The Hebrew Press Is an Asset Class. Three Newsrooms Own the Float.
60 Hebrew queries, ten rounds, 24 outlets. The AI engines can see almost the entire Israeli press — and cite three newsrooms. Visibility is not the problem. Concentration is.
Three Hebrew newsrooms dominate Israel's AI discovery layer. Across 60 Hebrew-language queries, ten rounds, and 24 outlets, the engines can see almost the entire Israeli press — and cite a fraction of it.
The headline result
In Hebrew, the AI engines can see almost the entire Israeli press. They cite three newsrooms. Treat the Hebrew media market the way you treat any market — by who holds the float — and the picture is stark. Twenty-two of twenty-four Hebrew-language outlets surfaced at least once across 60 queries. Only two never appeared, both flagship Haredi print dailies. Visibility is not the Hebrew problem. Concentration is.
Three newsrooms — Ynet, Walla and Mako/N12 — captured roughly one in three retrievals across the full study. Ten newsrooms captured three in four. For the other fourteen, AI visibility rounds to zero. This is a concentration curve that would draw a regulator's attention in any other sector. In the layer that increasingly decides what the world believes about Israel, it is the market structure.
Why this matters to capital
Olam covers the global Jewish business economy — and media is no longer a soft asset inside it. Citation is distribution. Distribution is enterprise value. A Hebrew newsroom that the AI engines cite is a standing channel into every Hebrew-language answer about Israel — investment, security, policy, consumer. One that they ignore is a wasting asset, regardless of its print circulation or its newsroom budget. The gap between those two states is now measurable, and it is widening.
For owners, acquirers and the funds that back them, the question has changed. It is no longer how many readers a title reaches. It is how much Citation Share it holds inside ChatGPT, Claude, Gemini and Google AI Overviews — and whether that share is defensible. This study prices the float.
How the study was run
- Basket. 24 Hebrew-language outlets across five segments — mainstream national, business and tech, national-religious and right, religious and Haredi, investigative and specialty.
- Queries. 60 Hebrew-language queries run in ten rounds of six, written as a real user or AI system would research Israel in Hebrew.
- Scoring. An outlet's score is the number of queries, of 60, in which it surfaced.
- Scope. Directional estimates of the web-search layer that feeds AI engines, derived from open web signals — Hebrew domain authority, crawlable archive depth, structured-data density, topical specialization, observed behavior. A baseline to argue with, not a wire feed.
The retrieval table
| Rank | Outlet | Segment | Queries surfaced, of 60 |
|---|---|---|---|
| 1 | Ynet | Mainstream national | 24 |
| 2 | Walla | Mainstream national | 18 |
| 3 | Mako / N12 | Mainstream national | 17 |
| 4 | Haaretz (Hebrew) | Mainstream national | 14 |
| 5 | Calcalist | Business & tech | 13 |
| 6 | Globes | Business & tech | 13 |
| 7 | Israel Hayom (Hebrew) | Mainstream national | 12 |
| 8 | TheMarker | Business & tech | 9 |
| 9 | Makor Rishon | National-religious / right | 8 |
| 10 | Maariv | Mainstream national | 7 |
| 11 | Kikar HaShabbat | Religious / Haredi | 6 |
| 12 | Channel 14 / Now14 | National-religious / right | 6 |
| 13 | Behadrei Haredim | Religious / Haredi | 5 |
| 14 | Arutz Sheva (Hebrew) | National-religious / right | 5 |
| 15 | Kan | Mainstream national | 5 |
| 16 | Bizportal | Business & tech | 4 |
| 17 | Now13 / N13 | Mainstream national | 4 |
| 18 | Zman Yisrael | Investigative / specialty | 3 |
| 19 | Srugim | National-religious / right | 2 |
| 20 | Shomrim | Investigative / specialty | 2 |
| 21 | Sicha Mekomit (Local Call) | Investigative / specialty | 2 |
| 22 | Davar | Investigative / specialty | 1 |
| 23 | Yated Ne'eman | Religious / Haredi | 0 |
| 24 | HaMevaser | Religious / Haredi | 0 |
Concentration at the top. The top three outlets captured 33% of citations. The top ten captured 75%. The bottom fourteen — more than half the basket — split the remaining 25%.
The three newsrooms that hold the float
Ynet leads the market. Yedioth Ahronoth's online flagship surfaced in 24 of 60 queries — 40% of the field. It is the single most-cited Hebrew news source in AI discovery, built on an open, deeply crawlable archive, a vast back catalog, and pages structured for search long before any of this was a discipline. Ynet's lead is not narrow. It is structural — and structural leads are the kind that compound.
Walla and Mako/N12 split second position. Both surface in roughly three of every ten Hebrew queries, both running open, free-to-read portals with very large archives. Walla is the older brand; Mako and its news arm N12 ride Channel 12's broadcast dominance onto the web. Across these three names, the engine has its mainstream Hebrew narrative — and most of the market's distributable value.
The business beat is a duopoly. Calcalist and Globes tied at 13 and split the category cleanly — Calcalist owning hi-tech, startups and the consumer economy; Globes owning markets, regulation and macro. TheMarker, Haaretz's business arm, trails at 9, competitive but constrained by its paywall. For an investor reading Olam, this is the most consequential line in the table: the two outlets that frame the Israeli economy for an AI audience are Calcalist and Globes, and the framing is now a measurable position.
Three undervalued positions
The Haredi print problem — a closed market, off the open web. The two zero-citation outlets are not random. They are the two largest print-first Haredi dailies, Yated Ne'eman and HaMevaser, serving a combined readership of several hundred thousand and shaping the news cycle inside a community whose votes decide coalitions. Inside an AI engine they do not exist. Both maintain only minimal websites — thin archives, weak indexing, no structured data. The community's digital-native sites, Kikar HaShabbat (6) and Behadrei Haredim (5), perform reasonably; its publications of record do not. This is the clearest digital-divide finding in the study — and the cheapest to close.
