now apply this to EPC project management software and the parallel is clear; much of project management is data-based so using AI to replace or improve decision-making seems only logical and in fact, we’re beginning to see this happen in the real world as AI-driven systems are assisting human managers to make better decisions, faster.
How does AI work in the EPC context?
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.
Industry Reactions to AI in EPC: From Skepticism to Adoption
It must be said, however, that there is a huge variety in the industry’s reaction to AI-driven EPC project management software ranging from eager and enthusiastic acceptance to outright distrust and dismay. Yet, AI in itself is not a new development; after all machines have been impacting the way we plan and build all through history and as with every other new technology, there will of course be differences in how people adopt and work with the new systems.
A good way to think of it would be to define different ways of interacting with such systems.
For example, AI can automate ie entirely replace a human-led process – consider ATM machines – and in such cases of course, there will be some who prefer to work with human tellers and therefore most banks still offer that option, albeit in a much more limited way.
Or, AI can simply augment the process ie it can offer insights and data and advice that nudge the human worker towards informed action. EPC software which offers such AI-augmented functionality is now available and it is likely that more companies will explore such solutions in the future. In other words, AI as a support to human decision-making is likely going to be the more comfortable option at this time.
In conclusion, although the term AI is being increasingly thrown around, the definition of what it actually is is still very much open to interpretation (and context). Some dub any kind of automation “AI”, arguing that any system that replicates human effort is displaying rudimentary ‘intelligence’ while others believe the word ‘intelligence’ is itself open to interpretation. This fuzziness must therefore apply to artificial intelligence as well. Such debates will continue for many years yet but it seems fair to say that technology and automation is here to stay, to the point where human and artificial/machine roles will continue to overlap and that is true of EPC project management as well.