The numbers are difficult to ignore. According to a 2025 analysis from the Pew Charitable Trusts, 24 U.S. states project a combined $86.3 billion funding gap over the next decade to keep their roads and bridges in good repair. That shortfall exists even after accounting for federal programs, increased state spending, and long-standing asset management requirements. That gap is beginning to shape the condition of the nation’s transportation network and the risks that agencies and DOTs face every day. What makes this gap especially difficult to close is that it’s driven by a lack of revenue and of defensible, consistent data that agencies can use to explain where the investments are going, why they’re needed now, and what happens if funding is delayed. Funding decisions too often depend on incomplete inspections or outdated assumptions. This makes budgets more reactive and ultimately leads to underinvestment in infrastructure maintenance.
Transportation agencies are being asked to justify more spending under tighter scrutiny while relying on planning tools that were never designed for the scale or complexity of today’s networks. The result is a system that struggles to make a financial case for maintenance and repairs, even when the long-term costs of delaying those repairs become clear.
Why Underinvestment in Infrastructure Maintenance Keeps Repeating Itself
Most transportation agencies aren’t ignoring maintenance needs. Instead, knowing about those needs and then communicating them to decision-makers constrains them. Traditional planning that relies on periodic inspections, sample-based assessments, and condition ratings can only be refreshed every few years. It can support compliance but falls short when agencies need to defend their requests in competitive or uncertain funding environments.
The Pew report highlights a recurring issue across states: inconsistent data and gaps in reporting. These make it difficult for decision-makers to fully understand the scope of infrastructure needs. Some states cannot clearly link funding levels to future outcomes, while others may lack reliable forecasts for asset degradation. Without that clarity, preservation becomes easier to defer to an unspecified date.
And it gets worse. As one recent report highlights, even states that have increased their transportation spending since the pandemic still expect gaps in their ability to maintain roads and bridges. Funding levels have risen, but confidence in long-term outcomes and improvements has not. When agencies cannot quantify risk early, they’re forced to respond later, when emergency repairs become necessary, and costs rise.
The Costs of Not Seeing Problems Early
The physical condition of U.S. roads reflects this increasingly recurring pattern. A growing share of the network is rated in poor or mediocre condition. It has roughness levels that affect safety, vehicle wear, and even public confidence. Recent reports show that drivers across the U.S. continue to experience deteriorating road quality, despite billions spent annually on maintenance and repair.
From a financial perspective, this matters because the cost curve for roadway assets is steep. Early interventions, such as sealing cracks or addressing surface distress, are relatively inexpensive. But once defects progress into structural failures, costs rise sharply. Agencies know this in principle. However, proving where and when those interventions will deliver the greatest return remains difficult without continuous, network-wide visibility.
Planning that relies on sparse data, in turn, prioritizes visible failures. Pothole fixes get funded because they are obvious, but fixing early-stage surface deterioration does not. Over time, that bias inflates costs and erodes trust in long-term planning models.
Turning Data Into a Financial Planning Tool
Agencies need data that reflects real conditions across their full road and infrastructure network. And, they need that data frequently to support forecasting and financial planning. Finally, that data needs to be defensible, transparent, and scalable. How is that precision not just possible, but achievable?
AI-driven roadway intelligence changes what is possible in this context. Instead of replacing human judgment, it strengthens it. Agencies can observe asset conditions continuously rather than periodically, gaining a better picture of how roads within their jurisdiction perform under traffic, weather, and time. That visibility, in turn, allows planners to model deterioration trends and align their budgets with measurable outcomes.
This shift has important implications for fiscal sustainability. Instead of framing budget requests around generalized needs or historical averages, transportation agencies can tie the same requests to specific risks, locations, and timelines. They can show how even modest investments today prevent far higher costs tomorrow, and how funds are allocated equitably across regions rather than focusing only on the spots where complaints are loudest, or failures are most visible.
Building Transparency and Trust Into the Process
Data-backed planning also changes how agencies communicate with legislators, oversight bodies, and the public. In addition to improving internal decision-making, conversations with key stakeholders can shift toward evidence-backed decision-making that’s based on clearly observable conditions and projections.
The Pew analysis notes that inconsistent data reporting limits policymakers’ ability to evaluate whether spending aligns with stated goals. Better data closes that gap. It allows agencies to explain tradeoffs, defend prioritization decisions, and track their progress over time. That transparency is essential, especially as it provides the evidence needed to combat underinvestment in infrastructure maintenance.
For state and local agencies, this approach can help to stabilize funding discussions that may otherwise be shaped by short-term pressures and needs. Continuous data supports longer-term preservation strategies, making them harder to dismiss and easier to sustain even across political cycles.
A More Sustainable Path Forward
Too often, chronic underinvestment in transportation infrastructure maintenance is simply unavoidable. In practice, it’s a planning challenge that better information can help to overcome. The $86.3 billion funding gap is a warning sign, but it can also signal the need to rethink and update current planning methods to account for the scale of the problem.
Integrating continuous, network-wide data into financial planning allows agencies to move from reactive budgeting to proactive stewardship. Reducing their reliance on emergency repairs, they can improve forecasting accuracy and make stronger cases for preservation funding.
This approach, in turn, creates a more data-based strategy that, at its best, can actually lead to more equitable decision-making that bridges the infrastructure divide. Over time, it transforms how they build, evaluate, and sustain transportation budgets for future years.
Building a More Confident Infrastructure Plan
There is little doubt that transportation agencies face headwinds in doing more with limited resources, all while maintaining transparency and accountability. Meeting that challenge requires moving beyond assumptions and inconsistent or incomplete data, and toward verifiable, comprehensive insights into the entire road network.
That’s where Blyncsy comes in. The platform provides agencies with precise, scalable roadway data that supports smarter financial planning and clearer budget justification. By grounding investment decisions in real-world, real-time conditions, agencies can build better budgets, reduce long-term costs, and earn greater trust from the stakeholders they serve.
