The company said it will start using internal detection systems from May 2026 to identify videos containing what it described as “significant photorealistic AI” content.

When creators fail to disclose that material, YouTube will now add the label automatically.

The update also changes where viewers see those warnings. Instead of hiding them inside video descriptions, YouTube will place labels directly below long-form videos and over Shorts, making them easier to spot.

YouTube has required creators since 2024 to disclose content made with AI tools when videos could realistically be mistaken for real people, places or events. However, content that was clearly fictional, animated or unrealistic did not need the same treatment.

Now, the company says it wants a more reliable system as AI video tools become harder to distinguish from real footage.

“We’ve heard consistently from our community that they value transparency when it comes to generative AI content,” YouTube said.

“That’s why since 2024, we’ve been labeling content when creators disclose they’ve used AI tools.”

The platform said the policy itself has not changed, but enforcement is becoming more active as AI-generated video quality improves.

The announcement follows the launch of Google’s Gemini Omni models at the company’s developer conference last week. Google said the models can generate highly realistic videos while showing an understanding of subjects including physics, science, history and culture.

Under the new system, creators will still be expected to disclose AI-generated content themselves. However, YouTube explained it will step in when its systems detect realistic AI content that has not been labelled.

“If a creator doesn’t specify whether or not they used AI, but our systems detect significant photorealistic AI use, we will now automatically apply a label,” the company said.

Creators who believe their content was wrongly flagged will be able to update the disclosure status through YouTube Studio. Still, YouTube said labels will remain permanent in some situations.

That includes videos produced using YouTube’s own AI tools such as Veo and Dream Screen. The same applies to videos carrying C2PA metadata showing they were fully generated with AI systems.

C2PA is an industry standard designed to help identify AI-generated and digitally altered media. Companies including OpenAI, Nvidia, Kakao and Eleven Labs have backed the standard in recent months.

YouTube is also changing how labels appear across the platform.

For long-form videos, labels will now be directly below the video player and above the description section. On Shorts, viewers will see them as overlays on the video itself.

The company said labels for unrealistic or lightly edited AI content will still appear only inside the expanded description section.

“By moving these labels on to the main stage, viewers get the context they need at a glance,” YouTube said.

The changes align with YouTube’s expansion of other tools aimed at detecting manipulated content. The company recently increased access to its AI deepfake detection system, allowing adults to scan the platform for videos that may contain their likeness.

At the same time, YouTube continues adding AI features across its services, including AI-generated video summaries, playlist tools for YouTube Music, interactive search functions and creation tools for creators.

Despite the labelling system, YouTube said the presence of an AI label will not affect recommendations or whether creators can make money from their videos.

“It’s important to note that a disclosure label alone does not change how a video is recommended or whether it’s eligible to earn money,” the company said.

The round was co-led by New Era Capital Partners and Osage Venture Partners, with additional participation from 97212 Ventures, Maccabee Ventures, Ginossar Ventures, Itai Tsiddon, and other strategic investors.

Unlike traditional text-only social listening tools that rely heavily on keyword searches, Dig was designed from the ground up as a video-first, LLM-native platform. By understanding briefs and research questions, Dig identifies more than 90% of relevant content across video, images, and text; automatically filtering out noise by mapping narratives instead of keywords. 

The platform also flags policy violations such as deepfakes, disinformation, or harmful content, alerting communications teams in real time and recommending next steps before issues escalate.

“Social video builds and breaks reputations faster than any other medium. Our mission is to give brands immediate, precise visibility into those narratives, along with the tools to respond before risk becomes a crisis,” said Ofer Familier, Co-founder & CEO of Dig. 

“With the backing of New Era, Osage, and our other partners, we are doubling down on product innovation and scaling Dig’s impact for marketing, communications, and insights teams globally.”

Customer Growth and Market Context

Dig has rapidly gained traction among luxury, consumer packaged goods, fashion, and Fortune 500 technology companies. Customers deploy Dig across brand management, consumer insights, communications, and social media teams, leveraging the platform for:

• Early detection of viral narratives
• Brand perception benchmarking
• Dynamic customer segmentation
• Campaign and narrative impact analysis

The rise of short-form video has transformed the media sector. Platforms such as TikTok have fuelled the “video takeover” of social media, with 2025 marking the first year in which more than half of all social media posts are video. 

This trend is accelerating with the emergence of generative video platforms like Veo-3, leaving many brand and insights teams exposed to fast-moving risks and consumer signals without automation.

Investor Perspectives

“We’re excited to continue backing Dig as they define the future of social video intelligence. When we first invested at Seed, the team predicted that video would eclipse text as the internet’s primary language,” said Ran Simha, managing partner, New Era Capital Partners. 

“Their growth to more than 70 enterprise deployments in under 18 months proves that thesis. Dig is helping brands transform social video from an unpredictable risk into a strategic growth channel.”

“Dig combines computer vision depth with a business model designed for Fortune 500 security and ROI standards,” added Nate Lentz of Osage Venture Partners. “The speed at which enterprises move from proof-of-concept to production is unlike anything we’ve seen in market intelligence software.”

Next Phase of Growth

Dig will use the new capital to:

• Expand global sales and marketing
• Broaden coverage across emerging video and messaging networks
• Advance its proprietary AI stack, including in-house large language models that deliver up to 100x cost efficiency compared to off-the-shelf alternatives.