3 Takeaways:
- Policy-Technology Disconnect: The U.S. Transportation Department wants to add gyms to airports, but surveys show travelers want less time at airports—not more amenities to fill waiting time.
- AI is Eliminating Airport Uncertainty: Predictive technology (real-time traffic, security wait times, biometric screening) enables just-in-time arrival, undermining the business model of airport retail built around forced 2-3 hour waits.
- System Redesign vs. Point Solutions: Adding gyms is like installing steam pipes in factories that should be redesigned around electricity—we need airports designed for 30-minute arrivals, not better ways to spend 3 hours waiting.
Introduction: Policy Out of Touch
U.S. Transportation Secretary Sean P. Duffy has a vision for American airports: fitness facilities where travelers can work out while waiting for their flights. In his “Make Travel Family Friendly Again” campaign, adding gyms to major airports like DCA features prominently. The logic seems straightforward. Americans spend hours at airports anyway, so why not let them burn some calories?
“I want a workout area where people might get some blood flowing and doing some pull-ups or some step-ups in the airport,” said Duffy during the press conference.
There’s just one problem. Americans don’t want to spend hours at airports anymore.
According to a 2025 survey conducted by the U.S. Travel Association and Ipsos, American travelers are demanding something entirely different—more modern, streamlined experiences at domestic airports. They’re not asking for spas, museums, or gyms to fill the waiting time. They want less time at airports altogether.
This isn’t a minor policy disagreement. It reveals a fundamental misalignment between three powerful forces moving at different speeds: what people actually want, what technology can now deliver, and what policymakers are choosing to implement. The airport gym proposal isn’t just tone-deaf. It’s a symptom of a system trapped in an outdated paradigm while the future arrives around it.
The Three-Way Disconnect
What People Want: The Streamlined Experience
The survey data paints a clear picture. When Americans describe their ideal airport experience, they don’t mention a lack of amenities. They talk about unnecessary friction:
- Security delays that remain unpredictable despite technological advances
- Confusing processes that vary wildly from airport to airport
- Wasted time buffers that force early arrival “just in case”
- Technology gaps where digital tools promise efficiency but fail to deliver
The modern traveler doesn’t dream of arriving three hours early to squeeze in a workout at the airport gym. They dream of arriving 45 minutes before their flight with confidence, breezing through security in minutes, and boarding without stress. They want precision, not more ways to endure the imprecision.
This represents a sea change in consumer values. Previous generations might have viewed airports as destinations in themselves—places to shop, dine, and while away the hours. Today’s travelers, raised on Uber’s real-time tracking and Amazon’s same-day delivery, see airports differently. They’re obstacles to minimize, not experiences to extend. The airport isn’t the destination. It’s the frustrating barrier between them and where they actually want to be.
Economist George Stigler captured this perfectly decades ago: “If you never missed the plane, you’re spending too much time in airports.” What felt like provocative wisdom then is becoming operational reality now.
What Technology Enables: The End of Uncertainty
Meanwhile, artificial intelligence and predictive technology are quietly dismantling the very foundation that modern airports were built on.
In their influential book Power and Prediction, economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb use airports as a case study for understanding how AI reshapes entire industries. Their argument is both elegant and devastating for current airport business models.
The Core Insight: Modern airports are elaborate, expensive infrastructures built entirely around uncertainty. Think about why you arrive three hours before an international flight:
- You can’t predict traffic conditions with certainty
- Security line length is a complete unknown until you arrive
- Parking availability is anyone’s guess
- Check-in and baggage processes have wildly variable wait times
Because of this uncertainty, you build in a massive time buffer. And because millions of passengers build in massive time buffers, airports have evolved into shopping malls with runways attached. The shops, restaurants, spas, lounges, and now proposed gyms don’t exist because travelers want them. They exist to monetize your forced waiting time.
The Private Terminal Contrast
The authors make this point vivid by comparing commercial airports to private terminals. Walk into a private aviation terminal and you’ll notice something striking: sparse, minimal facilities. No elaborate food courts. No shopping centers. No spas. Certainly no gyms.
Why? Because there’s no uncertainty. The plane doesn’t leave until you arrive. There’s no security line. Parking is steps away. When there’s no need for a buffer, there’s no need for infrastructure to make the buffer bearable.
How AI Changes Everything
AI-powered prediction is now bringing private terminal certainty to commercial aviation:
- Real-time traffic prediction from Google Maps and Waze tells you exactly when to leave
- TSA PreCheck and CLEAR provide predictable security timing
- Mobile apps deliver live security wait times down to the minute
- Dynamic parking systems show real-time availability
- Digital boarding passes and bag tags eliminate check-in uncertainty
- Biometric screening promises walk-through security without stopping
Each improvement reduces uncertainty. Each reduction chips away at the rationale for arriving hours early. And each minute of reduced terminal dwell time undermines the business model of airport retail.
