The transportation sector is at a pivotal moment. As aging infrastructure, decarbonization goals, workforce shortages, and funding pressures converge, the industry is also being pushed to modernize faster than ever. These challenges are accelerating the need for innovation and reshaping how transportation organizations plan, design, build, and operate for the future.
Digital transformation and technologies like AI and cloud are helping organizations connect data across the infrastructure lifecycle, creating new opportunities to plan and deliver infrastructure more effectively.
Autodesk’s latest 2026 Design & Make Report: Spotlight on Transportation examines what this disruption means for transportation, an industry at an inflection point, and what sets leaders apart.
Drawing insights from 900 leaders and experts from 14 countries across the transportation industry, this report sheds light on what it really takes to turn digital ambition into operational advantage.
Digital transformation is no longer optional. According to Autodesk’s report, 60% of transportation organizations have made substantial progress, while another 16% are accelerating investment to drive further adoption.
Core technologies such as BIM and GIS have become foundational across transportation organizations, with half reporting they are nearing full implementation. At the same time, most organizations are advancing toward more data-driven operations.
More advanced capabilities — including digital twins and generative design — are also gaining traction, with more than half of organizations reporting they have reached full implementation.
At this stage, the challenge is no longer digital adoption alone. Most transportation organizations already have core technologies in place. What now differentiates leaders is their ability to connect data across systems, teams, and partners.
Digitally mature organizations are pulling ahead because they have built more connected data environments that enable information to move seamlessly across the infrastructure lifecycle. As a result, these leaders are realizing measurable gains in efficiency, stronger collaboration, and greater resilience in the face of disruption.
While the majority of transportation leaders (84%) agree that poor data management impacts project delivery, a significant number (40%) admit they struggle with siloed data. So, while leaders clearly recognize the importance of connected, accessible data, there is a gap between that awareness and execution.
One of the biggest challenges in closing that gap is data governance and security, a priority with many public sector entities. Nearly half (45%) of transportation industry leaders point to security and privacy as the top barrier to interoperability.
While addressing these challenges is complex, the payoff is significant. Our research shows that organizations that successfully improve data governance and interoperability report stronger performance outcomes, including less rework, shorter project timelines, and more effective collaboration with external partners.
According to Amanda Coleman, Engineering Innovation & Data Center Manager at the Port of Portland, OR, “We are stewards of data, whether that be an old drawing from 1900 or a model with asset data attached to it. Our role is to understand what data is important to the organization and how we capture it, store it, maintain it, and make it available to the rest of the organization.”
The takeaway is clear: technology alone isn’t the differentiator anymore — connected data is.
Organizations that treat data as a strategic asset across the lifecycle will be the ones that move faster, reduce risk, and deliver better outcomes.
Just as digital transformation evolved from a competitive advantage to an imperative, AI is now following the same trajectory. It’s no longer viewed as optional or experimental. A whopping 99% of transportation leaders say AI is necessary to remain competitive.
Why are leaders increasingly optimistic about artificial intelligence? It increases capacity and improves productivity, with 84% saying that AI gives time back to focus on other, higher-priority tasks. Beyond saving time, AI also helps teams solve problems faster and make better decisions, with 79% saying it accelerates solving tough engineering problems and 77% saying it contributes to infrastructure resiliency.
AI is not about replacing people — it’s about augmenting human expertise and enabling teams to focus on higher-value work. The greatest value from AI comes when humans remain in the loop, combining machine speed and pattern recognition with human judgment, creativity, and domain expertise.
In transportation and infrastructure, that means reducing the time teams spend on manual checking, rework, and navigating complex project data so they can focus more on engineering, problem-solving, and critical decision-making that improves project outcomes. As organizations move beyond using AI solely for repetitive tasks, they are creating capacity to do more with existing teams while empowering employees to work more strategically and effectively.
This human-centered approach to AI is becoming especially important as the industry faces an aging workforce and persistent talent shortages. Organizations that successfully integrate AI into existing workflows are not replacing talent — they are amplifying it.
