As the volume and velocity of project data continues to accelerate, the challenge facing infrastructure owners and delivery teams is no longer access to information, but making sense of it.
Construction productivity has historically lagged other sectors while broader research on workplace efficiency suggests knowledge workers can spend a significant part of their day searching for and reconciling information – reinforcing the need for smarter analytics and visualization in infrastructure delivery.
Today, digital advisory capabilities have become essential for helping clients cut through that complexity – supporting better decision-making, improving transparency and managing capital programs with greater confidence. Rather than relying on static dashboards or manual reporting, project teams are increasingly looking to advanced analytics, automation and AI-enabled workflows to surface insights faster and communicate them more effectively.
As STV, our digital advisory team is actively testing emerging visualization platforms and AI-enhanced coding workflows, paving the way for broader discussions about how these technologies will shape the next era of infrastructure data storytelling. In this roundtable discussion, Bilal Assaad, senior data scientist; Mark McElroy, digital solutions director; and Arnesa Novaj, data scientist reflect on how emerging AI tools complement – not replace – existing tools, and why combining technical depth with AI-driven workflows helps clients navigate the next wave of digital transformation.
As you think about how quickly digital tools are evolving, what stands out to you about where data analysis and visualization are heading in the industry?
Mark McElroy: AI-supported workflows aren’t theoretical anymore: they’re here. What stands out is how quickly we can build functional prototypes using coding frameworks and alternative visualization tools. Instead of manually assembling dashboards, we can write logic that automatically structures the data, applies modeling and generates interactive visuals on the fly.
This points to a future where analysts spend less time wrangling data and more time interpreting it: digging deeper into performance metrics, asset conditions and program risks. In an industry as data-heavy as infrastructure, that shift is enormous.
Arnesa Novaj: The value isn’t just efficiency; it’s clarity. Infrastructure project datasets are massive, and without strong visual storytelling, they can become overwhelming. By combining AI-enabled inputs with user-centered design principles, we can present clients with data insights in a way that supports real-time decision-making, with tools that help clients understand the “why” behind the numbers.
Let’s talk about the role of AI in complementing or even replacing traditional workflows. How do you see that relationship evolving?
Bilal Assaad: AI isn’t here to replace what works; it’s here to unlock what current software doesn’t capture well today. Those models are powerful, but they’re not always optimized for rapid scenario modeling, predictive analysis or cross-platform integration. When you pair AI and coding frameworks with those outputs, you can run simulations, evaluate alternatives and automate repetitive model-based tasks.
The same insights we currently obtain can be achieved through new digital workflows that are sometimes faster, sometimes more flexible and often in a manner that better supports program-level decisions.
Arnesa Novaj: Those models only work if experts train them. Our engineers, planners, estimators and project controls leaders are what makes these tools credible. STV’s strength is that these workflows are being shaped by SMEs who deeply understand construction, transportation, transit, energy and the broader infrastructure landscape in collaboration with data scientists.
When you consider how digital tools are advancing, what will define the next phase that will shape how these tools are applied?
Bilal Assaad: AI is changing workflows, but only because experts are behind the wheel. We can spend less time assembling reports and more time analyzing scenarios.
Mark McElroy: This evolution makes data more meaningful. By designing tools that prioritize clarity, interactivity and context, we help clients understand the story behind their infrastructure. That’s how we strengthen transparency and support better decision-making across major capital programs.
