Page 21 - BENTLEY SYSTEMS PR REPORT - MAY 2023

Over the last year, there has been a lot of discussion about using AI-powered applications and
solutions to improve project efficiency, organisational effectiveness, and infrastructure
outcomes. Leveraging AI, machine learning, and other intelligent applications presents immense
potential for addressing issues across the infrastructure life cycle.

Unfortunately, data is the foundation for AI-powered anything and the infrastructure sector has
a large data management hurdle it must clear before the promise of AI can be realised.

Better data

For decades, the infrastructure project lifecycle was linear. Planning, design, procurement,
construction, and operations had distinct phases with individual stakeholders, requirements, and
discrete hand-offs. Each phase typically used different technologies and processes.

This approach created information silos and data loss, resulting in design rework and errors,
project delays, and increased costs and risks.

As infrastructure projects and their respective phases have become more interconnected, there
is a real need for bringing engineering, information, and operational technology systems and
data together.

But the reality is that an abundance of valuable data from these technology systems is trapped
in files, models, drawings, and even paper. Unlocking this data is critical to better decision-
making across the infrastructure project lifecycle as well as for using AI-powered solutions.

Instead of generating critical project and asset data in disparate systems, infrastructure
engineers, construction contractors, and owner-operators should start producing data layers
with open platforms that generate digital twins.

Digital twins

https://www.intelligentcio.com/me/2024/05/08/can-genai-enhance-the-middle-easts-
construction-industry/