Engineering has always relied on experience, judgment, and knowledge built over decades of projects. Today, artificial intelligence is helping engineers unlock that knowledge faster, but the engineer remains at the center of every decision.
According to Hani Akkari, Technical Director at Egis, structural engineering has always been data-rich. Every project generates valuable information, yet much of that data has traditionally remained archived rather than fully utilised.
Artificial intelligence is changing that by transforming historical project data into knowledge that can support future projects.
Instead of spending weeks developing early predictions, engineers can now access informed starting points much faster, giving them more time to focus on what matters most: evaluating solutions, exploring alternatives, and making better engineering decisions.
However, as he explains, AI is only as good as the data behind it. Data quality remains the foundation for every meaningful prediction.
Where the Biggest Decisions Are Made
The greatest opportunity for AI comes during the concept stage.
This is where solutions remain flexible, changes can still be made easily, and the decisions taken will influence the rest of the project.
By using AI-powered predictions, engineers can begin from more advanced starting points instead of building every option from scratch. The time saved can then be invested in exploring different structural systems, materials, and design approaches.
For clients, that means better decisions earlier in the process, with a positive impact on cost and programme.
Prediction Supports. Engineering Decides.
The role of AI is clear.
It provides predictions based on data, but it does not replace engineering judgement.
As Hani puts it:
"AI estimates, finite element validates, engineer decides."
Engineering analysis remains essential, and the final responsibility always stays with the engineer.
Confidence Starts with the Right Controls
Engineering is built on safety, and every prediction must be trusted before it is used.
AI-generated predictions pass through engineering filters and validation checks before they are presented to engineers. These preliminary outputs help accelerate the design process while ensuring that every recommendation is reviewed and validated before moving forward.
The technology supports the engineer but responsibility never changes hands.
Turning Experience into Earlier Decisions
One practical example is ColumnEgisAI, an internally developed tool that predicts preliminary column sizes within seconds.
Instead of waiting for detailed calculations, architects and clients can review multiple structural options during the earliest design discussions, helping shape projects while ideas are still flexible.
A similar approach is applied through CoreWall AI, which provides preliminary core wall thicknesses while considering building drift and optimum material usage.
Together, these tools allow engineers to begin with stronger foundations, while retaining full engineering oversight throughout the design process.
The Future Belongs to Engineers Who Use AI Well
Looking ahead, Hani believes the engineer's role will continue to evolve.
As AI takes over repetitive engineering tasks, engineers will have more time to focus on judgement, innovation, leadership, and responsibility.
The future is not about competing with AI.
It is about knowing how to use it, challenge its outputs, and apply it with the right engineering perspective.
"The successful engineer will not compete with AI, but know how to use AI, challenge its output, and use it in the correct perspective."
