Snap launches Dotmo: the AI video spinoff that changes the game

The timeline: from internal team to independent company

June 18, 2026, TechCrunch has reported the official news. Snap has decided to spin off its AI video R&D group. The new company is called Dotmo . It is made up of current Snap employees leaving the social company's structure to set up an independent entity.

The stated reason is clear: costs. Developing AI video models requires massive infrastructure. Plus, it needs specialized teams that hardly find their natural home inside a company focused on Snapchat and social advertising. Therefore, the spinoff is a rational choice, not an escape.

It is not the first time Snap has gone down this road. In the past, the company has already spun off internal units to reduce operational overhead. However, this move has a different significance: it concerns generative AI applied to video, one of the most competitive and expensive segments in the entire tech landscape.

Who wins and who loses in this scenario

From a market balance perspective, the birth of Dotmo has effects on multiple levels. Let's look at them in order.

Snap it lightens the balance sheet. Consequently, it can focus resources on its core advertising business. However, it gives up a tech asset that, if mature, could have differentiated it from competitors. It's a defensive choice, not an offensive one.

Dotmo it gains operational freedom. In fact, as an independent entity it can raise capital from AI-focused VCs, form partnerships with video platforms, and develop products without the constraints of a social roadmap. On the flip side, it loses Snap's distribution network and data. The journey will be anything but easy.

The martech market receives an important signal. More and more players are building vertical stacks on video AI. Besides, competition with Runway, Pika Labs, and Google and OpenAI's video models is already fierce. Dotmo will need to find a precise positioning to survive.

Why AI video is so expensive to develop

It's worth understanding the technical context. Generative video models require much higher computational resources than text or image models. McKinsey estimates that training and inference costs for video models are still an order of magnitude higher than language models.

Furthermore, the quality expected by users and brands is sky-high. Generating coherent videos isn't enough: you need outputs ready for distribution on advertising platforms, with precise standards for resolution, timing, and brand safety. So, the gap between a research prototype and a commercial product is still very wide.

Because of this, lots of tech companies are deciding to outsource or separate these teams. Just like what happened with some NLP research divisions in past years, AI video is turning into its own specialized field.

SHM Studio's take: real opportunity or premature hype?

We at SHM Studio we work daily with marketing managers who ask us when and how to integrate AI video into their creative pipelines. The honest answer is: it depends on the use case.

Today, the available AI video tools are handy for specific scenarios. For example, producing creative variants for google ads campaigns or for A/B testing on short video formats. However, for productions requiring brand consistency, recognizable actors, or complex narrative, the limitations remain evident.

Dotmo, if it manages to build a solid commercial product, could close some of these gaps. Specifically, it could do so for the SME segment that lacks the budget for traditional video productions. Therefore, the strategic interest is there. But the product's maturation timeline is still uncertain.

For marketing managers evaluating investments in AI solutions , the advice is to monitor the evolution of Dotmo without expecting ready-to-use outputs in the short term. Likewise, it is worth exploring existing tools today to identify the most suitable use cases for your sector.

Operational implications for those managing content and campaigns

Beyond corporate dynamics, the news has practical implications for those working in Digital marketing and content strategy. Let's look at the most relevant points.

• Video content automation: the separation of teams specialized in AI video accelerates sector specialization. Consequently, over the next 12-18 months we are likely to see new vertical tools, more precise and less generalist.
• Synthetic UGC: one of the most interesting use cases for brands is generating video content that looks like real user-generated content. But platforms are getting better at spotting them, so the quality of the final result will make all the difference.
• Integration with existing stacks: who manages campaigns on Linkedin or on Meta knows how expensive creative production is. Well-integrated AI video tools could significantly reduce the cost per creative variant.
• SEO and video content: Google continues to index and value video content. Therefore, a more scalable video production also has a direct impact on strategies SEO .

In short, AI video is not yet plug-and-play for most Italian companies. However, the market is structuring itself rapidly. Therefore, ignoring it today means finding yourself behind tomorrow.

The still-open site: what to watch in the coming months

Dotmo was just born. Therefore, it is premature to evaluate its product or final positioning. However, there are some signals to monitor closely.

First of all, the funding round. If Dotmo manages to attract significant capital from AI-specialized VCs, it will be an indicator of technical credibility. Next, the choice of partnerships: integrating with existing video distribution platforms or building your own distribution are two paths with very different implications.

Finally, the type of clients Dotmo will work with. If it goes after big brands and enterprise clients, it'll be competing with Runway and Adobe's tools. On the flip side, if it targets creators and SMBs, it could carve out a more accessible, less crowded space. Harvard Business Review has already analyzed how generative AI is redefining corporate creative models — and video is the next front.

To learn more about how to integrate AI tools and content automation into your strategy, you can explore the SHM Studio services or read the in-depth articles on our Blog . Furthermore, the team is available for dedicated consultation through the page contacts .

Besides this, those working on strategies of copywriting and content you'll find it useful to understand how AI video integrates with text production — two increasingly complementary assets in multichannel campaigns. Similarly, those who manage corporate web presence through web solutions will have to consider how generative video content will impact user experience and time spent on the site.