---
title: "AI in Aviation: Inside the FAA's SMART Rollout and the Startups Building It"
description: "The FAA has expanded AI-supported flight planning across 22 US centers. Here's how SMART works, what AWS and Azure actually run, and why investors are backing aviation AI."
date: 2026-11-13T00:00:00.000Z
source: https://venturecapitaltracker.com/ai-in-aviation-faa-smart-cloud-asi-startups
---

# AI in Aviation: Inside the FAA's SMART Rollout and the Startups Building It

> The FAA has expanded AI-supported flight planning across 22 US centers. Here's how SMART works, what AWS and Azure actually run, and why investors are backing aviation AI.

Air traffic delays often begin long before an aircraft reaches the runway. A storm closes part of a route. Too many aircraft are scheduled through the same corridor. An airport has fewer usable arrival slots than airlines planned for. By the time passengers see a delay on a departure board, the disruption may already have spread across the network.

That is the problem the Federal Aviation Administration wants artificial intelligence to help solve. On November 10, 2026, the FAA said its new **Strategic Management of Airspace, Routes and Trajectories (SMART)** system was expanding to cover airspace managed by all 22 U.S. air route traffic control centers. The software predicts where traffic, weather and capacity constraints may collide, then helps humans adjust plans in advance.

For investors, the striking part is who built it: **ASI, formerly Air Space Intelligence**, a venture-backed software company that announced a **$325 million Series C at a $3 billion valuation** in October. In June, the company won a **12-year, $875 million FAA contract** covering SMART and the related Flow Management Data and Services (FMDS) program. The contract's announced value is not money already paid to ASI, and it is not a $875 million funding round.

## November 13, 2026 update: FAA orders nationwide departure ground stop

**Developing incident — information available on the evening of November 13, 2026.** The FAA's Air Traffic Control System Command Center issued a nationwide ground-stop advisory at approximately **20:54 UTC (3:54 p.m. Eastern)**, directing aircraft operators across the United States to hold departing flights on the ground for safety reasons. International inbound flights were to be handled individually. The order **did not instruct aircraft already airborne to land immediately**.

U.S. Transportation Secretary **Sean Duffy said a communications issue was affecting all 22 regional air route traffic control centers**, which manage aircraft between airports, and that FAA technicians were investigating. At the time of this update, **an officially confirmed technical root cause or restoration time had not been established in the public statements reviewed**. The 2023 nationwide departure halt followed a malfunction of a different FAA information system, the Notice to Air Missions (NOTAM) system; it does not establish the cause of this incident.

### Is the shutdown connected to SMART, AI or public cloud?

**No such connection has been established.** The timing is notable: the FAA announced the nationwide expansion of SMART on November 10, three days before the November 13 ground stop. But the FAA describes SMART as a **human-reviewed traffic-flow planning tool**, not the communications or radar system that allows controllers to manage aircraft safely. There is likewise **no verified public evidence** that the ground stop was caused by Microsoft Azure, AWS, the previous day's Microsoft 365 disruption, malicious cyber activity or a foreign government. Neither the rollout date nor the FAA's general use of commercial cloud services proves a shared technical dependency.

For aviation investors, the incident illustrates why the reliability, redundancy and fallback arrangements of the *underlying air-traffic infrastructure* matter alongside AI-assisted efficiency. The FAA's modernization program includes telecommunications and controller systems that are distinct from SMART. Until investigators identify the failure domain, claims assigning the incident to a specific software product or cloud vendor should be treated as unsubstantiated.

**Operational status may change after publication.** For live restrictions and subsequent official advisories, consult the [FAA's National Airspace System status](https://nasstatus.faa.gov/) and [FAA Air Traffic Control System Command Center](https://www.fly.faa.gov/).

## What SMART does — and what it does not

SMART combines approximately **200 data streams**, including airline schedules, flight paths, weather, traffic flow, airport constraints and controller staffing. Its job is to help planners spot bottlenecks early enough to change departure times or choose less congested routes.

The FAA describes a human review chain. Specialists at the SMART center in Washington, D.C., assess and validate its recommendations. They pass scheduling proposals to the FAA Air Traffic Control System Command Center in Warrenton, Virginia. The Command Center forwards them to affected facilities, whose local leadership decides what to use.

That is an important boundary. **SMART does not fly aircraft, issue autonomous clearances or replace controllers responsible for safe separation.** It is an AI-supported *planning and traffic-flow layer* operating alongside the systems controllers already use.

