FAA rolls out SMART AI to forecast US flight delays

The Federal Aviation Administration has begun rolling out a new artificial intelligence system called SMART, designed to predict flight delays before aircraft leave the gate and to give traffic managers more time to keep passengers and planes moving across the United States.

What SMART Is And How It Works

SMART, short for Strategic Management of Airspace, Routes, and Trajectories, is a cloud-based traffic management platform that layers artificial intelligence on top of existing Federal Aviation Administration systems. Publicly available descriptions indicate that it pulls together hundreds of data streams, from airline schedules and filed flight plans to radar feeds, airport runway configurations and staffing information at key facilities.

According to FAA fact sheets, SMART analyzes this information alongside detailed weather forecasts, airport capacity signals and broader airspace conditions to anticipate where demand for airspace will outstrip available capacity. The system then uses an AI-supported engine to model how traffic is likely to evolve in the hours ahead, highlighting specific flights, routes or time windows where congestion and knock-on delays are most likely to emerge.

Instead of reacting to bottlenecks once aircraft are already queued on taxiways or holding in the sky, SMART is intended to shift more of the decision making to the pre-departure phase. By showing planners, airline operations centers and air traffic managers a shared, data-driven picture of expected traffic, the tool is designed to encourage earlier adjustments such as retiming departures, rerouting aircraft around storm systems or spacing out demand at overburdened hubs.

Published coverage emphasizes that SMART functions as an advisory tool rather than an automated controller. It does not issue clearances or replace human decision making in the tower or en route centers. Instead, it provides forecasts of traffic flows and potential conflicts that can inform how people sequence flights, allocate runways or meter traffic into busy airspace.

Initial Deployment At Washington Area Airports

Reports indicate that the FAA began live operational use of SMART this week at three major airports serving the United States capital region: Ronald Reagan Washington National, Washington Dulles International and Baltimore/Washington International Thurgood Marshall. The focus on the Washington area allows the agency to test the system in a region with dense traffic, complex airspace and frequent weather disruptions.

The early rollout involves integrating SMART into the workflow at the FAA Command Center and local facilities that manage traffic into and out of the three airports. In practice, that means planners can see predicted surges in departures or arrivals several hours ahead and can consider steps such as rerouting flows, adjusting miles-in-trail restrictions, or recommending departure time changes to airlines to smooth peaks.

Travelers in the Washington region are unlikely to see a dedicated SMART label in airline apps or on airport displays in the near term. The tool operates behind the scenes, feeding into the decisions that determine whether a particular bank of departures is allowed to push back on time or is spread out to avoid congestion later in the day.

Public information from the agency indicates that, after the Washington deployment, the FAA plans to expand SMART to additional parts of the country in phases. The timing and sequence of that wider rollout have not been detailed, but the long-term objective is to apply the same predictive approach across major corridors where bad weather and tightly packed schedules routinely trigger widespread delays.

Potential Benefits For Travelers And The Aviation System

Flight delays in the United States regularly cascade across the network when storms, staffing shortages or unplanned ground stops disrupt peak travel periods. Research cited in federal planning documents links these disruptions to significant economic costs, in part because a late departure in one city can ripple through an aircraft’s subsequent rotations throughout the day.

SMART is designed to reduce those knock-on effects by giving traffic managers more advance warning. If the system shows that a busy evening arrival bank at a hub airport is likely to be constrained by thunderstorms or limited runway capacity, traffic planners might try to move some connecting flights earlier, reroute aircraft around the most affected airspace, or meter departures from feeder airports so that fewer flights arrive at once.

For passengers, the impact is expected to be indirect. Travelers may still receive delay notifications in airline apps or see gate change announcements, but the goal is that these adjustments happen earlier and in a more coordinated fashion, reducing the chances of long tarmac waits, rolling departure estimates or last-minute cancellations. Publicly available information on the program suggests that success will be measured in terms of reductions in total delay minutes, fewer cascading disruptions and more predictable daily operations.

The tool may also contribute to environmental and operational efficiency goals. By identifying where congestion on the ground or in the air is likely to form, SMART could help cut down on extended taxi times with engines running or repetitive airborne holding patterns, both of which burn fuel and add to emissions. Any measurable improvements along those dimensions are expected to emerge gradually as the system is validated and expanded.

How SMART Fits Into The FAA’s Technology Strategy

The launch of SMART builds on a broader shift toward data-driven traffic management within the FAA. Over the past decade, the agency has invested in new platforms for sharing information across airlines, airports and air traffic facilities, as well as tools that provide real-time views of traffic flows and airport surface movements.

In technical planning documents, the FAA has described the need for AI and machine learning applications that can help balance demand and capacity across the National Airspace System while preserving safety margins. SMART represents one of the first high-profile operational deployments of such a tool aimed squarely at delay reduction, rather than purely at research or simulation.

The system works alongside existing programs such as the FAA’s daily air traffic reports, which provide broad expectations for delays and ground stops at major airports. Where those public reports summarize anticipated impacts, SMART aims to highlight specific flights and routes that are most likely to be affected, giving managers a finer level of control when deciding which departures to slow, reroute or keep on time.

External analyses also point out that SMART is arriving amid heightened public attention to aviation system reliability, following several years marked by high-profile disruptions and crowded peak travel seasons. The initiative is framed as one way the agency is trying to use newer analytical tools to anticipate problems rather than respond to them as they occur.

Limitations, Questions And Next Steps

Despite its promise, SMART comes with clear limitations that have been outlined in public discussions of the program. The quality of any forecast depends on the accuracy and timeliness of the underlying data, from weather models and staffing plans to airline schedules and airport capacity estimates. Rapidly changing storm systems, unexpected ground stops or late-arriving aircraft can all undermine predictions that looked reliable only a short time earlier.

The tool also operates within a complex web of operational and commercial priorities. Decisions to delay or reroute flights affect airlines differently depending on their schedules, hub structures and passenger connections, which means that any system recommending preemptive changes must account for questions of fairness and impact distribution. Advisory panels that review FAA use of AI and machine learning have urged the agency to track metrics such as aggregate delay and how delays are spread across airspace users when new tools are deployed.

Another open question is how quickly and extensively SMART will be adopted beyond the initial Washington-area deployment. Scaling the system nationwide will require training for air traffic personnel, integration with local procedures and coordination with airline operations centers across multiple regions. Early phases are likely to focus on data validation and performance assessment, comparing SMART’s predictions with actual outcomes to gauge where the tool adds the most value.

For now, the introduction of SMART marks a notable step in the gradual modernization of U.S. air traffic management. While travelers may not see an immediate transformation in on-time performance, the system reflects a broader move toward anticipating where delays are likely to form and trying to address them before they strand passengers at the gate.