# AI Video Case Studies

<details>

<summary><strong>Early Stage Case: ASML Ad- Midjourney+Stable Diffusion+Runway</strong></summary>

ASML utilized Generative AI (GenAI) technology to create a promotional video.

<mark style="color:red;">**How This Video Was Created:**</mark>&#x20;

This video serves as a prime illustration of the <mark style="color:orange;">AI video production process as of 2023</mark>. Drawing on the official website for details, it seems the journey began with <mark style="color:orange;">Midjourney</mark>, leveraging 1,963 natural language prompts to bring forth 7,852 images. These images underwent subsequent editing and rendering by an impressive ensemble of 900 computers, likely with the aid of <mark style="color:orange;">Stable Diffusion</mark>. The process culminated with <mark style="color:orange;">Runway</mark>, which handled the video editing and compilation, resulting in a video comprised of 25,957 frames. Impressively, each frame demands up to 1000MB of resolution space, showcasing the cutting-edge capabilities in AI-driven video production.

{% hint style="info" %}
This was a method for creating creative videos during the early stages of Generative AI development. Due to the poor performance of various video generation applications up until 2023 and the inconsistency in image generation services, it was the best choice at that time. Nowadays, direct video generation services like Sora, Luma AI Dream Machine, and Runway Gen-3 have significantly advanced. Midjourney also ensures consistency. Whether generating videos directly from text or by first generating images and then videos, both methods now offer better performance and simpler steps. Therefore, using such a complex method is no longer the best option.
{% endhint %}

</details>

{% embed url="<https://youtu.be/OPnCbbLYPV4>" %}

***

<details>

<summary><strong>Case: Ai.lonso</strong></summary>

Ai.lonso is an AI-powered avatar of Formula 1 driver Fernando Alonso, created through a collaboration between ElevenLabs and DeepReel, combining voice cloning technology and AI avatar generation to enhance fan engagement for the Aston Martin F1 team by providing multilingual content on their website.

</details>

{% embed url="<https://x.com/elevenlabsio/status/1844775176279405041?s=20>" %}

***

<details>

<summary><strong>How Intermarché Reimagined Holiday Storytelling with Generative AI</strong></summary>

French retail giant Intermarché has long been celebrated for its cinematic, high-budget holiday commercials. However, for the 2024 festive season, the brand took a bold leap into the future of marketing by launching "L’Amour (Encore)"—a heartwarming campaign created significantly with Generative AI.

#### The Creative Vision

The film follows a lone wolf drawn from the cold wilderness toward the warmth of a festive village. Traditionally a symbol of threat, the wolf is transformed by the aroma of fresh food and the spirit of togetherness. The narrative maintains Intermarché's core brand promise: "Helping you eat better every day," suggesting that even a wild creature can be tamed by the quality of great ingredients.

#### Why It Matters for AI & Business

This campaign serves as a landmark case study for AIGC (AI-Generated Content) in mainstream advertising for several reasons:

* Aesthetic Innovation: Instead of pursuing hyper-realism or traditional 3D animation, the production team used AI to craft a "dreamlike" visual style that feels both poetic and modern.
* Production Efficiency: By integrating AI into the visual effects pipeline, the brand explored new ways to shorten production cycles while maintaining high artistic standards.
* Emotional Resonance: The success of the ad proves that AI is not just a tool for automation, but a medium capable of conveying deep human emotions and brand values.

#### The Bottom Line

Intermarché’s "AI Wolf" ad marks a shift in the industry. It demonstrates that when a strong human-led narrative meets the power of Generative AI, the result is a compelling, cost-effective, and highly memorable brand story.

</details>

{% embed url="<https://youtu.be/Na9VmMNJvsA?si=eYUqErTZsid8DySn>" %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aiandbusiness.com/by-industry-cases/movies-films/ai-video-case-studies.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