A simple example illustrates the value: if thunderstorms are forecast to restrict a busy air corridor later in the afternoon, the system can suggest changing departure times or routes earlier in the day. A few well-timed adjustments may avoid a queue of aircraft waiting on the ground or circling near a destination.

## From Washington trial to nationwide coverage

The FAA announced the ASI contract on **June 22, 2026**, began limited SMART operations around Washington's three major airports on **September 21**, and announced expansion to the airspace of **all 22 centers on November 10**.

The agency says its initial use helped reroute **180 flights**, saving an average of **10 minutes** and nearly **80 gallons of fuel per rerouted flight**. These are **FAA-reported early outcomes**, not independently audited nationwide results. They should not be extrapolated into annual national savings without more traffic, baseline and measurement data.

There is also a distinction between deployment and integration. Saying SMART covers the airspace of 22 centers does not mean the FAA has replaced every controller's workstation or fully commissioned every component of the much larger FMDS modernization program.

## How U.S. air traffic control actually works

It helps to separate several different functions that are often described collectively as "air traffic control."

**ERAM — en-route control.** The FAA's En Route Automation Modernization system processes surveillance and flight-plan information and gives controllers tools for monitoring and guiding aircraft between airports. The FAA says ERAM currently supports the **20 continental U.S. en-route centers**, with expansion to Anchorage and Honolulu beginning in 2027. That is why the figures **20 ERAM centers** and **22 SMART-covered centers** are not necessarily contradictory.

**STARS — airport-area control.** The Standard Terminal Automation Replacement System supports controllers handling arriving and departing aircraft near airports. It combines surveillance and flight-plan information and supports functions such as sequencing, safety alerts and radar vectoring.

**TFMS, FMDS and SMART — traffic-flow planning.** The existing Traffic Flow Management System helps balance demand with national airspace capacity. FMDS is the newer data and traffic-management backbone being developed for the Command Center; SMART adds predictive planning. These tools address *when and where flights should travel*, rather than taking over the controller's job of keeping aircraft apart.

**SWIM — aviation data exchange.** System Wide Information Management provides standardized information-sharing services across FAA programs and authorized aviation users. The public-facing SWIM Cloud Distribution Service supports distribution for external, non-operational uses such as research and business analysis.

**FENS — communications infrastructure.** The FAA Enterprise Network Services modernization is intended to replace aging telecommunications infrastructure connecting aviation facilities and systems. Public federal spending records identify **AT&T** as the contractor for an August 2026 early-start FENS planning order. A communications backbone is not the same thing as an AI application or a public-cloud provider.

In short, flight surveillance, safety separation, nationwide traffic planning, data distribution and telecommunications are related but different technology layers. A failure or improvement in one does not automatically explain what happens in another.

## Which clouds does the FAA use: AWS, Azure or something else?

The best-supported public answer is **both Amazon Web Services and Microsoft Azure — but not necessarily for the same systems**.

FAA Cloud Services 2 procurement documents explicitly seek access to **AWS and Azure** for FAA lines of business, including mission-related operating environments. A 2024 FAA market-research description put the agency's *then-current* cloud environment at approximately **95% AWS and 5% Azure**, across hundreds of hosting accounts. That is a **historical FAA-wide estimate**, not a verified 2026 split and certainly not the architecture of SMART.

An FAA reference architecture published in 2022 is equally revealing. It envisions a **hybrid model** combining commercial cloud infrastructure, FAA-controlled data centers and computing at aviation facilities. It discusses security, availability, latency and the different levels of criticality required by aviation services. It is a *target architecture*, not a map proving where each operational system runs today.

What can be established publicly?

- **FAA cloud procurement:** AWS and Azure are explicitly named.
- **SMART:** The FAA calls it cloud-based, but the production cloud provider and exact deployment topology have **not been publicly established in the sources reviewed**.
- **ERAM and STARS:** The FAA documents their operational roles at control facilities; those sources do **not** establish that safety-critical separation runs on either hyperscaler's public cloud.
- **NOTAM modernization:** The FAA describes a cloud-hosted replacement service supplied by **CGI Federal**, but does not name the underlying cloud provider in its public overview.
- **SWIM cloud distribution:** Cloud is explicitly used for external aviation data distribution; that should not be confused with remote cloud software directly controlling aircraft.

The difference is more than technical wording. "The FAA buys Azure" and "Azure is responsible for U.S. air traffic separation" are two very different claims. The first is documented; the second is **not supported by the public evidence reviewed**.

