Oliver Karaz

CEO of ZocDoc

Claims

As speaker

Mentioned in

Key positions and views

Real-world operational experience is a more durable competitive advantage ('moat') against new AI entrants than technology alone, a concept he calls the 'Coast of England problem.' [15, 17, 20]

In the emerging AI agent economy, essential service providers (like ZocDoc, Uber) have significant negotiating power over foundational AI platforms, a reversal of the dynamic they had with Google's search monopoly. [14, 19]

A controlled, deterministic AI architecture that selectively uses LLMs is superior for high-stakes applications like healthcare scheduling because it ensures accountability and allows for graceful escalation to human agents. [3, 11]

AI will primarily augment the healthcare industry by replacing 'Dr. Google' for patient self-research, but it will not make doctors obsolete in the foreseeable future due to the physical and complex nature of medicine. [1, 8, 21]

ZocDoc's growth was fundamentally unlocked by shifting its business model from a flat provider subscription to a transactional, per-booking fee, which better aligned the company's success with its customers' success. [7, 9]

Podcast consensus on Karaz

Points of consensus

▶Both sources report Karaz's prediction that "Dr. AI" will replace "Dr. Google" for initial patient self-research and guidance, with patients learning to discern when to seek human medical judgment. [1, 8]Apr 2026

▶Karaz consistently claims that service providers with real-world integration, like ZocDoc, Uber, and Airbnb, have significant negotiating leverage over the competing major AI agent platforms, a dynamic that didn't exist with Google's search monopoly. [14, 19]Apr 2026

▶Across both interviews, Karaz asserts that ZocDoc's competitive moat is its deep, multi-year experience in solving the complex, real-world operational challenges of healthcare scheduling, which he refers to as the "anthropology problem" or the "Coast of England problem." [15, 20]Apr 2026

▶Karaz's claim that ZocDoc's AI scheduling agent achieves a ~52% conversion rate, outperforming competitors (below 40%) and average humans (high 40s), is mentioned in both podcast appearances. [5, 24]Apr 2026

Points of debate

▶Karaz presents a nuanced view on AI vs. human performance, highlighting that while ZocDoc's AI (52% conversion) outperforms average humans (high 40s), it is still significantly less effective than the best-performing human agents (65%). [4, 5, 23, 24]Apr 2026

▶There is a tension in Karaz's predictions for AI in medicine: he forecasts "Dr. AI" will become the primary tool for patient self-guidance [1, 8], yet he also firmly believes medicine will be one of the last professions to be made obsolete by AGI due to the need for physical examination. [21]Apr 2026

▶Karaz advocates for a specific AI architecture, emphasizing ZocDoc's use of a "deterministic orchestration layer" that selectively employs LLMs. This contrasts with a pure, open-ended LLM approach, suggesting a debate on the right balance between control and capability for high-stakes applications. [3, 11]Apr 2026

▶While Karaz is bullish on AI for scheduling and patient research, he is skeptical about near-term AGI, citing OpenAI's Sora as evidence that the industry is "many, many years away" from achieving it. [16]Apr 2026

Key themes

▶The 'Real-World' Moat Against Pure AIApr 2026

Karaz argues that ZocDoc's sustainable competitive advantage lies not in its AI technology alone, but in its two decades of experience navigating the complex, real-world workflows of medical practices. He terms this the "anthropology problem" or the "Coast of England problem," suggesting that this deep operational knowledge is difficult for new, purely digital AI agents to replicate. [15, 17, 20]

This theme suggests that investors should value companies that combine AI with deep, domain-specific operational expertise, as this integration creates a more defensible moat than a purely technological one.

▶Strategic Business Model TransformationApr 2026

A key element of ZocDoc's success, as described by Karaz, was a fundamental shift in its business model. The company moved from a flat subscription fee for doctors to a per-patient booking fee, which he claims "unlocked significant growth" and led to an "order of magnitude" increase in the number of providers on the platform. [7, 9]

This highlights the critical importance of aligning a platform's business model with value creation for its users; the move to a transactional model directly tied ZocDoc's revenue to its ability to deliver patients, accelerating network effects.

