Sora 2 and Veo 3: using AI video in brand marketing in 2026

In 2026 AI video moved from "wow factor" phase to "operational tool" phase. Sora 2, Veo 3 and Runway produce videos that 2 years ago would have been indistinguishable from cinematic productions. For brands this means one thing: understanding where to use them and where not is the difference between multiplying creative production or wasting budget on bad videos no one will watch.

In this guide we tell you what really works, what's still vendor marketing, and how to integrate AI video into brand production without replacing what already works. It's the same approach we apply in video projects managed by +Click, where we combine AI and traditional production.

#What Sora 2 and Veo 3 really do in 2026

Let's start from basics without selling smoke. The two main models today (Sora 2 from OpenAI and Veo 3 from Google DeepMind) generate video from text prompts, in FullHD or 4K quality, 8-30 second clip duration, with synchronised audio (dialogue, music, effects).

What they do well: landscapes and environments, generic product animations, atmospheric scenes, cinematic transitions, recreating specific visual styles (70s, noir, cyberpunk), complex camera movements (dolly, crane, drone).

What they still do poorly: character consistency across different clips, close-up human hands (the old problem persists), specific recognisable products (a shoe brand doesn't reproduce identically), natural Italian dialogue with perfect lip sync, real material textures (wood, leather, specific fabrics).

#Sora 2 vs Veo 3 vs Runway: practical differences

Three main players, each with strengths. Let's see them without fanboyism.

Sora 2 (OpenAI)

• Main strength: physical realism and light management. "Real" scenes look real.
• Limits: less skilled on stylised animations, higher generation cost.
• Availability: inside ChatGPT Plus/Pro or via OpenAI API.
• Price: $0.30-0.80 per second of generated video depending on quality and resolution.
• Ideal for: luxury brands, aspirational videos, premium ads where realism matters.

Veo 3 (Google DeepMind)

• Main strength: integrated audio (music, dialogue, effects) generated together with video.
• Limits: more verbose prompts, slightly less realistic than Sora 2 in "real" scenes.
• Availability: inside Vertex AI (Google Cloud) or via Gemini API.
• Price: $0.20-0.60 per second, cheaper than Sora 2 at equal duration.
• Ideal for: videos with native audio, advertising stories with dialogue, educational content.

Runway (Gen-4 and successors)

• Main strength: advanced integrated editing tool (motion brush, camera control, lipsync).
• Limits: quality slightly below Sora and Veo on pure realism, but better for control.
• Availability: runwayml.com web platform with $15-95/month plans.
• Price: included in monthly plan (credits), no per-second like Sora/Veo.
• Ideal for: projects needing lots of manual editing, lip sync on generated faces, precise control.

#The 6 real use cases for brands

Where AI video is bringing concrete value in brand projects in 2026.

1. Assets for short-form ads (Reels, Shorts, TikTok)

The #1 use case for economic impact. Producing 20 videos at 8-15 seconds per week to test different hooks on Meta Ads would cost €2,000-5,000 with traditional production. With AI video cost drops to €100-300 for 20 videos. The value isn't the single video, it's the speed of creative testing. Covered in the video marketing on social media playbook.

2. B-roll and transition scenes

In a real product video shot in studio, you need contextual B-rolls (landscape, atmosphere moments, transitions). Shooting those scenes can cost €500-1,500 per outdoor shoot day. Generating them with AI in coherent quality: €30-80 total. The real product stays real (shot in studio), the surroundings are AI.

3. Mock-up videos for pitches and proposals

When you present a proposal to a client or investor, showing a mock-up video of the final product/service makes a difference. Before motion graphics cost €1,500-4,000. With AI you generate a mock-up video in hours at low cost. It's not the final video, it's the "pitch video" that sells the idea.

4. Video localisation for different markets

The same brand wants a video with Italian visual setting for Italian market, Scandinavian for Northern European market, Mediterranean for Southern Europe. Shooting three versions traditionally: €15,000-30,000. Generating them with AI maintaining the message: €500-1,500 total.

5. Brand storytelling with fantastic elements

Brands selling "magical" products or immersive experiences (toys, cosmetics with effects, food experience) can use AI for scenes impossible to film. A cosmetic transforming into butterflies, food floating, a surreal travel experience. Things that 5 years ago required VFX from premium agencies.

6. Low-cost educational content

Short tutorials, concept explanations, animated infographics. Sectors like finance, health, education need constant content that explains visually. AI video lets you scale weekly tutorial production at manageable cost.

#Costs, licences and commercial use rights

Critical point often ignored by vendors. Understanding commercial use rights of AI-generated videos is fundamental before planning high-visibility campaigns.

OpenAI Sora 2

Videos generated with Sora 2 are owned by the user who generates them, with commercial licence included in Plus and Pro plans. Restrictions: no use for disinformation, illegal content, unauthorised deepfakes of real people. The user is responsible for compliant use. For enterprise use (above $500/month spend) there are SLAs and dedicated support.

Google Veo 3

Videos generated with Veo 3 (via Vertex AI) are owned by the user, with standard commercial licence. Google reserves the right to use anonymised prompts and output to improve the model, opt-out available for enterprise customers. Stricter on potentially copyright-infringing content (e.g. "Disney-style" generation automatically filtered).

Runway

Runway videos are owned by the user with commercial licence included in all paid plans (Standard, Pro, Unlimited, Enterprise). Free plans have watermark and commercial use limitations. For any business use, the Pro plan at $35/month is the recommended minimum.