## The investment story: ASI is selling software into critical infrastructure

The **$875 million, 12-year award** covers both FMDS and SMART. It is a government program value over time, not annual recurring revenue or an amount the company has already earned.

ASI's October **$325 million Series C**, led by **Spark Capital**, included participation from affiliates of Citadel Securities, Meritech Capital, Craft Ventures, Energy Impact Partners and Andreessen Horowitz. Its reported **$3 billion valuation** reflects investors' expectations for technology that forecasts and optimizes complex physical systems, including aviation, energy and defense.

What makes this interesting is the potential business model. Rather than manufacture aircraft, ASI aims to sell decision software to institutions that already operate enormous physical networks. Once a product is integrated into operational workflows, the potential for recurring software revenue is significant — but so are implementation costs, security requirements, procurement uncertainty and service obligations.

For a deeper breakdown of the financing and the difference between contract value and revenue, see [Venture Capital Tracker's ASI funding analysis](https://venturecapitaltracker.com/asi-325m-series-c-3b-valuation).

## Other companies showing where aviation AI investment is going

ASI is not the whole market. It represents one category — network-level flight planning — while other companies work on aircraft autonomy, pilot assistance and operational data. Their financing is therefore **not a like-for-like comparison of direct SMART competitors**.

| Company | Product direction | Disclosed 2026 financing or transaction |
| --- | --- | --- |
| **ASI** | Airspace simulation and traffic-flow planning | **$325M Series C**; $3B valuation (October) |
| **Skyryse** | Software-defined flight controls and aircraft automation | **More than $300M Series C**; $1.15B valuation (February) |
| **Reliable Robotics** | Autonomous flight systems for existing aircraft | **$115M additional capital** in October, including $25M debt; valuation above $1B |
| **Navi AI** | AI-assisted pilot training and flight debriefing | **$6.7M total funding** announced in March |
| **Merlin** | Autonomous pilot technology | **About $200M gross proceeds** from a March SPAC combination; now publicly traded as MRLN |

There are established alternatives outside the venture-backed autonomy group. **Metron Aviation**, part of Stratify Aerospace, introduced new collaborative air-traffic-flow platforms in 2026, including AI-enabled predictive capabilities. And the FAA began operating its first camera-based digital towers in Florida and Alaska in November, using **Frequentis** technology. Digital towers are another form of aviation modernization; they should not automatically be labeled autonomous AI control.

These companies illustrate three different markets: improving the **flow of aircraft through shared airspace**, assisting the **people piloting aircraft**, and eventually automating more of the **aircraft itself**. They face different buyers, certification requirements and paths to revenue.

## What pilots and controllers say aviation AI still needs to solve

SMART has a clear technical purpose, but its success will ultimately depend on how well it fits the unpredictable work of flying and managing aircraft. Discussions in [r/ATC](https://www.reddit.com/r/ATC/comments/1wj9gxx/the_faas_plan_to_fix_air_traffic_875m_worth_of_ai/), [r/flying](https://www.reddit.com/r/flying/comments/1xvj54r/) and other aviation communities raise several useful questions. **These are anonymous, unverified accounts and opinions—not a survey of air traffic controllers, evidence of a SMART defect, or an FAA investigation.**

### A flight plan made weeks ahead can change minutes before departure

The FAA says SMART supports planning hours, days and even weeks in advance. But an [r/ATC commenter](https://www.reddit.com/r/ATC/comments/1swjava/comment/oig7pn1/) offered a practical counterpoint: flight crews may not know their pushback time accurately even 15–30 minutes ahead when deicing, taxiway congestion and other moving pieces interfere. These views are compatible rather than contradictory. Longer-range AI can help estimate capacity; *near-term operations still require continual replanning*. An important performance test is whether the system updates recommendations rapidly when its inputs stop matching reality.

### Does better traffic flow create more work in the cockpit?

In a [September discussion](https://www.reddit.com/r/ATC/comments/1wj9gxx/comment/paiawc1/), someone identifying as a major-airline first officer described another pilot repeatedly changing an aircraft's vertical-navigation settings to meet a precise arrival time, creating distraction around a crossing restriction. **There is no independent verification of the account or proof the flight was using SMART.** It nevertheless highlights a measurable risk for any time-based routing initiative: benefits for the network can be offset if pilots or dispatchers must make frequent, difficult adjustments. Operators should evaluate crew workload, compliance with altitude and speed restrictions, and the acceptance rate of proposed routes—not simply the theoretical minutes saved.

