- The timeline: from internal team to independent company
- Who wins and who loses in this scenario
- Why AI video is so expensive to develop
- SHM Studio's take: real opportunity or premature hype?
- Operational implications for anyone running content and campaigns
- The construction site is still open: what to watch in the coming months
Snap has announced the spinoff of its in-house AI video team. The new entity is called Dotmo. It is made up of Snap employees who are leaving the parent company to focus exclusively on developing AI-based video technology.
So this is not just an internal reshuffle. It's a clear signal: the cost of AI video weighs too heavily on a social-first company like Snap. Spinning the team off lets it seek dedicated funding and build a vertical product. But for Italian marketing managers, the key point is something else. Dotmo could become an independent player in the content creation automation market, with direct implications for video campaigns, synthetic UGC and scalable creative production.
At SHM Studio, we are watching these moves closely. AI video is maturing fast. And the tools that come out of it are increasingly entering the digital marketing pipelines of Italian SMEs. In short, Dotmo is still a work in progress, but it deserves a place on your strategic radar.
The timeline: from internal team to independent company
On June 18, 2026, TechCrunch reported the official news. Snap has decided to separate its AI video research and development group. The new company is called Dotmo. It is made up of current Snap employees who are leaving the social company's structure to found an independent entity.
The stated reason is clear: costs. Developing AI video models requires enormous infrastructure. It also requires specialized teams that rarely find their natural habitat inside a company focused on Snapchat and social advertising. The spinoff is a rational choice, not an escape.
This isn't the first time Snap has taken this path. In the past, the company has already separated internal units to reduce operational weight. This move is different, though: 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
In terms of market balance, Dotmo's birth has effects on several levels. Let's go through them one by one.
Snap lightens its balance sheet. As a result, it can focus resources on its core advertising business. But it gives up a technology asset that, once mature, could have set it apart from competitors. It's a defensive move, not an offensive one.
Dotmo gains operational freedom. As an independent entity, it can raise capital from AI-focused VCs, partner 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 road ahead will be anything but easy.
The martech market gets an important signal. More and more players are building vertical stacks around AI video. Competition with Runway, Pika Labs and the video models from Google and OpenAI is already fierce. Dotmo will need a very clear positioning to survive.
Why AI video is so expensive to develop
The technical context is worth understanding. Generative video models need far more computing power than text or image models. McKinsey estimates that training and inference costs for video models are still an order of magnitude higher than for language models.
On top of that, users and brands expect very high quality. Generating coherent videos isn't enough: you need outputs ready for distribution on ad platforms, with precise standards for resolution, timing and brand safety. The gap between a research prototype and a commercial product is still very wide.
That's why many tech companies are choosing to outsource or spin off these units. Much like some NLP research divisions in recent years, AI video is becoming a specialized field of its own.
SHM Studio's take: real opportunity or premature hype?
At SHM Studio, we work every day with marketing managers who ask us when and how to bring AI video into their creative pipelines. The honest answer: it depends on the use case.
Today, the AI video tools available are useful for specific scenarios. For example, producing creative variants for Google Ads campaigns or for A/B tests on short video formats. But for productions that demand brand consistency, recognizable actors or complex storytelling, the limits are still obvious.
If Dotmo manages to build a solid commercial product, it could close some of these gaps. In particular, it could do so for SMEs that don't have the budget for traditional video production. So the strategic interest is there. But the product's timeline to maturity is still uncertain.
For marketing leaders weighing investments in AI solutions, our advice is to follow Dotmo's progress without expecting ready-to-use output in the short term. At the same time, it's worth exploring existing tools today to identify the use cases that best fit your industry.
Operational implications for anyone running content and campaigns
Beyond the corporate dynamics, the news has practical implications for anyone working in digital marketing and content strategy. Here are the most relevant points.
- Video content automation: spinning off teams specialized in AI video speeds up specialization in the sector. As a result, over the next 12-18 months we're likely to see new vertical tools that are more precise and less generalist.
- Synthetic UGC: one of the most interesting use cases for brands is generating video content that mimics the authenticity of user-generated content. However, platforms are refining their detection systems. So output quality will be the deciding factor.
- Integration with existing stacks: anyone running campaigns on LinkedIn or Meta knows how costly creative production is. Well-integrated AI video tools could significantly cut the cost per creative variant.
- SEO and video content: Google continues to index and reward video content. So more scalable video production has a direct impact on SEO strategies too.
In short, AI video is not yet plug-and-play for most Italian companies. But the market is taking shape quickly. Ignoring it today means being behind tomorrow.
The construction site is still open: what to watch in the coming months
Dotmo has only just been born. It's too early to judge its product or its final positioning. Still, there are a few signals worth watching closely.
First, the funding round. If Dotmo manages to attract significant capital from AI-focused VCs, it will be a sign of technical credibility. Next, the choice of partnerships: integrating with existing video distribution platforms or building its own distribution are two paths with very different implications.
Finally, the type of customers Dotmo will serve. If it targets enterprises and big brands, it will go head to head with Runway and Adobe's tools. If it targets SMEs and creators, 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 frontier.
To learn more about integrating AI and content automation tools into your strategy, explore the SHM Studio services or read the insights on our blog. Our team is also available for a dedicated consultation through the contact page.
If you're working on copywriting and content strategies, you'll also find it useful to see how AI video fits with text production, two increasingly complementary assets in multichannel campaigns. Likewise, if you manage your company's web presence through web solutions, you'll need to consider how generative video content will affect user experience and time on site.
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