Travel Through the Lens of AI with with Booking.com CEO Glenn Fogel
Glenn Fogel, CEO of Booking Holdings, discusses his 27-year journey from a struggling Priceline during the dot-com crash to a $130+ billion company, while reflecting on AI's transformative potential in travel, competitive moats, job displacement concerns, and the importance of meaningful work.
Summary
Glenn Fogel shares his unconventional career path, beginning with work in mainframe computing, investment banking, and trading before joining Priceline in 2000 just after the NASDAQ peak. He recounts how Priceline's stock plummeted from $30 billion market cap to a couple hundred million, trading at $1 per share, yet he remained with the company for 27 years as it grew over 1,000x in value. Fogel emphasizes that there is no such thing as a durable moat in business—competitive advantages can disappear, requiring constant innovation and customer focus to maintain long-term success.
Regarding AI's impact on travel, Fogel argues that AI is a beneficial tool rather than an existential threat to travel platforms. He describes Penny, Priceline's agentic AI system, which generates personalized travel itineraries by asking clarifying questions and managing complex multi-leg trips. While still at small scale relative to total transactions (186 billion dollars in travel annually), the tool demonstrates strong metrics in conversion lift, faster search paths, and lower cancellation rates. Fogel stresses that Booking's scale—8.6 million alternative accommodation listings and comparable room-night volumes to Airbnb—provides advantages, but these can be overcome through continuous innovation rather than serving as permanent protection.
Fogel addresses the AI investment strategy at Booking Holdings, noting approximately $700 million in annual AI and technology investments funded by cost savings. He emphasizes rigorous ROI analysis, including token economics, model selection, customer lifetime value, and loyalty metrics. The company has already reduced customer service costs per contact by 10% while improving satisfaction through AI-powered support.
On job displacement, Fogel acknowledges historical parallels with previous technological shifts (agrarian to industrial revolutions) but emphasizes the current speed of change is unprecedented and concerning. He cites the elimination of human translation jobs as AI-powered machine translation improved, and expresses concern about displaced workers like 50-something truck drivers who may struggle to retrain. Rather than relying on government retraining programs (which he views as largely ineffective), Fogel advocates for companies to invest in upskilling employees to become AI-literate and more productive. He warns against technology rejection driven by fear, noting that other countries like China are not hesitating to adopt AI, which could create competitive disadvantages.
Fogel reflects on life purpose and meaning, stating his mission is to make it easier for people to experience the world through travel, believing this improves quality of life and cross-cultural understanding. He urges people to choose careers wisely rather than defaulting to conventional paths, warning against the risk of mid-life regret for those who never pursued meaningful work.
About this episode
When Glenn Fogel joined Priceline in 2000, the business was worth a few hundred million dollars. One week later, the Nasdaq peaked, eventually sending its stock down to a dollar a share. But over 25 years later, Booking Holdings has scaled over 1000x into an over $100 billion dollar global travel behemoth. Elad Gil is joined by Booking Holdings CEO Glenn Fogel to discuss his career, from law school and Wall Street to working at Priceline through the dot-com crash, and to helping grow the business into a multifaceted, dynamic travel marketplace in the AI era. Glenn explains how leveraging AI and agents such as Priceline’s ‘Penny’ makes travel planning and customer service better, while emphasizing the importance of preserving some human support for some users. He also talks about Booking’s strategy of reinvesting over $700 million into AI and other technologies while still offering stock buybacks and dividends, the durability of their scale and complexities of dealing with a large portfolio physical properties across the world, and why upskilling is so important for employees amid concerns about AI-driven job displacement. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @bookingcom | @priceline Chapters: 00:00 – Cold Open 00:05 – Glenn Fogel Introduction 00:41 – Glenn’s Early Career 06:49 – Lessons from the Early Internet 09:24 – Deciding Factors for Exiting 10:56 – Travel Through the Lens of AI 13:30 – Agentic Travel Planning 18:59 – Agents, Token Economics, and ROI 22:46 – Booking’s Capital Investment Philosophy 25:23 – Scale as Durable Asset 29:40 – Purpose and Choosing Wisely 33:18 – AI’s Impact on Jobs 36:38 – Upskilling in the AI Era 38:36 – Public Perception of AI 40:24 – Conclusion
Key Insights
- Fogel argues that companies must abandon the concept of durable competitive moats because any advantage can be disrupted by innovation, requiring constant service development and customer focus to maintain long-term success.