▶AI as a Controlled Augmentation, Not a ReplacementApr 2026

Karaz details a cautious and controlled approach to AI implementation. ZocDoc uses a "deterministic orchestration layer" to manage its AI agent, selectively using LLMs for specific tasks like parsing patient answers, while maintaining the ability to escalate to humans. This philosophy extends to his view that AI will replace "Dr. Google" for self-research but not the diagnostic and physical role of a doctor. [1, 3, 8, 11, 21]

Karaz's strategy indicates a belief that in high-stakes fields like healthcare, the most successful AI applications will be those that prioritize reliability, control, and human oversight over pure generative capability.

▶Shifting Power Dynamics in the AI EconomyApr 2026

Karaz posits that the rise of competing AI agent platforms (the "five major LLMs") creates a new power dynamic. Unlike the era of Google's search monopoly, essential real-world service providers like ZocDoc, Uber, and Airbnb now hold significant negotiating leverage because no single AI agent can afford to lack access to their services. [14, 19]

This perspective suggests a future where value in the AI ecosystem may consolidate not just with foundational model creators, but also with indispensable service platforms that control access to real-world actions and inventory.

Source episodes

Timeline

Early Operational Phase

Karaz describes an intensive early period where ZocDoc spent four years focused solely on New York City to master the complex "anthropology problem" of real-world medical practice workflows before expanding. [15]

Business Model Transition

Karaz led ZocDoc through a major business model change, pivoting from a flat subscription fee for doctors to a per-patient booking fee model. [9]

Post-Transition Growth

Following the business model change, Karaz states the company experienced an "order of magnitude" increase in the number of doctors on its platform, indicating a period of rapid scaling. [7]

Present AI Era

Karaz is currently focused on integrating AI into ZocDoc's services, having released an autonomous AI phone scheduling agent named "Zo" and architecting systems with a deterministic, controlled approach to using LLMs. [3, 10, 11, 18]

Suggested prompts

How does Karaz's "Coast of England problem" analogy for competitive moats apply to other industries being disrupted by AI, such as logistics or finance? &nearr;What are the potential regulatory and liability challenges for ZocDoc as its "Dr. AI" concept evolves, despite its stated policy of not giving medical advice? &nearr;Analyze the strategic trade-offs in ZocDoc's decision to use a "deterministic orchestration layer" for its AI rather than relying purely on more powerful, but less predictable, LLMs. &nearr;Evaluate Karaz's claim that service providers like ZocDoc and Uber hold significant leverage over the "five major" AI agent platforms. What factors could strengthen or weaken this position over time? &nearr;

Key concepts

AI in Healthcare 2 ep ZocDoc Business Model 1 ep Competitive Moat 2 ep Conversion Rates 2 ep Dr. AI vs. Dr. Google 2 ep AI Agent Platforms 2 ep Service Provider Leverage 2 ep Deterministic Orchestration 2 ep Anthropology Problem / Coast of England Problem 1 ep

Notable quotes

“because of that learning curve, because of all the edge cases, all these things. even if the AIs were to start learning about them, we're so much further ahead. We can always deliver a better experience. So this is the Coast of England problem. Our cartographers have been at this for 20 years. There is no way that anyone would catch up to us anytime soon.”

Oliver Karaz · Decoder Podcast Live! Host Nilay Patel interviews CEO of ZocDoc, Oliver Kharraz

“There's five major LLMs or AI companies that are competing to be your agent... the providers of these services actually have a lot of leverage right now to negotiate the kinds of relationship with these AI agents that they never had with Google, because Google was already the monopolist when they came up.”

Oliver Karaz · Decoder Podcast Live! Host Nilay Patel interviews CEO of ZocDoc, Oliver Kharraz

“dr google is going to be replaced by dr ai and the patient will develop their own judgment”

Oliver Karaz · Decoder Podcast Live! Host Nilay Patel interviews CEO of ZocDoc, Oliver Kharraz

“we literally we did not leave New York for four years just to make sure that we get even to a base level of this functioning because there are there is the technology problem of integrating with all these ehrs but then there's an anthropology problem on top of this”

Oliver Karaz · Zocdoc CEO Oliver Kharraz on AI in healthcare | Decoder

Report last updated: Apr 21, 2026

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