Exploring Google’s Veo 3 for GenAI Videos

Google’s Veo 3 represents a significant leap forward in AI video generation, pushing the boundaries of what’s possible in creative content creation. Unveiled on May 20th at Google I/O 2025, this DeepMind-developed model is lauded for its ability to produce high-resolution, often 4K, videos complete with natively generated audio, including sound effects, ambient noise, and even synchronized dialogue.

Beyond mere visual fidelity, Veo 3 excels in areas like real-world physics simulation, consistent character portrayal across multiple clips, and advanced cinematic controls, allowing users to specify camera movements, angles, and framing. Its integrated audio capabilities and improved prompt adherence set a new standard, empowering filmmakers and storytellers to bring their visions to life with unprecedented realism and ease.

Getting Wild with Veo 3:
A Weekend of AI-Powered Cinematic Shenanigans

We’ve been putting Google’s fancy new Veo 3 through its paces over the weekend, experimenting with our Groove Jones mascot, and the results are frankly pretty wild! Gone are the days of feeling like we’re feeding an AI slot machine; with the proper prompt structure (and admittedly, a healthy dose of around 5,000 credits), we started to achieve genuinely controllable, even cinematic, outcomes. What’s more, we experienced those delightful ‘happy accidents’ you’d expect if you were actually on set, shooting a live-action piece. Case in point? We somehow manifested a flying bear, inexplicably adorned in tuxedo-cutoff sleeves and mocap marker shorts. And yes, that happened!

veo 3

Now, is Veo 3 fully ‘production-ready’? No, not yet. It is still experimental. You’re still going to burn a lot of expensive credits before you get that shot that’s perfect, and you can’t iterate on it if you want to change one or two things, it will be new every time you regenerate. It still retains its endearing workflow quirks, as well as occasional moments of creative defiance. However, the speed at which this technology is advancing is truly astonishing, and it’s becoming production-ready rapidly. We genuinely feel that the era of ‘creativity at the speed of thought’ is just right around the corner for us and our clients.

Creativity at the Speed of Thought

Our most successful experiments leveraged a specific prompt structure we found highly effective. It involves breaking down the desired shot into clear components: defining the POV (e.g., ‘POV selfie-style, handheld by a grizzly bear in a black tux’), setting the scene (‘A glowing, futuristic creative lab’), establishing a clear tone (‘Genius bear meets creative tour guide’), and even delivering a punchline (‘“You think bears just hibernate? Nah… we innovate.”’). This approach emphasizes clear POV, defined motion, modular scenes, and an intentional emotional tone – essentially, it’s filmmaking principles applied directly to AI direction.

GenVFX-Veo3-Example
Our current tech stack for these exciting experiments includes Veo 3 for video generation, ElevenLabs for advanced audio, and a custom project in ChatGPT Pro with custom system instructions for refining our prompts and ideas. The synergy between these tools is unlocking truly exciting possibilities.

GenVFX-Veo3-Example

Why Consider GenAI Videos

People are rapidly adopting Generative AI (GenAI) video tools because they offer unprecedented speed, efficiency, and creative possibilities in content creation. These tools leverage advanced AI models to generate, edit, and customize videos from simple inputs like text prompts, images, or even existing video footage. Here’s a breakdown of why and how people are using GenAI videos:

Speed and Efficiency: GenAI dramatically reduces the time and effort traditionally required for video production. Tasks that once took days or weeks, like creating a marketing video or an explainer, can now be done in hours or even minutes. This allows for faster responses to market trends and quicker content deployment.
Cost Reduction: By automating many aspects of video creation (scripting, voiceovers, animation, editing), GenAI tools significantly cut down on production costs, making high-quality video content accessible to a broader range of creators, businesses, and independent artists who may not have the budget for traditional production.
Accessibility and Democratization: GenAI lowers the barrier to entry for video creation. You no longer need extensive technical expertise, expensive equipment (cameras, lighting, studios), or specialized software knowledge to produce polished videos. Anyone with an idea and a text prompt can generate compelling visual content.
Enhanced Creativity and Experimentation: While some fear that automation might stifle creativity, GenAI often acts as a creative stimulant. It enables users to rapidly prototype ideas, experiment with various styles, and explore concepts that might have been too costly or time-consuming using traditional methods. The ability to generate variations quickly fosters innovation.
Scalability: GenAI enables the efficient production of large volumes of video content. For example, sales teams can create hundreds of personalized outreach videos, or L&D departments can automate training content for distributed teams, all without overwhelming internal resources.
Multilingual and Localized Content: Many GenAI video platforms can automatically translate scripts, generate voiceovers with local accents, and adjust avatar speech to match various languages, making content universally accessible and easily localized for different audiences.

