Doximity (DOCS) Q2 2027 Earnings Call Transcript

Doximity reported Q2 revenue of $174.5 million, up 4% year over year and 2 percentage points above the high end of guidance; adjusted EBITDA was $88.9 million at a 51% margin, 9 percentage points above guidance. Management raised FY2027 revenue guidance to $678 million–$683 million and adjusted EBITDA guidance to $317 million–$325 million, citing Q2 outperformance and growing AI-search demand; 16 of the top 20 pharmaceutical companies have purchased AI Search, now an eight-figure bookings product. Active workflow prescribers grew 34% to about 900,000, while the company repurchased $54 million of shares. Risks include a 2.3% error rate in a study of AI drug-dose queries, with 40% of errors classified as serious or potentially lethal, and lengthy medical-legal reviews that may delay AI-search revenue.

Analysis

DOCS has a credible distribution-to-monetization pathway, but the near-term debate is conversion, not clinician adoption. Workflow engagement can strengthen pharma targeting and health-system retention; however, pharma search bookings are not yet evidence of durable incremental revenue. MLR review pushes conversion out by months, while an auction model may broaden smaller-account access only after product and sales execution are proven. The key 1–3 month catalyst is the year-end pharma upfront cycle and February update; the 6–18 month test is whether AI Search lifts growth and NRR without structurally eroding gross margin. Current 103% overall NRR and modest revenue growth leave little room for execution slippage despite raised guidance.

The second-order winner may be WKL: licensed UpToDate content could become more valuable as health systems demand governed, source-grounded clinical AI. But commercial upside depends on partnership economics and measurable customer adoption, neither established here. GOOG faces a possible share-of-budget headwind if pharma reallocates paid-search spend, but the cited survey and early adoption do not establish material displacement; its diversified revenue base makes a direct short thesis weak.

DOCS’s safety and security positioning could benefit from tighter hospital AI governance, but the disclosed dosing-error study also exposes a liability and trust tail risk. Verify independent validation, incident handling, and security controls. Margin expansion from inference efficiency is encouraging, yet gross-margin compression and high SBC temper the quality of headline EBITDA and buyback-driven share reduction. A cautious, catalyst-gated DOCS long is preferable to chasing the earnings reaction; valuation and post-call price action are needed before sizing. Falsifiers: weaker upfront bookings, delayed MLR launches, NRR deterioration, or AI costs again growing in line with usage.

Key Decisions for Investors

• DOCS: Avoid chasing the initial earnings move. Consider a staged long only after reviewing price/valuation and the year-end upfront cycle; February disclosure should show bookings converting to launch schedules and revenue, not just customer interest.
• Track DOCS gross margin, AI cost growth versus usage, and overall NRR over the next two quarters. Reassess the long thesis if NRR slips below current levels or AI unit-cost leverage reverses as engagement scales.
• WKL: Treat the partnership as strategic optionality, not a near-term earnings estimate. Verify revenue-sharing or licensing economics and evidence that UpToDate access is driving paid DOCS adoption before making a standalone position.
• GOOG: Do not short on this evidence alone. Monitor independent pharma budget data and DOCS auction-product adoption for demonstrated paid-search substitution; the reported survey is an early signal, not proof of meaningful revenue displacement.