Show Notes
Airline distribution is sitting on decades of tech debt and AI might be the only thing that can fix it. Jim Hetzel is a travel and airline technology veteran who now leads retailing strategy at TWAI. In this conversation, he traces the full arc of airline distribution from fragmented pre-GDS ticketing to the NDC standards work and makes the case that AI is positioned to become the new orchestration layer the industry desperately needs. The discussion also explores the trust problem that no one in the AI agent era has solved yet: who plays the role of IATA when billions of bots are buying plane tickets?
What You'll Learn GDS origin: The Global Distribution System was built to solve a fragmentation problem giving travel sellers a single electronic marketplace instead of supplier-by-supplier chaos. NDC's limits: NDC is a messaging standard, not a retailing platform; airlines that want to become true retailers still need massive investments in CRM, personalization, and revenue management. Standards incompatibility: NDC versions are not backwards compatible with each other, which means early adopters face millions of dollars in re-implementation costs every major release cycle. AI as normalizer: AI can sit on top of both legacy GDS infrastructure and modern NDC standards simultaneously, acting as an intelligent interpreter rather than waiting for the industry to agree on a single format. Bot demand risk: AI shopping agents never stop checking, unlike human travelers, which means airline systems could face look-to-book ratios of one million to one, infrastructure costs that dwarf current GDS fees. Trust gap: IATA's historic role was to certify agents and airlines as legitimate counterparties; no equivalent trust and authentication layer exists yet for machine-to-machine AI agent transactions. Fare calculation art: Even today, skilled international pricing specialists can find fare combinations that GDS pricing engines miss and that variability, tolerance for imprecision, is baked into the industry by design. Intermediaries survive: AI doesn't kill intermediaries wholesale; it kills the weak ones. The players who solve orchestration, trust, and content normalization at scale will define the next generation of distribution.
Time-Stamped Highlights (00:00) Introduction and episode framing (00:21) Distribution before computers: fragmentation and the pre-GDS world (03:04) How the GDS created an electronic marketplace buffer (04:11) NDC: messaging standard vs. retailing platform (09:59) Why backwards incompatibility made NDC costly for early adopters (12:17) "A dumpster fire": the current state of airline distribution standards (15:25) Travel agencies caught supporting both GDS and NDC simultaneously (17:22) AI as the normalization layer across incompatible standards (22:21) Bot demand: look-to-book ratios and machine-generated traffic at scale (23:55) IATA's dual trust role and why AI agents have no equivalent (35:05) GDS pricing discrepancies: three systems, same itinerary, different fares (38:39) The "art" of international fare calculation and AI's opportunity there (40:25) Who builds the next trust and orchestration layer? (45:53) TWAI: modern retailing across GDS, NDC, and non-air content today
Guest Bio Jim Hetzel is a travel and airline technology executive with a career spanning corporate travel agencies to enterprise distribution platforms. He currently works at TWAI, a travel retailing technology company that enables airlines and travel sellers to offer multi-source content: GDS, NDC, hotels, car rental, activities through a unified platform. LinkedIn: https://www.linkedin.com/in/jhetzel/ | Company: https://twai.com
About the Podcast The Travel Tech Podcast features long-form conversations with leaders across travel and technology. The show explores how software, data, operations, and distribution come together in real businesses, with an emphasis on tradeoffs, incentives, and lessons that transfer beyond any single company
More from Travel Tech Podcast
An AI asked to protect every passenger connection gave a flawless answer: cancel the flights. Kevin Hightower is Chief Innovation Officer at Cirium, where he leads Propulsion Labs, the company’s innovation group. He and host Alex Brooker, former colleagues at Cirium, discuss Kevin’s path from oceanic air traffic control at Lockheed Martin to Google’s drone delivery program, how AI is changing product development and decision making in aviation, Cirium’s aviation knowledge graph, and the data interoperability problems holding the industry back. What You’ll Learn Automating the routine: Lockheed’s oceanic ATC system let controllers comfortably manage 30 aircraft instead of a busy 7 to 15 by automating conformance checks and altitude probes. The