Doximity posted $156.6 million in revenue for its fiscal 2027 first quarter on Thursday, beating Wall Street estimates by roughly $5 million, as the company bets heavily that hospitals - not individual doctors - will drive the next wave of AI adoption in healthcare. CEO Jeff Tangney told investors the company sees a "once-in-a-generation opportunity to build the new AI age of medicine" and is spending accordingly, with 165 health systems now signed as AI clients including Northwestern, Penn Medicine, and the University of Michigan.
Doximity offers a digital platform for U.S. medical professionals that includes telehealth, a clinician-to-patient dialer, and digital faxing. Its paying customers are pharmaceutical manufacturers, health systems, and medical recruiting firms. The company now aims to become a leading AI platform for doctors, scaling its clinical AI suite including the ambient notetaking tool Scribe and the AI assistant and search engine Ask.
Enterprise AI adoption shifts from individuals to hospitals
"We saw a shift somewhere early this year where it wasn't just individual decisions to go choose whatever AI I want to use. It became an enterprise decision," Tangney said on the earnings call. He expects the same shift in healthcare as hospitals get "rightfully concerned about the leakage of patient data and what's called PHI, protected health information, out to the broader internet."
Doximity shares rose 33% on Friday after the company's results, with the stock more than doubling in early overnight trading, according to CNBC. The company brought in net income of $24 million, down from $53 million a year ago, but raised its full-year revenue outlook to between $671 million and $681 million. CFO Matthew Sonefeldt attributed the earnings miss to "faster-than-expected" adoption of AI tools among clinicians, saying it was a "good problem" that creates near-term margin pressure.
Study: Doximity Ask ranked second in clinical safety
During the call, Tangney touted a study from ARISE, a clinical AI research team led by physicians at Stanford and Harvard Medical Schools, that evaluated 24 clinical AI models on 1,100 real-world patient cases. The study found that following unchecked LLM recommendations could cause severe harm in up to 24.6% of cases. Doximity's Ask product ranked second out of all tested models with a 4.8% error rate, trailing only AMBOSS AI Mode.
Tangney credited the results to Doximity's built-in drug reference and its 12,000-physician PeerCheck editors, who review AI outputs. "It's the kind of rigorous independent physician-led research that we need more of," he said. "These safeguards and quality checks are critical for hospital AI steering committees who could be held liable for their outputs and, therefore, care deeply about their accuracy."
Doximity sees strong utilization and pharma AI search interest
Quarterly active workflow prescribers grew more than 30% year-on-year to record highs, and nearly half of those prescribers used Doximity's AI tools in Q1. AI prompt volume was up more than 25% quarter-over-quarter, and the company's Scribe notetaking users grew tenfold from July 2023 to July 2024. Doximity launched an AI search product for pharma customers in April, onboarding its first cohort across more than two dozen programs, with revenue expected to build in the third quarter.
Tangney positioned the company as building a "digital assistant" for physicians that combines all of its offers into one place: "If you look at the leaders in the scribe market today, it's Microsoft. If you look at the leaders in clinical decision support, it's UpToDate. I think we're in a strong position here to be that combined doctor's digital system."
William Blair researchers said in a note that "monetization of AI offerings in 2026 should unlock a new multibillion addressable paid search market over time" and that Doximity can "remain a share gainer in healthcare professional marketing" with strong growth.
Why this matters for healthcare professionals
Hospitals are making enterprise-level decisions about which AI tools their staff can use, and safety and trust are becoming the determining factors. The ARISE study suggests that general-purpose regular LLMs may produce clinically dangerous output, but that specialized tools from vendors with medical domain expertise shown can achieve significantly lower error rates. For doctors, the implication is that Doximity's platform - including Scribe, Ask, telehealth, and peer-reviewed AI - may eventually act as a single certified, liability-managed tool chosen by their hospital, not one they pick on their own. AI for Healthcare has become a boardroom decision for them rather than a personal one.
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