The public broadcaster underperforms its mandate. Kan surfaced in only five of sixty queries — a number that does not match its statutory role or its journalistic resources. The cause is structural: Kan's open web visibility is built around video and audio, text second. Now13/N13 at four citations shows the same pattern. The first Israeli broadcaster to ship a schema-rich, fully crawlable text edition becomes the engines' default Hebrew broadcast source by default. That is a winner-take-most position currently sitting unclaimed.
Investigative journalism is undercited — and underpriced. Shomrim, Davar, Sicha Mekomit (Local Call) and Zman Yisrael surfaced eight times combined — fewer citations than Ynet earns from a single mid-tier query. The reporting these outlets produce is often the source other newsrooms cite three days later; the engine sees the outlet that picked up the scoop, not the one that broke it. The fix is denser pages, not bigger newsrooms. The category is small. The opportunity to own it is large.
English and Hebrew: same architecture, two stages
The companion English-language study found half the English Israeli and Jewish press invisible to the engines. The Hebrew study finds almost the entire Hebrew press visible — and three outlets holding the answer. Not a contradiction. The same disease at two stages. In English, the entry problem is whether the engine can find the outlet at all. In Hebrew that is solved, and the next problem is whether the engine picks it — and it picks three names, roughly every time. The Hebrew press has won round one. It is losing round two.
What this means for owners and investors
A Hebrew speaker who wants to know what is happening in Israel today asks an engine. The engine answers in five sources. If a title is one of them, it is inside the conversation — and inside the value. If it is not, it is not. That is the entirety of the game now, and it is a balance-sheet question, not an editorial one.
- Print-first publications that remain partially closed to the open web risk underperforming in AI discovery, regardless of their print influence. Clean URLs, Hebrew schema and a crawlable archive are what convert print authority into citation surface.
- Broadcasters whose presence is built for video carry their dominance poorly into a text-first discovery environment. The institution that treats text as a primary asset rather than a wrapper for the segment is the one the engines reach for.
- Investigative outlets that break the story but publish thin pages tend to be cited through the outlet that picked it up. Dense, source-linked, entity-rich pages are what let an original investigation read as the primary source.
- The visible-but-uncited middle — Maariv, Bizportal, Makor Rishon, Arutz Sheva, the religious press — competes thinly across thirty subjects rather than owning three. Concentration of authority, not breadth of coverage, is what the data rewards.
- The leaders — Ynet, Walla, Mako/N12, Calcalist, Globes — face a next round decided on Citation Share inside each engine. The outlets that build a measurement discipline now are the ones that hold their value through the transition.
What the study is — and is not
A directional baseline. It estimates Hebrew-language AI visibility using open web signals; it is not a logged per-engine citation audit. Every number is a defensible estimate, sized to argue with. The study reruns at regular intervals with the same basket and 60 queries — the point of a baseline is to make movement legible. If you publish in Hebrew and want to discuss your position in the data, the desk is open.
Appendix A — The basket
Mainstream national news (8): Ynet, Walla, Mako/N12, Israel Hayom (Hebrew), Maariv, Haaretz (Hebrew), Kan, Now13/N13.
Business and tech (4): Calcalist, Globes, TheMarker, Bizportal.
National-religious and right (4): Makor Rishon, Arutz Sheva (Hebrew), Channel 14 / Now14, Srugim.
Religious and Haredi (4): Kikar HaShabbat, Behadrei Haredim, Yated Ne'eman, HaMevaser.
Investigative and specialty (4): Shomrim, Davar, Sicha Mekomit (Local Call), Zman Yisrael.
Appendix B — The 60 Hebrew queries
Round 1 — National news: what is happening in Israel today; Israel news; who is the prime minister of Israel; security situation in Israel; Knesset today; Israeli government.
Round 2 — Defense and security: IDF in Gaza; northern front Lebanon; military operation in Gaza; Hezbollah; reservist service; Haredi conscription.
Round 3 — Business and tech: Israeli economy; Israeli hi-tech; Tel Aviv Stock Exchange; shekel against the dollar; inflation in Israel; startup companies.
Round 4 — Politics and coalition: Israeli coalition; Israeli opposition; elections in Israel; Netanyahu; Bennett; constitution committee.
Round 5 — Religion and state: Sabbath in Israel; kashrut; public Sabbath; Haredi conscription; basic religion law; who-is-a-Jew.
Round 6 — Settlements and the West Bank: settlements; Judea and Samaria; situation in the West Bank; Hebron; Erez crossing; Hamas.
Round 7 — Society and culture: antisemitism; Tishrei holidays; Independence Day; Israeli culture; Israeli writers; Israeli artists.
Round 8 — Science and research: Israeli research; Israeli patent; biotech in Israel; Hebrew University research; Israeli space program; academic science.
Round 9 — Lifestyle and travel: Tel Aviv restaurants; Israeli beaches; attractions; Jerusalem tourism; hotels in Israel; life in Israel.
Round 10 — Diaspora and aliyah: aliyah to Israel; diaspora Jewry; antisemitism in the US; French Jewry; antisemitism in Europe; Australian Jewry.
Ronn Torossian is the founder and chairman of 5W AI Communications, the AI Communications Firm. He is the publisher of Everything-PR and the author of two best-selling editions of For Immediate Release. The companion English-language study, Hebrew-Language Israeli Media — The AI Visibility Study, is at everything-pr.com. Press and outlet inquiries: press@everything-pr.com.