#Prompt engineering for AI video: 7 rules

The difference between a disappointing AI video and a spectacular one is in the prompt. Seven concrete rules we apply in our projects.

1. Start from visual genre: "cinematic", "documentary style", "60s film", "luxury commercial". Genre sets the overall style.
2. Specify the subject in detail: not "a woman walking", but "a woman in her thirties, brown hair in the wind, beige linen jacket, walking on a Mediterranean beach at sunset".
3. Describe camera movement: "slow dolly forward", "low angle crane shot", "static wide shot". Movement is one of the factors separating professional videos from home videos.
4. Define light: "golden hour soft light", "harsh midday sun", "moody studio lighting from left". Light is 60% of visual feeling.
5. Specify setting: location, objects, context. "Mediterranean villa terrace at sunset, infinity pool, palm trees in the distance, marble floor".
6. Add technical notes: "shot on Arri Alexa, 35mm lens, shallow depth of field, 24fps". AI responds better to professional references.
7. Iterate: the first output is rarely perfect. Change one parameter at a time, save prompts that work to build a style library.

#Limits nobody tells you in demos

OpenAI and Google demos show you the 5 best videos. Operational reality is different. Seven real limits to consider before basing a campaign on AI video.

• Cross-clip consistency: two videos generated with identical prompts still have visible differences. If you need 10 clips in sequence with same character, it's still hard.
• Human hands: the persistent video model problem. Close-up hands often have extra fingers, unnatural postures, deformities.
• Specific products: if you have a product with unique design (e.g. a chair with distinctive line), AI doesn't reproduce it identically. It sees "generic chair".
• Italian dialogue: Italian lip sync and prosody are still behind English. For serious spoken dialogue you need post-production dubbing.
• Visible branding: specific logos and texts (e.g. your brand logo on a t-shirt) don't reproduce correctly. They need adding in post.
• Narrative continuity: a story with 4 logically connected scenes still requires manual editing to tie generated clips together.
• Post-production work: even the best AI videos need editing: colour correction, grading, audio mix, eventual frame corrections. Not "ready from prompt to audience".

#Operational workflow: integrating AI video into production

The workflow we apply in +Click projects to integrate AI video without compromising brand quality.

Phase 1: strategy (never start from the tool)

Before touching Sora or Veo, define: what videos the brand needs (hero brand video vs short-form ads vs B-roll), what percentage of video can be AI without compromising identity, where AI adds value vs where authenticity of real production makes the difference. Content plan must guide tools, not vice versa.

Phase 2: asset mix

Typical mix that works for mid-size brand: 70% AI video assets for ads and social at volume, 25% traditional production for hero content and brand story, 5% UGC or influencer content. Distribution changes by sector: fashion ecommerce uses more traditional production for products, home gadget ecommerce can use 90% AI.

Phase 3: quality control before publishing

Every AI video passes through QC checklist before going live: no visible deformed hands, no wrong branding, professional audio added in post, coherence with brand visual guidelines, copy adapted to channel. Without structured QC, even the fastest workflow produces content that damages the brand.

Phase 4: integration with automation

To really scale, AI video must be integrated in automated workflows. Example: brief generated by n8n from a Notion trigger, structured prompt sent via API, video generated, saved in shared Drive, notification to video editor for QC, automatic posting in approved channels. Described in the AI marketing automation with n8n and Voiceflow guide.

#When NOT to use AI video (and rely on traditional production)

AI video isn't universal. Five scenarios where traditional production remains better or necessary.

1. Hero brand videos lasting 2+ years: traditional production investment is justified by longevity. AI hero video ages visually more quickly.
2. Storytelling with real brand people: videos with founder, employees, real customers. Authenticity can't be replicated with AI without damaging trust.
3. Products where texture/materials are fundamental: jewellery, luxury watches, artisan leather goods. Difference between reality and AI is still visible and damaging for luxury positioning.
4. Events and social proof: real weddings, corporate events, celebrations. They document moments, can't be recreated.
5. Regulated sectors: pharmaceutical, finance, health. Video must show verifiable realities and often has strict legal requirements on visual content.

Real cases where traditional production stays winning: Hotel Don Diego with professional drone and five-star interior shoots, Villa Pacieri with drone video of the villa for events/wedding segment. The reality shown of existing locations doesn't get replaced with AI without losing conversion.

AI video is a tool, not a strategy. Those using it to replace human creativity make mediocre content. Those using it to amplify human creativity multiply brand production.

— Niccolò Giuseppetti, founder +Click

#The 5 most common errors in AI video projects

1. Using AI for everything: produces uniformly mediocre content. Mix AI and traditional production.
2. Generic prompts: "nice video of my product" doesn't work. You need specific structured prompts.
3. Publishing without QC: even the best AI model has occasional glitches. Manual QC stays necessary.
4. Ignoring Italian limits: spoken Italian and specific Italian brands are still poorly handled. Plan accordingly.
5. Underestimating post-production: AI video is raw material, not finished product. Colour, audio, grading stay necessary.

Starter pack to begin AI brand video

1. Runway Pro account ($35/month): most versatile tool to start.
2. Sora subscription via ChatGPT Plus ($20/month) for realistic experiments.
3. Adobe Premiere or DaVinci Resolve for post-production.
4. Structured prompt library for brand (50-100 tested and saved prompts).
5. Visual brand guidelines shared with prompt generators.
6. Pre-publication QC checklist (hand check, brand, audio, coherence).
7. Defined workflow with clear responsibilities (who generates, who QCs, who publishes).

#FAQ AI video marketing