AI and Israeli Marketing

Executive Summary

Generative AI has moved the top of the marketing funnel. In the United States, 35% of consumers now begin product discovery inside an AI tool, compared with 13.6% who begin inside a search engine. In B2B, 42% of decision-makers open the buying process with a query to a large language model. The shift is no longer a forecast; it is a measured change in consumer and buyer behavior.

The most consequential single finding for communications and marketing leaders is that this shift rewards earned media at a structural level. Muck Rack's analysis of more than one million AI prompts found that 85.5% of AI citations reference earned media rather than brand-owned content. University of Toronto research puts the ratio at approximately five to one. Broad distribution can raise AI citation rates by up to 325%. A brand on four or more third-party platforms is 2.8 times more likely to be cited than one that relies on its own domain.

This reframes the role of public relations. The same earned-media placements, executive thought leadership, LinkedIn presence, Wikipedia accuracy, review-platform management, and community engagement that communications firms have always produced are now also the primary retrieval inputs to AI-generated answers. Work that historically read as reputational overhead now has measurable performance-marketing value.

For the Israeli market, the opportunity is unusually well-defined and quantifiable. Israel's $1.58 billion digital advertising economy is concentrated on two platforms — Google at 46% of local digital spend and Meta at 15% — that are themselves becoming AI-answer surfaces. Israel's largest consumer categories are oligopolistic, so share of model translates directly into share of wallet. Israeli technology exporters operate in English-language AI environments where competition is already intense. And Hebrew, as a minority training language in every frontier model, has a thinner source pool — meaning a disciplined Hebrew earned-media program can capture disproportionate AI citation share while competitors wait.

Across the ten major Israeli consumer and B2B sectors mapped in this study, a 15–25% reallocation toward earned-media-driven GEO implies a national reallocation opportunity in the range of NIS 750 million to NIS 2.4 billion — roughly $215 million to $680 million — over the next 24 to 36 months, before any net-new spending is added. The tech and SaaS export component alone accounts for the majority of the upper bound.

1. The Shift: Search to AI Answers

Generative Engine Optimization (GEO) is the emerging discipline of structuring content, third-party coverage, and brand mentions so that generative AI systems cite a brand by name when answering a user question. GEO does not replace search engine optimization. Approximately 99% of Google AI Overview citations still originate from the organic top 10, and 87% of ChatGPT citations correspond to Bing top results. GEO layers a new requirement on top of SEO: the content must be cited inside the synthesized answer, not only ranked below it.

Adoption is faster than any previous channel shift

• ChatGPT reached 100 million users in 60 days after its November 2022 launch — the fastest consumer adoption in technology history.
• ChatGPT reached 400 million weekly active users in February 2025 and 800 million by October 2025.
• Gemini grew 157% between April and September 2025 to 1.1 billion monthly visits.
• Perplexity processed 780 million queries in a single month as of early 2026, up from 230 million in August 2024 — more than a 3x increase in under 18 months.
• Business AI adoption rose from 14% to 29.2% in the first half of 2025. 84% of businesses now consider AI their top strategic priority.

Consumer behavior inside AI is different from consumer behavior inside search

• Average session length on AI search is 6 minutes, compared with seconds on Google.
• Average AI query length is 23 words, compared with 4 words on Google — users describe entire situations rather than typing fragments.
• Median time spent in AI Mode: 77 seconds comparing brands or products, 71 seconds learning information, 52 seconds choosing or purchasing.
• Users treat AI responses as authoritative answers rather than starting points, producing higher trust transfer to the brands cited inside them.

The traffic is small but disproportionately valuable

• AI referral traffic is approximately 1% of total web visits globally, growing approximately 1 percentage point per month.
• AI search visitors convert 5x better per visit than traditional organic (14.2% vs 2.8%, Semrush 2026).
• AI-driven traffic to US retailers grew 4,700% year-over-year as of July 2025.
• Click-through rate on informational queries falls from 1.41% to 0.64% when an AI answer appears — a 55% decline.

2. The Israeli Advertising Market

Israel's advertising economy has been digitizing steadily for a decade and is now structurally dependent on platforms that are themselves being reshaped by generative AI.

Five structural features amplify the Israeli GEO opportunity

Platform concentration. Google captures approximately 46% of Israeli digital ad spend; Meta captures approximately 15%. Roughly 61% of local digital advertising flows through two platforms that are integrating AI answers directly into the user experience. The platforms Israeli brands already buy from are the platforms that are intermediating away their direct click traffic.

Oligopoly structure. Israel's largest consumer categories are concentrated: five major banks, three cellular carriers, four HMOs, two dominant supermarket chains, four to five top insurers. In oligopoly, share of model maps more directly onto share of wallet than in fragmented markets.

