Shipvane · 4 AE roles
Marco E. · joined Cargolio
Fleetora · first roles in DEGoogle Veo VS Kling AI_
As of 4 November 2026, Kling AI is named by 224 companies and Google Veo by 185; Google Veo skews to companies under 200 people (54% vs 53%), Kling AI to companies over 1,000 (14% vs 14%).
As of 4 November 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.
The website-and-DNS footprint is not comparable between a marketing suite and a CRM: Google Veo's script and mail records show on hundreds of thousands of small sites, Kling AI rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- Google Veo: 2–200 employees
- 54%
- Kling AI: 2–200 employees
- 53%
- Google Veo: 1,000+ employees
- 14%
- Kling AI: 1,000+ employees
- 14%
- Postings per company, 90 days
- 2.0 · 1.7
- Website or DNS footprint
- 0 · 0
Who chooses which
Share of each tool's companies in every segment. "Leans" marks a gap of more than two points.
| Segment | Google Veo | share | Kling AI | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 18 | 10% | 28 | 13% | Kling AI |
| 2-10 employees | 24 | 13% | 29 | 13% | even |
| 11-50 employees | 39 | 21% | 47 | 21% | even |
| 51-200 employees | 37 | 20% | 42 | 19% | even |
| 201-500 employees | 23 | 12% | 27 | 12% | even |
| 501-1000 employees | 19 | 10% | 20 | 9% | even |
| 1001-5000 employees | 14 | 8% | 21 | 9% | even |
| 5001-10000 employees | 4 | 2% | 3 | 1% | even |
| 10,001+ employees | 7 | 4% | 7 | 3% | even |
| Segment | Google Veo | share | Kling AI | share | Leans |
|---|---|---|---|---|---|
| Business & finance services | 69 | 37% | 73 | 33% | Google Veo |
| Technology & software | 41 | 22% | 67 | 30% | Kling AI |
| Media & content | 23 | 12% | 30 | 13% | even |
| Consumer services & leisure | 13 | 7% | 11 | 5% | Google Veo |
| Commerce & trade | 11 | 6% | 16 | 7% | even |
| Manufacturing & industry | 11 | 6% | 10 | 4% | even |
| Public, community & associations | 7 | 4% | 4 | 2% | even |
| Property & construction | 4 | 2% | 3 | 1% | even |
| Transport, logistics & rental | 2 | 1% | 2 | 1% | even |
| Utilities & infrastructure | 2 | 1% | 3 | 1% | even |
| Automotive | 1 | 1% | 2 | 1% | even |
| Hospitality & travel | 1 | 1% | 2 | 1% | even |
| Segment | Google Veo | share | Kling AI | share | Leans |
|---|---|---|---|---|---|
| United States | 96 | 52% | 113 | 50% | even |
| Germany | 13 | 7% | 18 | 8% | even |
| United Kingdom | 12 | 6% | 12 | 5% | even |
| India | 11 | 6% | 14 | 6% | even |
| Australia | 4 | 2% | 2 | 1% | even |
| France | 4 | 2% | 5 | 2% | even |
| Netherlands | 3 | 2% | 3 | 1% | even |
| United Arab Emirates | 2 | 1% | 3 | 1% | even |
| Brazil | 2 | 1% | – | – | outside top 12 |
| Canada | 2 | 1% | – | – | outside top 12 |
| Saudi Arabia | 2 | 1% | – | – | outside top 12 |
| Singapore | 2 | 1% | 3 | 1% | even |
| Ukraine | – | – | 5 | 2% | outside top 12 |
| Italy | – | – | 4 | 2% | outside top 12 |
| Austria | – | – | 2 | 1% | outside top 12 |
| Segment | Google Veo | share | Kling AI | share | Leans |
|---|---|---|---|---|---|
| arts media and entertainment | 149 | 32% | 170 | 36% | Kling AI |
| Design & UX | 122 | 26% | 158 | 34% | Kling AI |
| Marketing & communications | 46 | 10% | 50 | 11% | even |
| Software engineering | 28 | 6% | 4 | 1% | Google Veo |
| Data & AI | 23 | 5% | 41 | 9% | Kling AI |
| Education & training | 6 | 1% | 4 | 1% | even |
| IT operations & business systems | 6 | 1% | – | – | outside top 12 |
| Quality, safety & environment | 6 | 1% | – | – | outside top 12 |
| Product, program & project management | 4 | 1% | – | – | outside top 12 |
| Business development & strategy | 3 | 1% | – | – | outside top 12 |
| Customer service & success | 3 | 1% | – | – | outside top 12 |
| Administration & office | 2 | 0% | – | – | outside top 12 |
| manufacturing and production | 2 | 0% | 2 | 0% | even |
| procurement and purchasing | 2 | 0% | – | – | outside top 12 |
| construction and civil | 1 | 0% | – | – | outside top 12 |
| Engineering (non-software) | 1 | 0% | – | – | outside top 12 |
| Finance & accounting | 1 | 0% | – | – | outside top 12 |
| General management & consulting | 1 | 0% | – | – | outside top 12 |
| personal care and wellness | 1 | 0% | – | – | outside top 12 |
| research and science | 1 | 0% | – | – | outside top 12 |
| Sales | 1 | 0% | – | – | outside top 12 |
| Unclassified | 1 | 0% | – | – | outside top 12 |
| hospitality and food service | – | – | 1 | 0% | outside top 12 |
The companies behind each column
Companies using Google Veo →
Companies using Kling AI →
generative media voice ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Kling AI is named by 224 companies in job postings and Google Veo by 185; 135 name both. (Breaknorm, 4 November 2026, https://breaknorm.co/compare/google-veo-vs-kling-ai)
Read from the source, not self-reported
Every number on this page can be traced to a page we crawled or a posting we read. Full methodology →
- Job postingsRead hourly from career sites. A tool counts when the employer's own text names it as the team's system; both tools can count for one company.
- Website and DNSScripts and embeds on the company's pages, plus SPF, DKIM, MX and CNAME records of its domain that point at the vendor.
- SegmentsCountry, size and industry from the company profile built from its website.
- Not a reviewNo ratings, prices or feature claims. For those, read the vendors.
Google Veo vs Kling AI: questions
Which is more used, Google Veo or Kling AI?
By companies naming it in their own job postings, Kling AI (224) over Google Veo (185). By website-and-DNS footprint, Kling AI (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses Google Veo?
54% of Google Veo companies have 2 to 200 employees, against 53% for Kling AI. 14% of Google Veo companies have over 1,000 employees, against 14% for Kling AI.
Do companies run both?
135 companies name both in their postings, usually Google Veo in marketing and Kling AI in sales, or during a migration.
Where do these numbers come from?
From the employer's own text in job postings read hourly from career sites, and from scripts found on company websites in our crawl. No vendor data, no surveys.
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with the person who owns it
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