2 Artificial Intelligence (AI) Stocks With Millionaire-Making Potential That Wall Street Is Overlooking

Airbnb posted $91B in gross booking value in 2025 and its stock sits ~40% below five-year highs as the company tests AI-driven, conversational search and hired AI researcher Ahmad Al-Dahle as CTO to improve discovery and personalization. Oscar Health recorded an operating loss near $400M in 2025 but launched an OpenAI-powered chatbot 'Oswell' and targets operating income of $250M–$450M after repriced plans. Both companies are positioned to use embedded AI to enhance the customer journey and monetization, and the article frames them as undervalued, long-term AI-enabled growth opportunities.

Analysis

Embedding conversational AI into two-sided consumer platforms creates asymmetric optionality: a modest lift in conversion or reduced time-to-purchase on the demand side compounds through higher utilization on the supply side, turning fixed-cost distribution into durable margin expansion. For a marketplace, a 5–10% increase in conversion can translate to a 15–30% uplift in incremental EBITDA over 12–24 months because incremental bookings have minimal incremental SG&A and enable higher take-rates via bundling (experiences, insurance, concierge).

Second-order supply effects matter: better discovery shifts selection toward higher-margin, professionally managed inventory while pressuring mom-and-pop suppliers to standardize or exit; this reduces variability of unit economics but raises capital requirements for hosts who must invest to meet new quality signals, potentially accelerating consolidation into professionally managed portfolios. Independent hoteliers and legacy OTAs will respond with faster metadata standardization, loyalty bundling, and search ergonomics — a battle that favors platforms with native listing-level data and first-party payments.

Key risk vectors are operationalization cost and trust: inference compute and latency for high-quality conversational search is non-trivial and will push incremental capex/opex to cloud/GPU suppliers, while in healthcare the regulatory/clinical-trust curve can blunt adoption or create liability if AI triage fails. Practical catalysts are measurable: conversion rate lift, average booking value, professional-host share (travel) and medical-loss-ratio, member retention (health) over the next 6–24 months; negative surprises on any of these can erase premium multiple expansion quickly.

Key Decisions for Investors

• Long ABNB equity (12–24 month horizon): accumulate on weakness with a target position size of 2–3% of risk budget. Thesis: 20–30% upside if AI-driven conversion and professional-host share increase take-rate by 50–100bps; tail risk is platform regulation or slower host supply response. Hedge: buy 9–12 month protective puts at ~30% OTM to limit near-term downside while capturing long optionality.
• Long OSCR with downside protection (18–36 month horizon): buy shares and fund by selling near-term covered calls or implement a collar (buy 18–24 month LEAP calls and sell 6–9 month calls). Thesis: AI triage reduces per-member medical spend and improves retention; payoff asymmetric if underwriting normalizes. Key risk: medical-loss ratio re-acceleration; maintain stop if quarterly MLR does not trend down within 3 consecutive quarters.
• Reduce directional NVDA exposure and monetize volatility (3–9 month horizon): sell near-dated call spreads or sell covered calls against part of exposure. Rationale: short-term expectations for enterprise inference capex are priced aggressively; realize premium while keeping convex upside from longer-term data-center secular growth. Risk: large upside from beat-and-raise datacenter bookings — cap position size to 1–2% of portfolio.
• Event triggers & monitoring: set data-driven alerts—ABNB: weekly conversion and professional-host %; OSCR: monthly medical-loss-ratio and enrollment trends; NVDA: datacenter billings and customer cadence—for tactical position adjustments within 30–90 day windows.