# Ahmed Omar

Ahmed Omar writes about how healthcare AI can improve health system finances and day-to-day work, with a focus on administrative costs, clinician retention, and measuring whether tools save staff time.

- Profile: https://b2binfluencer.marketing/creators/ahmed-omar/
- LinkedIn: https://www.linkedin.com/in/ao7
- LinkedIn followers: 28,930
- Topics: artificial-intelligence, healthcare
- Based on 14 dated posts, latest 2026-10-02

## Summary

Ahmed Omar is most useful for concise arguments on healthcare AI ROI, administrative work, and clinician retention.

- Best for: A healthcare AI vendor selling prior-authorisation, intake, or coding automation to US health systems.
- Not for: A physician recruiting or staffing marketplace promoting placement services to health system workforce leaders.
- Check first: Confirm whether they take sponsorships or paid collaborations and ask for audience demographics.

### Takeaways

- Hospitals adopt AI that makes them money before AI that saves society money.
- Prior authorization is clinical wages paid for clerical work.
- Retention is cheaper than recruiting and is the only option that scales.

## Main ideas

- **Hospitals buy the AI that makes them money before the AI that saves society money**: Omar takes a line from Taha Kass-Hout — "Hospitals will adopt the AI that makes them more money. The AI that saves society money is a different product" — and works out why. The revenue-generating AI does more of what a health system already bills for, faster and with the same staff: more calls answered means more appointments scheduled, fewer prior-authorization delays means fewer denied claims, lower administrative turnover means lower recruiting cost. That case, they write, fits on one slide. The society-saving AI is a different business — it avoids unnecessary procedures, catches overdiagnosis, flags overtreatment, and steers patients toward cheaper sites of care — and none of that is rewarded when hospitals are paid per procedure. They conclude with a sequence rather than a complaint: build the revenue AI first because that is what gets deployed, and treat the data and trust it generates as what makes the less profitable AI possible later.
- **Prior authorization is clinical wages paid for clerical work**: Omar sets out the prior-authorization burden as a cost problem with a second, worse symptom. Clinical staff spend 7 to 14 days on each authorization, across thousands a month, so every one of those hours is clinical wages paying for clerical work. The cost then resurfaces in turnover: prior authorization is, in their framing, the top reason doctors say they are done, and a burned-out physician costs roughly $500,000 to replace. The fastest return, they argue, is not a clinical model but taking administrative work off the people a system cannot afford to lose.
- **Retention is cheaper than recruiting, and it is the only option that scales**: Omar opens a post on attrition by calling it a health system's most expensive line item and noting that it is climbing. Nearly one in ten surgeons leaves clinical practice within eight years, and each departure can cost around $500,000 to replace before counting the revenue that goes with them. Recruitment cannot close that gap fast enough because the training pipeline is too slow. What a system can control is the administrative load on the clinicians still there — intake, coding, and follow-up at a fraction of the cost. They state the goal explicitly: not replacing the surgeon but making the surgeon's day survivable.
- **The turnover nobody totals is administrative staff**: Omar starts with the number that gets a board's attention — $800,000 to replace a physician — then points to a larger figure that stays invisible because it is spread across line items. At 20% annual administrative turnover, a 500-bed hospital churns hundreds of roles a year, each carrying recruiting costs, training costs, error costs while new hires ramp up, and revenue lost when phones are not answered fast enough. Any single line looks small; the total, they argue, runs into millions. Physicians cost more per head, while administrative staff cost more in volume.
- **Adoption is proof the tool is used, not proof it was worth deploying**: Omar gives a health system credit for passing one million ambient AI notes: it shows the technology works at scale and that clinicians will use it daily. They say they will build on it rather than argue with it. Then they shift the measure. The next milestone is not how many notes were generated but how many hours those notes gave back to people who would otherwise be charting at 10pm. Minutes added to the workforce, or saved by clinicians, prove a deployment was worth it; Omar predicts the systems that win the next phase will report that second number as proudly as the first.
- **Sometimes the absence of a human is what lowers the barrier to care**: Omar names a belief they say the industry repeats — that patients want a human on the phone for anything medical — and describes data pointing the other way. A health system ran outbound voice AI to walk patients through colonoscopy prep, and the agent got a higher response rate than the human care managers did; people picked up for the machine. Patients also asked the agent questions they had never asked staff: embarrassing, personal questions about preparation they would not say aloud to another person. The missing human, they argue, was the reason patients opened up, not the weakness everyone assumed. Shame is a barrier to care that the absence of a person in the room can sometimes lower.

## Work to read

- [“Hospitals will adopt the AI that makes them more money”](https://www.linkedin.com/posts/ao7_taha-kass-hout-named-the-most-honest-constraint-activity-7465386868898017282-aAYx)
- [The prior-authorization math: $2 an hour against $41](https://www.linkedin.com/posts/ao7_if-you-run-a-health-system-do-this-math-activity-7475618383733018625-muPc)
- [Retention is cheaper than recruiting](https://www.linkedin.com/posts/ao7_if-you-run-a-health-system-attrition-is-activity-7482599799297507328-g1m7)
- [$800,000 to replace a physician, and the admin math nobody runs](https://www.linkedin.com/posts/ao7_20-of-your-admin-staff-will-quit-activity-7443371334497304577-hYIY)
- [Adoption is not the milestone; returned minutes are](https://www.linkedin.com/posts/ao7_a-major-health-system-passing-1-million-ambient-activity-7483566171758301184-Z-2H)
- [Patients asked the machine the questions they never asked staff](https://www.linkedin.com/posts/ao7_we-keep-telling-ourselves-patients-want-a-activity-7483913524591841280-viSw)

## Brand relationships

- **Sully.ai** (disclosed_partnership)

## Partnerships

Ahmed Omar's seven posts, published between 27 March and 17 July 2026, offer commentary on health system economics and healthcare AI but do not say whether they take sponsorships or paid collaborations. None carries a sponsor disclosure, media kit, rate card, or stated way for a brand to commission work. The only commercial product they name and promote is Sully.ai, whose roughly $2-an-hour cost they contrast with $41-an-hour human administrative staff and the fully loaded cost of replacing a physician. The posts do not establish whether this reflects employment, an investment, or a paid relationship. For a campaign aimed at healthcare AI audiences, ask whether they accept paid collaborations and clarify their relationship with Sully.ai. A natural buying conversation would be a co-marketing or sponsored-commentary arrangement tied to a health system ROI or retention campaign; ask about terms, deliverables, review steps, and turnaround, which the posts do not specify.

## Alternatives

- Michael Belkin JD, MSHA, FACHE, CMPE: A stronger fit for a campaign about physician staffing, burnout, and workforce planning. In a post on burnout, Belkin connects administrative burden and difficult working conditions to turnover, then makes the case for flexible workforce models. Another post argues for anticipating clinician-supply gaps instead of reacting once they become urgent. Together, these offer a broader workforce-strategy frame than Ahmed Omar’s case for using AI to reduce administrative work.
- Blake Madden: Choose Madden for a campaign needing a concrete healthcare AI product explanation. His inpatient-coding post walks through the workflow, accuracy evaluation, human-review controls, and potential effects on coding backlogs and time to bill. That makes the product’s operational implications more tangible than Ahmed Omar’s emphasis on the link between administrative burden and workforce retention.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/