Mortgage and credit cycle. Israeli banking sector assets grew 10–12% year-over-year through 2024–2025, driven by a mortgage lending boom. High-intent Hebrew financial queries are currently among the most valuable uncontested AI real estate in the market.

Export dependency. Israel's largest corporates derive significant revenue from overseas. Their visibility inside English-language AI answers is a direct input to export demand and enterprise sales pipeline. The English-language citation environment operates as a separate market that must be worked independently of the Hebrew one.

High digital engagement. Israeli consumers index above OECD averages on smartphone penetration, e-commerce adoption, and digital service use. AI-answer behaviors arrive earlier and faster than in peer markets.

3. Category Exposure: Where the Money Moves First

The shift from search to AI answers does not affect all categories equally. Exposure correlates with three variables: the share of consumer decisions that begin with an informational query, the financial value of a converted customer, and the maturity of the category's digital funnel.

Category observations

Banking. Hebrew AI answers to high-value financial queries default to generic guidance or aggregator content. Major Israeli banks rank well on traditional SEO but are rarely named inside AI responses, leaving significant uncontested share of model during a period of record mortgage origination. Financial comparison queries in Hebrew represent one of the highest-value uncontested pockets of AI real estate in the market today.

Telecom. AI answers about Israeli cellular plans and fiber frequently cite Hebrew-language reviews containing outdated promotional pricing. Real-time plan updates do not propagate into the model's retrieval layer, creating a structural lag that reduces the efficacy of live acquisition campaigns.

Travel. Global aggregators dominate AI citations for Israeli hotel and flight queries. Direct-to-consumer hospitality and airline brands rarely surface in AI answers unless named explicitly, suppressing direct-booking revenue.

Tech and SaaS. This is the single most exposed category. 42% of B2B decision-makers now open evaluation inside an LLM, and the AI response functions as the shortlist. Israel's tech sector sells disproportionately into English-speaking markets, where competition for AI citation is already intense and where most Israeli vendors have not yet invested.

Defense and industrial. This is a sovereign-level narrative dimension rather than only a marketing problem. Multiple independent audits of leading AI models have documented uneven and at times unfavorable framing of Israel-related subject matter in English-language responses. The narrative inherited inside an English-language AI answer is not controllable unless citation surface area is actively built on authoritative domains.

4. The Earned Media Imperative

The single most consequential finding in the body of 2025–2026 GEO research is that AI systems prefer earned media at a structural level. This reverses two decades of digital marketing orthodoxy, which held that owned channels deliver the highest-margin, longest-duration brand value. In the AI-mediated discovery environment, owned content is a secondary input. Third-party coverage is the primary input.

What the citation data shows

• Muck Rack analyzed more than one million AI prompts and found that 85.5% of AI citations reference earned media sources.
• University of Toronto research found that AI engines cite third-party publications approximately 5x more frequently than brand websites.
• When a user mentions a brand by name in a query, earned media accounts for 48% of resulting citations.
• When a user asks what customers think about a brand, earned media accounts for 82% of citations.
• Owned content performs best only for functional and specification queries (~50% citation share).

Distribution mathematics favor disciplined PR

• Distributing the same piece of content across a wide range of publications can increase AI citation rates by up to 325% (Stacker, December 2025).
• Brands appearing on four or more third-party platforms are 2.8x more likely to be cited in ChatGPT responses than single-platform brands.
• Domains with more than 32,000 referring domains are 3.5x more likely to be cited by ChatGPT than domains with fewer than 200.
• Domains with profiles on review and listing platforms (Trustpilot, G2, Capterra, Yelp) have 3x higher citation rates.
• The average domain age of ChatGPT-cited sources is 17 years — AI systems display strong preference for established entities with long track records.

5. The Israeli Tech Export Premium

Israel's technology sector is the single most AI-exposed segment of the Israeli economy. Over 300 Israeli SaaS companies operate internationally, with flagship firms reporting 2024–2025 revenues between $150 million and $1.1 billion. The combined ecosystem — including cybersecurity, fintech, mobility, digital health, workflow, and e-commerce infrastructure — generates tens of billions of dollars in annual revenue, the majority sold into English-speaking markets where 42% of B2B buyers now open their evaluation inside an LLM.

The marketing spend reality in B2B SaaS

• Median B2B SaaS company spends 8% of annual recurring revenue on marketing (SaaS Capital, 2025 survey of 1,000+ private companies).
• Higher-growth B2B SaaS companies spend approximately 40% more on marketing than lower-growth peers.
• Equity-backed B2B SaaS companies spend approximately twice as much on marketing as bootstrapped companies — which describes most Israeli venture-backed tech.
• Applied to the Israeli tech ecosystem's top 50 private SaaS firms alone, median marketing spend conservatively exceeds $1.5 billion annually.