### Controllers want assistance, not another substitute for staffing

A recurring theme in [r/ATC's discussion of the $875 million program](https://www.reddit.com/r/ATC/comments/1wj9gxx/the_faas_plan_to_fix_air_traffic_875m_worth_of_ai/) is concern about staffing, overtime and whether new software improves conditions for controllers working live traffic. Those comments do not establish FAA-wide sentiment, but they point to a central deployment question: does AI reduce repetitive coordination and improve situational awareness **without assuming fewer trained controllers are needed**? For a vendor selling into safety-critical operations, adoption by frontline users may matter as much as forecasting accuracy.

### The 'floppy disks' headline hides several different technology systems

A [November r/ATC discussion](https://www.reddit.com/r/ATC/comments/1xtk0w3/ai_usage_in_atc/) cautioned against treating older floppy-disk-based information displays as evidence that all FAA radar systems run on floppy disks. The [FAA's E-IDS program](https://www.faa.gov/air_traffic/technology/eids) supports that distinction: it is replacing legacy **operational information displays** used for procedures, pilot reports, NOTAMs and other reference information—not replacing the ERAM and STARS aircraft-surveillance and separation tools. The FAA announced initial E-IDS deployments at five facilities on November 5 and targets **435 sites by the end of 2028**. E-IDS, SMART, safety-critical controller automation and the underlying communications network are related modernization projects, but they do different jobs.

### A national disruption tests information-sharing, too

During the November 13 ground stop, participants in [r/AirlinePilots](https://www.reddit.com/r/AirlinePilots/comments/1xvkkkg/faa_nationwide_ground_stop_megathread_discussion/) disagreed about whether the usual NAS status page adequately reflected the nationwide order. Those observations do **not** establish that an official status service malfunctioned, or why the ground stop happened. They highlight a different opportunity for aviation software: timely, consistent updates for controllers, airlines, pilots and travelers when a system-wide restriction changes.

The investment lesson is that **a persuasive aviation AI product needs more than a strong prediction model**. It must cope with stale data and rapidly changing constraints, integrate into cockpit and control-room workflows, make uncertainty visible, and preserve reliable human override and recovery.

## The hardest problem is earning trust

The economics of aviation AI depend on more than impressive predictions. Recommendations must be accurate, timely, explainable to trained operators, and safe to ignore or override. Bad data, poor integration or automation bias can undermine an otherwise useful system.

In October, U.S. lawmakers asked the FAA to pause SMART's Washington-area rollout while it explained safety testing, staff training and oversight. The National Air Traffic Controllers Association also told aviation media it had not participated in SMART's design, testing or implementation. Those concerns do not demonstrate that the software is unsafe, but they show why public test evidence and operator involvement matter.

The FAA's early reported fuel and time savings are promising. What would establish the long-term case is an independently understandable record of performance across severe weather, peak traffic, outages and ordinary operations — together with clear accountability when humans reject or accept a recommendation.

The wider modernization program adds another challenge: technology must operate alongside decades-old infrastructure while newer networking, data and controller systems are introduced. In September, the U.S. Government Accountability Office warned that the FAA's accelerated modernization effort needed stronger cost estimates and integrated schedule planning. The concern is execution, not proof that SMART itself is defective.

## What investors should watch next

The next meaningful milestones are not another AI demo. They are **repeatable operational results** across many regions, evidence of safe fallback procedures, the pace of FMDS integration, and whether the announced FAA contract turns into recognized revenue and durable software margins.

The opportunity is real: even modest improvements to airspace capacity and disruption recovery matter in a network handling thousands of flights a day. But investors should separate three milestones — **an AI recommendation shown to work, a government system adopted operationally, and a profitable software business**. They do not happen at the same time.

The FAA's SMART rollout suggests that AI in aviation is moving from airline experiments toward national infrastructure. The more consequential story is not an algorithm taking over a control tower. It is whether predictive software can help humans manage the world's busiest aviation networks without making those networks harder to understand, secure or recover.

**By:** [Venture Capital Tracker](https://venturecapitaltracker.com/editorial-policy)
**Last updated:** November 13, 2026

**Editorial note:** AI tools assisted with research, structure, or drafting. Venture Capital Tracker retains human editorial responsibility for factual accuracy, relevance, and source quality before publication.