# Joshua Love

Joshua Love is a co-founder of Zite AI, where they build AI software for healthcare administration, including forecasting patient volumes to help health systems plan care sites, budgets, and staffing.

- Profile: https://b2binfluencer.marketing/creators/joshua-love/
- LinkedIn: https://www.linkedin.com/in/joshua-love-ziteai
- LinkedIn followers: 2,103
- Topics: artificial-intelligence, startup, healthcare, ai-adoption
- Based on 9 dated posts, latest 2026-09-22

## Summary

Joshua Love is most useful for founder-led thought leadership on AI for healthcare site-of-care planning.

- Best for: A healthcare technology company selling forecasting or analytics to health systems.
- Not for: A consumer brand or general-interest publisher seeking large general-audience video reach.
- Check first: Confirm audience reach, engagement, and audience match before committing budget.

### Takeaways

- Health systems open new care sites without projecting patient volume and pay for it.
- One health system paid $2 million for a site-of-care plan and $1 million to validate it.
- The business followed a buyer's problem, not the founders' original plan.

## Main ideas

- **Industry-specific AI, not general AI, will force organizations to change**: Love argues that the AI worth watching is built for one field at a time — weather forecasting, fraud detection, supply chains — rather than as a general-purpose model. Healthcare administration is Zite AI's version. The case for it: AI does not forget, tire, or make decisions based on office politics or gut feelings, so within three to five years, AI-driven tools will outperform seasoned experts on key tasks. Love urges readers to act: research AI startups in your field now, because early adopters will be harder to outmaneuver.
- **Health systems open new care sites without projecting patient volume — and pay for it**: Love's sharpest operational argument: systems rarely build pro-forma projections for patient volume at new sites, even though each is a multi-million-dollar investment. Because projections have rarely matched reality, systems fall back on rough rules of thumb or guesswork. Some set a viability threshold, such as 10,000 patients a year for a primary care site; others open a location assuming it will succeed, then close it about three years later. Love puts the failure rate at one in five new sites within the first five years, and says each closure diverts money from patient outcomes.
- **The business followed a buyer's problem, not the founders' original plan**: Love traces Zite AI through two ideas the founders abandoned before healthcare. The first was to use AI to predict commercial real estate development, buy land there and resell it; the idea stalled because Love and co-founder Jacob were graduate students without $100M. The second forecast how many customers a store should expect so retailers could choose a location. It reached the finals of the Cozad New Venture Challenge but did not crack the market after more than 100 customer discovery interviews. The turn came when a health system CEO described the same forecasting question in a harder form: systems need patient volumes to decide where to open clinics, set budgets and allocate staff. Unlike retail, not every patient generates revenue; a patient journey can involve emergency visits, referrals, research and word of mouth. Love says the priority is the outcome: building something that helps people get healthy instead of helping sell more hamburgers.

## Work to read

- [How did we end up building software for healthcare administration?](https://www.linkedin.com/posts/joshua-love-ziteai_how-did-we-end-up-building-software-for-healthcare-activity-7374819597658681344-GWTc)
- [Health systems aren't making pro-forma projections of how many patients they'll see at new sites of care](https://www.linkedin.com/posts/joshua-love-ziteai_health-systems-arent-making-pro-forma-projections-activity-7367209527672303617-4ulC)
- [AI is Coming for Your Industry. Are You Ready?](https://www.linkedin.com/posts/joshua-love-ziteai_ai-is-coming-for-your-industry-%F0%9D%97%94%F0%9D%97%BF%F0%9D%97%B2-%F0%9D%97%AC-activity-7291115529266741248-MWGU)

## Brand relationships

- **Zite AI** (owned_business)

## Partnerships

The posts here contain no documented sponsorship, brand-partnership, or commercial collaboration offer from Joshua Love. All three posts are written in the voice of a Zite AI co-founder explaining the company's work and the healthcare site-of-care problem; none of them mentions sponsored content, paid placements, affiliate arrangements, or a media kit. Two posts do reference a company, Zite AI, and a co-founder named Jacob, so a brand approach would most plausibly be a business or product-level conversation with Zite AI rather than an individual creator sponsorship. This is a statement about what the posts here do and do not document, not a claim that Love never accepts sponsorships or partnerships. For a buyer planning a content collaboration, the practical requirement is to open that conversation directly rather than select from a published format menu, and to expect the collaboration to run through the company rather than a personal channel.

## Alternatives

- Michael Belkin JD, MSHA, FACHE, CMPE: Choose Belkin over Joshua Love when the campaign should lead with clinician supply and workforce planning rather than site-of-care demand. Belkin's 11 April 2026 post argues that healthcare delivery organizations cannot treat physician staffing as a reactive function: patient access and revenue stability depend on anticipating clinician supply. That means forecasting demand by service line, tracking retirement and attrition, and building pipelines before gaps appear. A technology company whose product forecasts coverage gaps, staffing needs, or service-line demand is making Belkin's case, which they have already made publicly from an operator's position after 22 years of client work rather than a vendor founder's.
- Brenda S.: Choose Brenda S. when the collaboration is a hosted conversation with health system leaders rather than a written argument about forecasting. The 17 March 2026 post describes a dinner of six leaders run with no titles and no presentations, reports what people said about being stretched and what they were building, and invites readers to direct-message for one of ten seats at a San Diego gathering. The 11 August 2026 post announces a director role at Kaiser Permanente Care at Home across Southern California and Hawaii and traces a career through workforce wellbeing programmes, cross-functional implementations, sales and benefits, a consulting practice, and authorship. For a healthcare technology company seeking an executive roundtable, a dinner series, or a people-and-experience angle to open doors with health system operators, Brenda S. brings a documented convening practice and a first-person account of running operational work inside a health system.
- Chris Johnson: Choose Chris Johnson when the campaign's message is the platform argument rather than the prediction argument. The 22 September 2026 post says health systems assembled technology one point solution at a time and now ask how those capabilities work together. It argues that the next phase of digital transformation will be won by connecting operational intelligence across access, capacity, patient flow, staffing, and care delivery rather than accumulating more technology. That is the purchase case a platform vendor is making, and Johnson has already published it. The 3 September 2026 post grounds the same theme in a personal account of a family member's fall, walking through the case managers, doctors, nurses, environmental services teams, transporters, and administrators whose separate roles a patient experiences as one journey. A technology company selling an enterprise platform rather than a single application will find Johnson's published position closer to its own pitch than Love's.

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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/