Customer acquisition cost benchmarks

The AI invisibility premium

For an Israeli mid-market SaaS exporter with 500 new customers per year at $1,500 CAC, total acquisition spend is approximately $750,000 annually. If 42% of target buyers now open evaluation in an LLM, approximately $315,000 of that spend is exposed to whether the brand is cited inside the AI answer during the initial shortlist stage. A brand absent from AI answers is not absent at the click stage; it is absent at the shortlist stage, which is earlier and more consequential.

For an enterprise-tier Israeli security or identity vendor, where CAC can exceed $10,000 per customer and buying committees of 5–7 people each run independent LLM queries, AI absence functionally raises CAC by compressing the early funnel. Industry estimates put the effective CAC premium for AI-invisible B2B tech brands in the 15–35% range, depending on category density.

6. How Communications Programs Produce AI Citation

Every service line that public relations firms have historically sold — earned media placement, executive thought leadership, LinkedIn and social strategy, Wikipedia and reference-site accuracy, press release distribution, awards, data-led research, podcast bookings, review-platform management, crisis response — is now also a direct input to AI citation. The work has not changed. The value of the output has.

What 5W audits and reports

• Share of Model (SoM): percentage of AI answers to a defined query set that name the brand, tracked monthly in Hebrew and English.
• Citation source mix: which domains are feeding the AI's answer about the brand, and whether those domains are trending up or down in model preference.
• Sentiment in citation: whether the brand is characterized positively, neutrally, or negatively when named.
• Prompt-level movement: each query tracked from absent to cited, with associated domain attribution.
• Competitive benchmark: the same metrics for the top three to five category competitors, producing a category share-of-model leaderboard.
• Platform split: ChatGPT, Gemini, Perplexity, and Google AI Mode each report separately because only 11% of domains earn citations across both ChatGPT and Perplexity.

7. Sector Spend Economics

The figures below are estimates built from published Israeli advertising data, sector revenue disclosures, and applied international marketing spend benchmarks; they are indicative ranges, not audited figures. Their purpose is to quantify the scale of the reallocation opportunity sector by sector.

Summing across all sectors, the aggregate national reallocation opportunity falls in a range of approximately NIS 750 million to NIS 2.4 billion — roughly $215 million to $680 million — over the next 24 to 36 months, before any net-new advertising spending is added. The tech and SaaS export component alone accounts for the majority of the upper bound because of the sector's size, its English-language exposure, and elevated customer acquisition costs.

8. The Hebrew Data Gap and the First-Mover Window

Hebrew is a minority training language in every major frontier AI model. This creates two asymmetric effects for brands operating in the Israeli market.

Effect one: thin source pool, low competitive floor

In Hebrew-language queries, the available pool of sources that AI systems draw from is materially smaller than the English, French, German, or Spanish pools. The Nagel Committee's August 2025 report to the Israeli government identified the absence of a Hebrew national language model as a digital sovereignty issue. For brands, this is an opportunity. A disciplined Hebrew earned-media program can capture disproportionate share of model quickly. The first 12–24 months represent the maximum arbitrage window.

Effect two: inherited English-language narratives

In English-language queries about Israeli companies, Israeli categories, or Israel itself, the source pool is dominated by international media whose coverage is uneven. For Israeli corporates with international revenue exposure, the narrative inherited inside an English-language AI answer is not under the company's control unless citation surface area is actively built on high-authority English-language domains.

Why the window closes

AI systems reinforce their own citation preferences over time. A domain cited today is more likely to be cited tomorrow because the model's retrieval patterns, external link economies, and human evaluation signals all tilt toward established authority. The average domain age of ChatGPT-cited sources is 17 years. Brands investing during the 2026 window are building citation surface area that compounds. The current competitive floor is unusually low: 47% of brands have no GEO strategy, 26% have zero mentions in AI Overviews. The arbitrage is available now. It will be substantially smaller in 18 to 24 months.

Frequently Asked Questions

Methodology and Sources

This study synthesizes published data from industry research, academic research, regulatory filings, and platform analytics disclosed between 2023 and April 2026. Sector spend estimates in Section 7 combine Israeli advertising market data with published international marketing allocation benchmarks applied to sector revenue profiles; these are indicative ranges, not audited figures.

Sources consulted include: Similarweb, Semrush, Ahrefs, SE Ranking, AirOps, Stacker, Muck Rack, University of Toronto, Omniscient Digital, Tinuiti, Profound, Superlines, Bluefish, SaaS Capital, First Page Sage, Benchmarkit, Paddle, SimplicityDX, Nielsen, Statista, Gartner, Conductor, Princeton University, Incremys, Capgemini Research Institute, Master of Code Global, eMarketer, GetLatka, Bank of Israel Annual Report 2024, Israel Marketing Association, Nagel Committee Report on Accelerating AI in Israel (August 2025), public Foreign Agents Registration Act filings, Calcalist, Globes, Times of Israel, and Ynet.

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