The implications run deep. As prediction accuracy improves—and it’s improving exponentially—the entire “scaffolding” of amenities becomes obsolete. The $4 billion airport retail industry isn’t built on what travelers want. It’s built on what travelers are forced to endure.
As the authors explain, this shift moves power from physical systems designed to manage uncertainty to data-driven insights that eliminate it. The question isn’t whether this transformation will happen. It’s who will control it and who will resist it.
The Power and Prediction Framework: Understanding System-Level Transformation
To fully understand why the airport gym proposal represents backward thinking, we need to dig into Agrawal, Gans, and Goldfarb’s deeper argument about how AI transforms systems.
Point Solutions vs. System Solutions
The authors draw a crucial distinction between two types of AI implementation:
Point Solutions: Using AI to marginally improve one component of an existing system while leaving the overall structure intact. It’s like using computers to make typewriters more efficient rather than recognizing that computers eliminate the need for typewriters altogether.
In airports, point solutions look like:
- AI-powered cameras to monitor security lines (while keeping the line structure)
- Predictive models for staffing levels (while maintaining unpredictable processes)
- Chatbots to help passengers navigate (instead of redesigning so navigation isn’t needed)
System Solutions: Using AI to redesign the entire system from first principles, eliminating the need for complex accommodations built around uncertainty.
True system solutions for airports would include:
- Biometric screening that eliminates traditional security lines entirely
- Risk-based, predictive security that identifies threats before people reach the airport
- Just-in-time arrival systems where passengers confidently arrive 30 minutes before departure
- Complete redesign of airport layouts around throughput rather than dwell time
Why This Misalignment Persists: The Political Economy of Disruption
Understanding why this disconnect continues requires examining who wins and loses when systems transform.
The Winners from Uncertainty
The current airport model generates significant economic value for specific stakeholders:
- Airport retail operators pull in billions annually from captive audiences
- Airport authorities collect substantial rent from concessionaires
- Airlines benefit from airport revenue that subsidizes operations
- Construction companies profit from building and maintaining elaborate terminals
- Food service companies enjoy guaranteed high-traffic locations
These stakeholders have resources, organization, and political influence. They can cite specific job numbers, tax revenues, and economic impact studies. They have a seat at the table when policy gets made.
The Diffuse Losers
Travelers bear the costs:
- Time wasted arriving unnecessarily early (multiplied by millions of passengers)
- Stress from unpredictable security processes
- Higher ticket prices as airlines pass through facility costs
- Reduced productivity from hours lost in transit
But these costs are distributed across millions of individuals. Nobody organizes around “airport efficiency advocacy.” The pain is real but politically diffuse. Travelers don’t have a lobbying arm. They just complain on Twitter and then buy their tickets anyway.
The Innovator’s Dilemma in Policy
This creates a textbook collective action problem. The benefits of transformation accrue broadly to everyone (slightly), while the costs concentrate intensely on specific groups (significantly). Political systems naturally favor organized, concentrated interests over diffuse public benefits.
Policy makers also face asymmetric risks:
- Risk of innovation: Push for system redesign and something goes wrong? You’re blamed for the disruption. Every security breach or delay becomes “your fault for changing the system.”
- Risk of status quo: Maintain the current system? Nobody specifically blames you for slow progress. The frustration remains ambient, unattributed.
This creates a powerful bias toward visible, incremental additions (gyms) rather than invisible, transformational redesign (eliminating the need for three-hour airport visits).
