Claims Library Entry
Midjourney Makes AI Images. Now It's Building a Full-Body Scanner
Midjourney, known for AI image generation, announced plans to build full-body ultrasound scanners, aiming for 50,000 units in spas by 2031 and a billion scans per month. The article argues the real product is not the scanner itself but the massive data flywheel the scans would create, drawing a parallel to Tesla's data-driven approach.
Published June 18, 2026 by Kamil Banc
Lead claim
Midjourney's spa-based body scanners are really a data flywheel play, not a medical device business.
Atomic Claims
What this article supports
Copy individual claims as needed.
Claim 1 · Source summary
50,000 Scanners by 2031
Midjourney plans to deploy 50,000 full-body ultrasound scanners in spas by 2031.
Claim 2 · Source summary
Billion Scans Monthly Target
The company targets running a billion full-body scans per month once deployed.
Claim 3 · Source summary
MRI Power, Spa Casual
Founder David Holz described the scanner as powerful as an MRI and casual as a spa.
Claim 4 · Source summary
Three Years of Images
Midjourney spent three years turning text prompts into AI images on Discord.
Claim 5 · Kamil's interpretation
Scanner as Misdirection
The author argues the scanner is misdirection for building a data flywheel like Tesla's.
Evidence
Context behind the claims
Quote
"As powerful as an MRI, and as casual as a trip to the spa."
Key statistics
50,000 scanners
Midjourney's stated plan is to have 50,000 full-body ultrasound scanners in service by 2031.
1 billion scans per month
The company's stated target volume of full-body body scans it aims to run monthly at scale.
1.28 million cars
Tesla vehicles on paid Full Self-Driving cited by the author as a comparable data flywheel already operating at scale.
3 years
Time Midjourney spent building its text-to-image product on Discord before announcing the medical scanner.
Supporting context
The article's methodology is strategic pattern-matching: the author compares Midjourney's announced scanner deployment to Tesla's Full Self-Driving data collection model, arguing both businesses derive durable value from proprietary training data rather than the visible product. Practitioners should note the analytical lens here — evaluating AI companies by the data flywheel they create, not the product they sell. For founders and strategists, the applicable lesson is that distribution channels (spas, vehicles) can be engineered primarily as data-generation infrastructure. Readers should verify the scanner's technical claims independently, as the piece focuses on business strategy rather than clinical efficacy.
How to Cite
Use the claim-level citation when you need a precise statement. Use the article or claims-collection citation when you want the wider argument and source context.
Individual Claim
Best when you need to cite one atomic claim directly inside a memo, deck, research note, or AI output.
"[claim text]" (Banc, Kamil, 2026, https://kbanc.com/claims-library/midjourney-makes-ai-images-now-its-building-a-full-body-scanner)Original Article
Use this when you want to cite the full newsletter article at AI Adopters Club rather than the structured claims page.
Banc, Kamil (2026, June 18, 2026). Midjourney Makes AI Images. Now It's Building a Full-Body Scanner. AI Adopters Club. https://aiadopters.club/p/midjourney-makes-ai-images-now-itsClaims Collection
Use this when you want to reference the full structured claims collection on this page.
Banc, Kamil (2026). Midjourney Makes AI Images. Now It's Building a Full-Body Scanner [Structured Claims]. Retrieved from https://kbanc.com/claims-library/midjourney-makes-ai-images-now-its-building-a-full-body-scannerAttribution Requirements
- Include the author name: Kamil Banc.
- Include the source: AI Adopters Club or the structured claims page.
- Link to the original article or the claims page you used.
- Indicate any edits or transformations if you changed the wording.
Related Reading
More from the library
Market research isn't hard because data is unavailable—it's hard because people don't know what questions to ask. This article reveals how AI tools like Gemini Deep Research can run the same structured analysis consultants charge $150K for, delivering market entry plans in 20 minutes instead of months.
5 claims
This article discusses how AI can transform customer persona development by focusing on concrete decision criteria instead of superficial demographic details. It outlines a method for using AI to extract meaningful insights about customer needs, pricing strategies, and sales objections.
5 claims
This article explores how AI can help businesses improve their valuation by systematically reducing operational risks and creating more predictable systems. It details five specific AI-powered approaches that can transform a business's attractiveness to potential buyers and increase its market value.
5 claims