The Road Ahead: AI and the Texas Department of Transportation
In June 2025, Texas signed the Responsible Artificial Intelligence Governance Act into law, outlining statutory requirements for the state’s use of AI. In response to this, the Texas Department of Transportation (TxDOT) released an updated Artificial Intelligence Strategic Plan in January 2026.
TxDOT is one of the largest state agencies in Texas, responsible for managing about 12,000 employees, nearly 200,000 miles of highways and other critical transportation infrastructure. The Department’s goal for AI implementation is a broader organizational transformation to continue stewarding and further developing a safe, efficient and resilient transportation network for Texans.
For vendors and partners, TxDOT’s plan to implement AI, includes specific goals, use cases and opportunities to expand solution offerings.
AI Goals
TxDOT is focused on transitioning from isolated pilot projects to integrating AI throughout its operations and digital infrastructure. The Department prioritizes three categories for use cases:
- Intelligent Delivery: Accelerating operations and project schedules by optimizing efficiency and accuracy
- Predictive Asset Management: Using data-informed models to transform fleet and infrastructure management
- Proactive Safety & Mobility: Identifying roadway safety issues with real-time sensor fusion and computer vision
In all use cases, TxDOT is emphasizing the importance of any technology solution being “Human-Led, AI-Supported.” Vendors and partners should be aware that the state agency has no desire to completely automate with zero human oversight. TxDOT wants every output to be reviewed and validated by a human professional. Technology solutions for the Department must keep humans in the loop to comply with its AI initiatives.
Past & Current Implementations
TxDOT has already implemented several AI projects. Its flagship project was automating invoice processing in the Professional Engineering Services Division, which had benefits including:
- Cutting processing time by 75%
- Saving an estimated 22,000 staff hours annually
- Minimizing errors while eliminating late fees
This illustrates TxDOT’s priorities for initial AI rollout: saving money and manpower. Additional current operational uses for the technology that also accomplish these aims include:
- Automating employee onboarding/offboarding process
- Streamlining pre-letting and bidding
- Drafting documents
- Synthesizing meetings
- Modernizing fleet procurement
All of these use cases are centered on enabling increased efficiency in TxDOT so it can focus on its core transportation mission and objectives.
As categorized by TxDOT, the vast majority of completed and in progress AI projects enable greater business productivity, rather than increased traffic safety or managing physical assets.
This means that empowering and streamlining internal operations is currently a high priority. Its present needs are more aligned with an AI-augmented HR or audit department, instead of using the technology to design highway routes or analyze soil; there is a higher ROI on implementing the former, which is why it is a focus of TxDOT.
While there is still some emphasis on imagining how AI can be used for external use cases like fleet management and engineering, TxDOT is spending more resources to ultimately reduce the enormous amount of employee hours and money spent on internal business processes. Vendors and partners should focus on helping the very large state agency with solutions that can compress these complex internal processes, allowing it to focus on its wide-ranging infrastructure portfolio and jurisdiction.
Future Use Cases
TxDOT currently has over 200 theoretical use cases for AI. Future objectives in development include:
- Automatically monitoring servers for outdated files and preparing them to be archived
- Using machine learning to review fuel card use to prevent misuse
- Developing a tool to improve the accuracy of transportation cost estimates
- A chatbot for general information on TxDOT online manuals and Texas Administrative Code
- Automating invoices and refunds
Similar to recent implementations, the majority of planned AI projects are categorized as business productivity. TxDOT is actively focusing on streamlining its operations and improving business processes in the next phase of AI implementations. Vendors and partners should prioritize this when proposing potential solutions.
Foundational Technology Architecture
TxDOT is actively building robust digital infrastructure to support AI project development and operational excellence, along with data integrity and compliance.
It has identified three main foundational technologies that support this goal: scalable machine learning platforms, resilient cloud infrastructure and low-code/no-code AI design studios.
Scalable machine learning standardizes AI model development, which creates more rapid experimentation for a wide range of use cases. The cloud infrastructure enables AI applications to be deployed in secure environments while creating seamless integration between TxDOT’s internal systems and external data sources.
Those two technologies are used in conjunction with an Enterprise Data Platform (EDP). Its EDP has consolidated nearly 100 data solutions from over 50 sources, providing high-quality fuel for accurate AI modeling.
Of particular note, TxDOT does not want innovation in AI to come exclusively from a small number of expert professionals. Its focus on giving non-technical employees access to low-code/no-code design studios would allow innovative, custom solutions to be created relatively easy and quick. An explicit goal of TxDOT is the democratization of AI, which would allow solutions to come from employees closest to operational challenges.
Vendors and partners need to be able to support TxDOT’s goal of creating organic, employee-driven solutions that solve real problems within the state agency.
Key Takeaways
TxDOT’s main long-term priorities for utilizing AI are improving internal operations and projects, managing fleet and infrastructure and creating safer roadways. However, recent and current AI projects show that increasing business productivity is currently the highest priority.
TxDOT is very interested in technology solutions that drive organizational efficiency, empower decision-making and streamline internal workflows. Vendors and partners should be able to show how their solutions enable more manpower and financial resources to be reallocated to TxDOT’s core focuses, such as roadway construction or engineering innovations.
Additionally, TxDOT wants innovation to come from within with digital infrastructure that allows non-technical employees to see their ideas come to fruition. Vendors and partners should offer solutions to create AI tools that even employees with novice (or even no) coding skills could utilize.
IT companies should be able to show the value of their technology solutions in automating time-intensive, complex processes to enable TxDOT to focus on its core mission: maintaining and expanding Texas’ massive transportation system.
To get more TD SYNNEX Public Sector Market Insight content, please visit our Market Intelligence microsite.
About the Author: Austin Gardner is a Discovery Rep on the DLT Market Insights team. He graduated from the University of Texas at Austin and lives in Washington, D.C.
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