What a Technology-First Policy Would Actually Look Like
What if we designed airport policy around what technology enables and what people want, rather than around preserving existing business models? Here’s what we’d prioritize:
Immediate Term: Reducing Uncertainty
1. Universal Real-Time Information
- Mandate live wait time data for security, customs, and all airport services
- Standardize APIs so third-party apps can provide accurate arrival timing
- Create accountability metrics for prediction accuracy (airports should be judged on how well their predictions match reality)
2. Biometric Expansion
- Accelerate deployment of facial recognition and biometric screening across all major airports
- Enable true “walk-through” security for pre-vetted travelers—no stopping, no bins, no shoes off
- Integrate biometrics seamlessly across check-in, bag drop, security, and boarding
3. Process Standardization
- Eliminate airport-to-airport variation in security procedures (TSA rules shouldn’t depend on which airport you’re in)
- Create predictable, technology-enabled experiences that work the same way nationwide
- Design systems around digital-first travelers, not as afterthoughts to physical processes
Medium Term: Infrastructure Rightsizing
4. Adaptive Terminal Design
- Design new terminals explicitly assuming reduced dwell time
- Create flexible spaces that can shrink commercial areas as needed without creating dead zones
- Focus on throughput efficiency over capacity for waiting
5. Risk-Based Security Evolution
- Move toward continuous, predictive security assessment rather than checkpoint bottlenecks
- Reduce blanket screening in favor of intelligence-driven approaches
- Partner with AI companies to pioneer new security paradigms instead of just improving the old ones
Long Term: System Redesign
6. The 30-Minute Airport
- Reimagine airport design around confident just-in-time arrival
- Restructure business models away from captive audience retail toward service-based revenue
- Create airports that are efficient transport nodes, not destinations in themselves
7. Distributed Security Screening
- Enable remote, pre-travel security verification (possibly even at home)
- Reduce airport screening to verification rather than discovery
- Use AI to continuously assess and update risk profiles so airport security becomes confirmation, not investigation
8. Integration with Broader Travel Ecosystem
- Coordinate seamlessly with rideshare, parking, and ground transportation
- Create truly predictable door-to-gate experiences
- Use AI to optimize the entire journey, not just the airport components in isolation
The Broader Lesson: Recognizing Paradigm Shifts
The airport gym proposal is a microcosm of a larger pattern visible across industries and policy domains: institutions optimizing for a world that’s already disappearing.
Similar misalignments are playing out in:
- Education: Adding tablets to traditional classrooms rather than reimagining learning around AI tutors that adapt to each student
- Healthcare: Digitizing existing workflows rather than redesigning care delivery around continuous monitoring and predictive intervention
- Transportation: Adding EV charging stations to existing infrastructure rather than rethinking urban design around autonomous vehicles
- Finance: Regulating cryptocurrency like traditional banking rather than creating frameworks for genuinely decentralized finance
In each case, policy makers ask “how do we make the current system better?” when they should be asking “do the assumptions underlying the current system still hold?”
It’s the difference between improving horse-and-buggy infrastructure in 1910 and recognizing that automobiles require completely different roads, regulations, and urban planning.
The Questions Policy Should Be Asking
Instead of “should we add gyms to airports?”, policy makers should be asking:
- What problem are we actually solving? (Passenger frustration with wasted time, not insufficient exercise opportunities)
- What does enabling technology make possible that wasn’t before? (Near-certain arrival timing, not better ways to fill uncertain waiting periods)
- What do our constituents actually want? (Streamlined experiences that respect their time, not more amenities to occupy forced waiting)
- Who benefits from the status quo, and who’s disadvantaged? (Concessionaires benefit; travelers lose)
- What does the future look like if we succeed? (Empty terminal retail space and frustrated landlords, not well-used gyms)
That last question is the hardest one to face. Success means disrupting powerful, organized constituencies. It means acknowledging that billions in airport retail infrastructure may become obsolete. It means confronting the reality that good policy might look like failure to the stakeholders who have the most political influence.
Conclusion: Building for the Future That’s Coming, Not the Past That’s Comfortable
The airport gym proposal will likely move forward. Stakeholders will lobby for it. Politicians will tout it as progress. Some travelers might even use the facilities. In isolation, it’s harmless—even marginally positive.
But symbolically, it represents something more troubling: policy paralysis in the face of paradigm shift.
We’re at a pivotal moment. AI and predictive technology are offering us a genuine opportunity to reimagine core infrastructure around reduced uncertainty, improved efficiency, and better alignment with what people actually want. We could have airports where travelers arrive with confidence 30-45 minutes before domestic flights, pass through near-invisible security, and board efficiently. We could convert massive terminal retail spaces into flexible, high-throughput designs optimized for movement, not monetization.
Instead, we’re proposing to add pull-up bars.
The gap between what technology enables, what people want, and what policy delivers isn’t inevitable. It’s a choice. A choice to prioritize visible additions over invisible transformation. Organized interests over diffuse benefits. Comfortable incrementalism over disruptive redesign. Photo opportunities over actual progress.
The question isn’t whether AI will eventually transform airports. It will. The economics are too compelling, the technology too powerful, the consumer demand too clear. The real question is whether we’ll lead that transformation thoughtfully and deliberately, or whether we’ll continue investing in elaborate scaffolding even as the foundation crumbles beneath it.
The next time you find yourself at an airport gym (if we build them), ask yourself: Would I rather be here, or already at my destination?
The answer tells you everything about what policy should be prioritizing. And what it currently isn’t. ✈️
