CGI vs AI: Revolution or Rivalry in Digital Art?

The trend toward using AI is skyrocketing. According to SurveyMonkey, 50% of content creators are already utilizing AI tools in their work. This confirms that artificial intelligence can serve as an additional tool for producing visual content. Let’s take a closer look at whether AI can be applied to CGI.

How Is Artificial Intelligence Used in CGI?

Artificial intelligence helps optimize workflows and reduce time spent on specific stages of CGI production. AI models can be applied in the following areas:

1. Concept and Pre-production. Based on text prompts, AI can gather references and suggest scenarios, sketches, color palettes, and visual styles for a CGI video. This approach saves time for artists and designers during the early concept development stage.
2. Initial Model Generation. AI can generate a basic 2D model of a mascot, which a CGI specialist can then refine by adding character traits and visual details, such as eye shape, lips, cheekbones, nose, hairstyle, and more.
3. Automation of Technical Processes. AI models simplify tasks like rotoscoping and keying. Removing unwanted objects or layering frames no longer takes hours.
4. Scalability. AI can be used for creatives where high emotional impact or premium quality isn’t critical. For example, informational city banners or high-volume visuals.

It’s important to understand that AI in CGI is not a replacement for specialists. It’s a powerful tool to enhance their capabilities, especially when working under tight deadlines or managing large volumes of content.

What Are the Limitations of Artificial Intelligence?

Despite the increasing popularity of AI-driven CGI, the technology still has many limitations, especially when it comes to producing high-quality visuals with charisma and emotional depth. Every CGI product must fulfill a specific narrative goal. And AI often falls short in that area.

Key limitations of AI in CGI

1. It can’t deliver a polished final product. Any visual generated by AI requires refinement. While AI can produce aesthetically pleasing images, its algorithms don’t grasp charisma or the subtleties of human perception.
2. Lacks charisma and emotional depth. AI models often produce “smooth” content that lacks liveliness and atmosphere. Algorithms are unable to grasp emotional tension, the element that makes a CGI video engaging and memorable.
3. Cannot build a visual climax. CGI artists craft scenes with an understanding of pacing and emphasize key moments to enhance impact. AI may overlook critical details in the visual narrative.
4. Doesn’t always meet the script or directorial intent. Algorithms rely on preset patterns and templates. AI may misinterpret a prompt and generate results that don’t align with the creative vision.
5. Editing AI-generated 3D models is challenging. Modifying an already generated model can be resource-intensive. Adjusting scene geometry, layers, or movement is much easier within a professional CGI pipeline. You can learn more about CGI tools here.

CGI vs AI: Coca-Cola’s AI-Generated CGI Video

Coca-Cola released a New Year’s campaign video created entirely by artificial intelligence — and it sparked mixed reactions. On the one hand, the visuals were impressive. On the other hand, the video lacked a festive feel and emotional depth. It followed a generic AI-generated template and likely didn’t leave a lasting impression.

This is a clear reminder for brands weighing CGI vs AI: visual perfection alone isn’t enough. What truly matters is the idea, the mood, and a human touch. Emotional engagement remains the key to effective advertising — and that’s something AI still struggles to deliver.

What Are the Future Trends in AI for CGI?

Currently, there’s a clear trend: AI models are capturing a significant share of the market, and the content they generate is largely stream-based and mass-produced. While AI still has limitations, it’s expected to improve through feedback-driven refinement.

Key future trends in AI for CGI include:

• Enhanced audio support. AI will be able to clean up audio tracks more effectively, clarify voice recordings, and adapt sound for different devices and formats.
• Noise Reduction in Digital Images. AI will be able to fix digital artifacts, remove unwanted shadows, enhance image details, and restore frames captured in poor lighting conditions. Disney Research, for instance, has developed an AI-powered noise reduction tool called AI Denoiser.

CGI vs AI: Key Takeaway

AI models will continue their integration into CGI production workflows. That’s why artists need to be open to innovations and learn how to utilize AI effectively. Combining expertise in CGI with AI tools will lead to stronger results.

At Acquisition.mobi, we create bold and memorable CGI visuals for advertising, games, film, and show content. From creative concepts to final rendering, we turn bold ideas into visual stories that grab attention from the first frame.