Take companies like Mott MacDonald, an engineering, development, and management consultancy company. According to Jay Mezher, Vice President, Digital Delivery, “We’re using AI to automate tasks in parametric design; a lot of coding that we used to do manually is now automated.”
That matters in an industry where delays are expensive, and resources are limited. Teams can move faster, focus on higher-value work, and deliver projects with more confidence, even when conditions are unpredictable.
AI is already reshaping how transportation projects are planned and delivered. The greater risk is no longer experimenting with AI — it’s delaying adoption while the industry moves forward.
Workforce shortages are concerns across many industries, and transportation is no different. Ninety percent of industry leaders say they are concerned about future talent availability.
The transportation industry is also facing a growing shortage of talent. As infrastructure investment accelerates and experienced professionals retire, organizations are struggling to attract enough specialized engineers to meet demand. This is especially critical in transportation, where projects rely heavily on deep engineering expertise and long-term institutional knowledge.
Concerns about the talent shortage aren’t abstract — the sector is feeling it on active projects today. Autodesk’s data shows that 38% of transportation organizations are already seeing the impact in the form of higher recruitment costs, reduced project quality, and operational inefficiencies.
The shortage of engineering talent does more than constrain hiring — it limits organizational capacity at a time when transportation projects are becoming increasingly data-intensive and complex. Engineers today are expected to navigate growing volumes of fragmented information while delivering projects faster, more efficiently, and with greater resilience.
Leading organizations are addressing this challenge by reducing the operational burden of data management and enabling engineers to focus on higher-value technical and strategic work. By improving access to connected, trusted information — and accelerating the ability to find, interpret, and act on that information — teams can make decisions with greater confidence, adapt more quickly as conditions change, and keep projects moving forward with less disruption.
To help address growing workforce constraints, transportation organizations are increasingly looking to AI as a force multiplier. In fact, 72% of respondents say AI has the potential to help alleviate workforce shortage challenges.
This shift is not about replacing people — it is about augmenting their capabilities and enabling teams to focus on higher-value work. As AI automates more repetitive and time-intensive tasks, engineers and project teams can spend more time on problem-solving, design, collaboration, and critical decision-making.
At the same time, realizing the full value of AI requires new skills and organizational capabilities. As a result, many transportation organizations are prioritizing talent with AI and digital expertise to ensure teams can effectively integrate these tools into existing workflows and project delivery processes.
The organizations making the most progress are taking a balanced approach — adopting AI while simultaneously investing in the skills, training, and change management needed to help teams use these technologies effectively. The goal is not simply to deploy new tools, but to build a workforce that can apply AI in ways that improve decision-making, increase productivity, and deliver better project outcomes.
Another key finding that emerged from the report is the importance of collaboration. Seventy-eight percent of leaders say collaboration has had a positive impact on project outcomes, often leading to more innovative solutions and smoother project delivery.
Some specific benefits include time savings (61%), improved project quality (59%), and lower costs (49%).
Organizations are investing heavily to improve collaboration. In fact, 81% now have dedicated roles or teams focused on it. But there’s a disconnect between effort and results. While 79% of leaders believe collaboration across their teams is strong enough to support project success, more than half have still seen projects fall short.
The issue isn’t intent, but execution. Teams may be aligned in theory, but in practice, they’re often working across disconnected systems, inconsistent or siloed data, and unclear workflows. Not all teams have a shared digital foundation, which leads to misalignment.
Effective collaboration in transportation doesn’t just happen by accident.
It requires structure, connected data, standardized workflows, and the right operational structure to enable coordination across teams and stakeholders. Organizations that get this right create greater alignment, accelerate decision-making, and identify issues earlier — reducing delays and improving project delivery outcomes.
Sustainability and resilience are no longer secondary considerations in transportation. They have become core strategic priorities shaping how transportation projects are planned, designed, and delivered.
More than 80% of leaders say resilient infrastructure is essential, reflecting the growing urgency facing transportation organizations today. Climate-related disruptions are more frequent, assets are under increasing strain, and public expectations around reliability, sustainability, and long-term performance continue to rise.
