AI Models vs Security AI moats
Security AI has the wider moat: an average of 79 out of 100 against 68 for AI Models AI, 11 points apart. They rank 1st and 6th of 29 AI markets. Security rates a wide moat and AI Models a narrow one. Security on regulatory barrier, habit and retention and switching costs. AI Models is less crowded, with a saturation of 30 against 33 for Security. Security is better protected but more crowded; AI Models is more open but easier to copy.
Side by side
The two markets on FalcoScan's moat rating, crowding and threats. The better figure of each pair is in bold; for crowding, threats and the no-moat share, lower is better.
| Measure | AI Models | Security | Better |
|---|---|---|---|
| Moat rating | Narrow moat | Wide moat | |
| Average moat | 68 of 100 | 79 of 100 | Security, by 11 points |
| Rank among AI markets | 6 of 29 | 1 of 29 | Security, by 5 places |
| Main moat | Hard to copy | Regulatory barrier | |
| Products with a wide moat | 18% | 84% | Security, by 66 points |
| Products with no moat | 6% | 0% | Security, by 6 points |
| Saturation (crowding) | 30 | 33 | AI Models, by 3 points |
| Wrapper exposure | 1% | 0% | Security, by 1 point |
| Platform dependency | 19 | 36 | AI Models, by 17 points |
| Products rated | 445 | 348 |
Moat sources
Each source and threat on a 0 to 100 scale, averaged across each market and rated against all AI markets.
AI Models, filled · Security, dashed
Where AI Models is stronger
No moat source more than 5 points ahead of Security.
Where Security is stronger
- Regulatory barrier+75
- Habit and retention+24
- Switching costs+21
Widest moats in each market
The five products with the highest moat score in each market, shown as bands. Exact scores are on paid plans.
Widest moats in AI Models
- 01JAXComposable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and moreWide moat
- 02Preferred NetworksJapans flagship deep learning company spanning auto, healthcare, roboticsWide moat
- 03EtchedAI accelerator chips purpose-built for transformersWide moat
- 04HelsingAI for democratic defenseWide moat
- 05TenstorrentOpen-source AI computeWide moat
Widest moats in Security
- 01ApiiroAI application risk graphWide moat
- 02CrowdStrike Charlotte AIGenerative AI for cybersecurity workflowsWide moat
- 03Axonius CyberCybersecurity asset management platformWide moat
- 04CyeraAI data security posture managementWide moat
- 05Drata ComplianceAI-powered security compliance automationWide moat
More comparisons
Each market against its closest rivals by moat, and against the widest and narrowest markets. The figures are the two average moats.
AI Models against
Questions
Which has a wider moat, AI Models AI or Security AI?
Security AI, with an average moat of 79 out of 100 across 348 rated products, against 68 across 445 in AI Models AI. 84% of Security products have a wide moat, against 18% in AI Models.
Is AI Models AI or Security AI more crowded?
AI Models is less crowded, with a saturation of 30 against 33 for Security. Saturation runs from 0 to 100 and measures how crowded a market is. Security is better protected but more crowded; AI Models is more open but easier to copy.
How do the moats of AI Models AI and Security AI differ?
AI Models's main moat is hard to copy and Security's is regulatory barrier. Security leads on regulatory barrier (+75), habit and retention (+24) and switching costs (+21).
Is AI Models AI or Security AI more exposed to wrappers?
AI Models AI: 1% of its products could be rebuilt on a public model quickly, against 0% in Security AI.
Which AI Models and Security AI products have the widest moats?
In AI Models: JAX, Preferred Networks and Etched. In Security: Apiiro, CrowdStrike Charlotte AI and Axonius Cyber. Exact moat scores for every product are on FalcoScan's paid plans.
Cite and share
Quote a figure, link to the comparison or take the data for every market.
FalcoScan, “AI Models vs Security AI moats”, data updated 9 October 2026. https://falcoscan.com/moats/compare/ai-models-vs-security
@misc{falcoscan_moats_compare_ai_models_vs_security_2026,
author = {{FalcoScan}},
title = {AI Models vs Security AI moats},
year = {2026},
month = oct,
howpublished = {\url{https://falcoscan.com/moats/compare/ai-models-vs-security}},
note = {Data updated 9 October 2026}
}<a href="https://falcoscan.com/moats/compare/ai-models-vs-security">AI Models vs Security AI moats (FalcoScan)</a>
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