three hour rule: No decision, from buying a car to buying a company, should need more than three hours of actual thought, with data gathering kept separate from thinking. Disposable prototypes: When AI cuts build time from months to days, the discipline shifts to throwing work away instead of defending ideas because of the effort already spent. AI as an accelerant for learning: Early career engineers who use AI to compress years of learning will outpace those who use it only to do an old job faster. Decisions, not dashboards: Most aviation decisions run roughly eight steps, and AI can now carry four or five of them before a human makes the call. The aviation knowledge graph: Aviation data starts with an aircraft and links orders, lessors, schedules, and tail swaps, so connecting it unlocks analysis no single dataset can. Efficiency before safety: AI will speed up flow management and sequencing well before it touches the safety critical systems that keep aircraft separated. The interoperability gap: Multi year, multi million dollar data lake programs rarely deliver usable value, and the real problem is combining data across boundaries while keeping control of it. Time-Stamped Highlights (0:00) Cold open: the AI that cancelled the flights (2:04) A Cessna ride to Embry-Riddle (4:48) "Do you want to kill people or save people?" Choosing air traffic control (6:26) Replacing paper strips over the Pacific (9:17) From Lockheed CTO to a quarter million drone deliveries (13:10) Why there's no one right way to be a product manager (16:22) The three hour decision rule (22:03) Formal testing in five minutes, not a few months (24:42) Fail fast, then fly everyone to Hawaii (32:39) Powering every decision connected to aviation (34:40) Behind the dip: analyzing every turn instead of one (47:17) Why nobody can predict the Charlotte arrival sequence (48:36) Could AI make travel worse for passengers? (54:09) Data interoperability and the $10 million data lake
AI made writing code nearly free, which only matters if code was ever most of the job. In this compilation episode, host Alex Brooker pulls together clips from seven past guests across travel software, airspace infrastructure, airline operations, corporate travel, content, and airline ancillaries who each arrived at the same idea independently. Alex Ragin of Zoftify puts a number on it: code is about 20% of a software product, and the other 80% is domain knowledge, process, and judgment. The episode follows that 80% through edge cases, daily operational disruption, fare construction expertise, and the question of what a product team's job becomes when execution costs almost nothing. What You'll Learn The 20/80 split: Code is roughly 20% of a complex travel system, and the remaining 80% is knowledge of how the business actually works. Vibe coding limits: A simple invoicing app can be vibe coded, but a CRM, ERP, or GDS cannot, because the hard part is specifying behavior rather than writing it. Edge case cost: One modest custom fields feature at Zoftify took about five days of internal and client discussion before it was ready to build. Failure at the seams: Complex systems break at their interfaces and edge cases, not on the happy paths that teams test and load test. No standard day: In airline operations, disruption from weather, aircraft swaps, or system faults is the normal state rather than the exception. Expertise outside the code: International fare specialists routinely beat GDS pricing engines by thousands of dollars by knowing where to break a fare. Where value moves: As development costs approach zero, advantage shifts to network effects, knowledge of customer pain, and position in the customer journey. The new job: When execution is cheap, deciding what to build and why becomes the core work for every team, not just well funded ones.
Two euros can decide who wins a metasearch sale. Inside most airlines, moving them is still revenue management's call, and it is rarely fast.
Everyone is racing to build the AI agent that books your trip, and nobody is building the thing that makes it safe to use one.
A guy who used to hand carry passports to airport cargo terminals just built the database he couldn't afford in 2018 for a fraction of the cost, and every application still passes through a human before it goes anywhere. Rob Lee is CEO and co-founder of Swift Passport and Visa Services, a company he started in 2008 helping private aviation clients navigate passport and visa logistics. In this conversation, Rob traces the industry from same day passport courier runs through the shift to eVisas and ETAs, and explains why his team uses AI heavily to build internal tooling while keeping customer data out of public AI tools and a human check on every application.