As a result, resilience can no longer be treated as a downstream design consideration. Leading organizations are embedding sustainability and resilience requirements early in the project lifecycle to better anticipate risk, improve asset performance, and deliver infrastructure that can adapt to changing environmental and operational conditions over time.
That shift is changing how teams approach design, with 81% of leaders reporting that they factor in long-term community and well-being at the design stage. In other words, resilience is a core pillar of planning and design, not revisited after issues show up.
Eighty-one percent of leaders report that long-term community well-being is a factor in project design.
Yanissa De Jonghe, Head of Technology and Digital Innovation at Lantis, reiterates this sentiment. “One of our moonshots is that we want to build eco-positive. That means constantly challenging how we design and build infrastructure.”
Teams are also thinking more about climate risk, water management, and long-term community impact from the start. Water in particular has become a major focus, with nearly all leaders calling it a priority as risks become harder to ignore.
AI and connected data are making sustainability and resilience goals more actionable and measurable. Rather than relying on assumptions or retrospective analysis, transportation organizations can increasingly model scenarios, evaluate tradeoffs, and make more informed decisions earlier in the project lifecycle.
Organizations that are further along in their AI and digital maturity are also more likely to incorporate complex risk factors — such as climate exposure, and long-term community outcomes — into planning and design decisions. With greater visibility into project, asset, and environmental data, these organizations are better positioned to anticipate risk, optimize outcomes, and plan with greater confidence and resilience over the long term.
Many leaders now see asset resiliency as a driver of revenue and long-term value, not just a compliance requirement. The takeaway is simple: resiliency isn’t separate from performance. It’s a big part of what drives it.
The industry is no longer struggling with digital adoption alone. Most organizations already have core tools in place. The real differentiator now is execution; how effectively organizations integrate their technologies, teams, and data into everyday workflows and decision-making.
The organizations pulling ahead are not facing fewer challenges. They are building more effective ways to navigate them. They are connecting data across the infrastructure lifecycle, embedding AI into operational workflows, and investing in skills and capabilities their teams need to succeed. Just as important, this approach improves day‑to‑day project efficiency while supporting long‑term asset resiliency, so decisions made during delivery strengthen performance and durability over the entire asset lifecycle. Equally necessary, these organizations are aligning short-term project execution with long-term asset performance. By integrating data, digital workflows, and AI-driven insights throughout planning, design, delivery, and operations, they are improving day-to-day efficiency while strengthening the resilience, reliability, and durability of infrastructure assets over time.
Transportation infrastructure will always be complex, requiring deep expertise, sound judgment, and the ability to navigate real-world tradeoffs. Today, that challenge is intensifying as organizations manage aging assets, constrained budgets, workforce pressures, and increasingly unpredictable environmental and operational conditions.
In this environment, the quality and timing of decisions matter more than ever. Early-stage planning and design choices can significantly influence long-term cost, performance, resilience, and project outcomes. As a result, leading organizations are placing greater emphasis on making better-informed decisions earlier in the lifecycle — using connected data, digital workflows, and predictive insights to reduce downstream risk and avoid costly reactive responses later.
The path forward is becoming increasingly clear. Transportation organizations must move beyond isolated technology adoption and focus on building the operational foundations required to scale transformation effectively. That starts with connecting data across the infrastructure lifecycle, so teams and stakeholders can operate from a shared source of truth. It also requires investing in the tools, skills, and organizational capabilities needed to translate technology investments into measurable business outcomes.
At the same time, resilience and sustainability can no longer be treated as downstream considerations. Leading organizations are embedding these priorities into strategy, planning, and delivery from the outset — enabling more adaptive infrastructure systems that can perform under increasingly uncertain conditions.
The organizations that act decisively now will do more than keep pace with industry change. They will define the next era of transportation infrastructure: delivering projects more efficiently, operating assets more intelligently, and building more resilient systems for the long term.
Want more insights on the future of transportation and how to prepare for it? Check out Autodesk’s Design & Make Report: Spotlight on Transportation.