- According to Fogel, agentic AI systems like Penny work best for complex travel scenarios where users retain decision-making authority while the AI handles permutations and logistics, rather than fully autonomous booking without user confirmation.
- Fogel claims that Booking Holdings' alternative accommodation business is approximately three-quarters the size of Airbnb by transaction volume, yet this scale advantage remains vulnerable to disruption and cannot be relied upon as permanent protection.
- Fogel states that the speed of job displacement caused by AI is unprecedented compared to previous technological revolutions, creating a mismatch between the rate of job disappearance and job creation that could cause social disruption.
- Fogel contends that government-sponsored retraining programs have largely failed over the past 50 years, and companies bear the responsibility to invest in upskilling employees to become AI-literate rather than waiting for policy solutions.
- Fogel asserts that rejection of AI technology based on fear would disadvantage Western societies relative to countries like China that are embracing AI without hesitation, potentially creating long-term competitive disadvantages.
- Fogel argues that many people default into careers (like law) for financial stability and social convention rather than pursuing meaningful work, leading to mid-life regret, and advocates for deliberate career choices aligned with personal values.
- Fogel claims that travel meaningfully improves human life by facilitating cross-cultural experiences and understanding, making the mission to simplify travel a contribution to society beyond mere profit generation.
Topics
Transcript
There is no such thing as a moat. There is no such thing as somewhere you're going to be protected against innovation. Today, we have a competitive advantage on areas. Absolutely. But those can go away tomorrow. The only way to run long-term is to continue to develop new services, new ways to do things. How can we do your business better? What do you need? Where do you need more demand? Where are you hurting? It's so much more complex if you think you're just going to come in and do this business and knock away these very big players I'd say you should really understand what this is before you decide to commit your capital today I know…
Full transcript available for MurmurCast members
Sign Up to AccessMore from No Priors: Artificial Intelligence | Technology | Startups
How Nuclear Will Unlock Energy Abundance with Valar Atomics Founder Isaiah Taylor
Isaiah Taylor, CEO of Valor Atomics, discusses how his company achieved the first nuclear power generation by a private startup through hardware iteration, simplicity-focused design, and organizational speed obsession. He argues nuclear energy's future depends on manufacturing-based scaling rather than design perfection, enabled by a regulatory environment that now allows experimentation through the Department of Energy pathway.
Re-engineering the Semiconductor Supply Chain with Intel CEO Lip Bu Tan
Intel CEO Lip Bu Tan discusses his strategy to transform Intel through cultural change, product simplification, foundry investment, and AI-driven demand. He shares his views on the semiconductor supply chain, government partnerships, and his venture capital philosophy built over decades of semiconductor investing.
The Rise of the Full-Stack Builder and Hyper-Leveraged Generalist with Microsoft CEO Satya Nadella
Microsoft CEO Satya Nadella discusses the company's AI ecosystem strategy at Build 2025, emphasizing that the goal is enabling every company to operate at the intelligence frontier with their own private models and evals. He covers topics ranging from MAI model training, agentic workflows, SaaS disruption, data center buildout, and societal impact of AI. Nadella argues that delivering tangible, broad economic benefits is essential for AI companies to maintain public trust and permission to operate.
Building an AI Guardian for Enterprise with Onyx Security CEO Maxim Bar Kogan
Maxim Bar Kogan, CEO of Onyx Security, discusses building AI agents to oversee other AI agents in enterprise environments. He explains how existing security tools are insufficient for governing autonomous agents, why Onyx trains specialized small models for this purpose, and why independent third-party oversight of AI is structurally necessary rather than something foundation model labs can solve themselves.
The Story Behind Cerebras’ $63 Billion IPO with Founder and CEO Andrew Feldman
Andrew Feldman, co-founder and CEO of Cerebras, discusses his company's journey from building wafer-scale AI chips in the mid-2010s to achieving a $63 billion market cap post-IPO. He covers the technical and market challenges of being ahead of demand, the pivotal OpenAI and AWS partnerships, and his views on how speed in AI inference will unlock entirely new business models rather than merely improving existing ones.