Current GenAI Video Limitations

High Token Costs: Generating video with models like Veo 3 isn’t cheap. We burned through about 5,000 tokens ($50) in a weekend just experimenting. Each revision costs more, so iterating creatively can get expensive fast.
No Isolated Iterations (…yet): If you want to tweak one part of a shot—say, change the background or reframe the camera—you often have to regenerate the entire scene. There’s no direct way to “inpaint” a video element like you can with AI images… but that’s coming.
Inconsistent Voices: Native voices in GenAI videos are often unstable—tone, pacing, and delivery can shift between takes. The fix? Export the VO and reprocess it with tools like ElevenLabs, where cloned voices can bring consistency.
Character Drift: Keeping characters visually consistent across shots is still a struggle. Even when repeating the same prompt, things like face shape, clothing details, or proportions can change. Some people work around this by generating a keyframe image first or locking down descriptions with hyper-specific language.
Physics Quirks: Gravity’s weird. Motion timing can be off. You’ll see floaty steps, odd inertia, or characters that hover unexpectedly. That said, some shots do nail it, and the models are improving fast.
Ethical and Legal Uncertainty: The use of training data, voice cloning, and character likeness still raises concerns regarding copyright, consent, and intellectual property. It’s a gray zone, especially for commercial work with big-profile clients, and creators should tread carefully and be transparent.

How People are Using GenAI Videos:

Marketing and Advertising:
- Creating engaging social media content (shorts, reels).
- Producing product demos, explainers, and promotional videos.
- Generating personalized video ads tailored to specific consumer data.
- Rapidly adapting to market trends and launching campaigns faster.
Education and Training:
- Converting complex textual data into engaging visual narratives for e-learning.
- Automating internal training videos for employees.
- Creating educational content with AI avatars and text-to-speech in multiple languages.
Content Creation and Entertainment:
- Generating short films, animated sequences, and conceptual visuals.
- Assisting in game development for creating detailed scenes, realistic environments, and character movements.
- Repurposing long-form content (webinars, podcasts) into short, shareable video clips.
- Experimenting with unique visual styles and effects.
Business and Corporate Communications:
- Producing internal communications videos.
- Creating professional presentations with AI avatars.
- Developing FAQ videos and customer service explainers.
Video Editing and Post-Production:
- Automating tedious tasks like scene detection, trimming clips, adding transitions, and removing filler words.
- Enhancing video quality (resolution, noise reduction, sharpening).
- Applying advanced visual effects, including rotoscoping and object removal.
- Generating subtitles and dubbing videos into various languages with lip-sync.

While the technology is still evolving and faces challenges like maintaining authenticity and ethical considerations, the widespread adoption of GenAI in video creation is fundamentally reshaping how content is produced and consumed across numerous industries.

What Companies are Developing GenAI Video Tools

The field of Generative AI (GenAI) video is rapidly evolving, with numerous companies, both large tech giants and innovative startups, releasing impressive tools and capabilities. Here are some of the key players and their notable contributions:

Major Tech Companies:

Google (Alphabet): A significant force in GenAI video, as evidenced by their Veo models (like the recently unveiled Veo 3). Google has also developed models like Lumiere and VideoPoet, showcasing their ongoing research and development in text-to-video generation, cinematic controls, and integrated audio.
OpenAI: Known for Sora, their highly anticipated text-to-video model that has garnered significant attention for its ability to generate realistic and coherent videos from simple text prompts, including complex scenes with multiple characters and specific movements. Sora is integrated with ChatGPT Plus and Pro.
Meta: While perhaps not as public with dedicated video generation platforms as some others, Meta is heavily invested in integrating generative AI into its social media platforms (Facebook, Instagram, WhatsApp) and has been developing models like Make-A-Video.
Adobe: With Adobe Firefly, Adobe is bringing generative AI capabilities directly into its creative suite. Firefly’s video model allows users to generate b-roll footage and other video elements from text or image prompts, with a focus on commercial safety and ease of use for creative professionals.
Microsoft: Microsoft is deeply integrated with OpenAI’s technologies and also has its own initiatives like Microsoft Copilot Studio, which allows businesses to create AI-powered assistants that can be applied to various tasks, including potentially aspects of video content automation.