Product visualization plays a crucial role in e-commerce success, yet creating high-quality product videos remains a significant challenge. Recent advancements in AI video generation technology offer promising solutions.
We evaluated leading AI video makers’ capabilities in generating product demonstration videos:
AI video maker benchmark results
Figure 1: Success of the tools in creating videos following the prompts and input images.
Examples from AI video makers
Kling AI KLING 1.6

Figure 2: An example image of a lantern in front of faded lights.
Prompt: Make the lantern’s flame flicker naturally. Add a slight glow effect that shifts with the breeze, keeping the nighttime atmosphere intact.
Output of KLING 1.6:
This video is rated 10/10 for fully meeting all criteria, including prompt accuracy, lighting and shadow, real-world physics, product integrity, and brand-specific details.
OpenAI Sora

Figure 3: An example image of an orange bag with brown straps.
Prompt: Pure white background, soft studio lighting. Smooth 360-degree rotation, starting and ending with front view. Keep bag centered and maintain consistent rotation speed.
Output of OpenAI Sora:
This video is rated as 6/10 due to these issues:
- Prompt compliance: It failed to demonstrate consistency between prompt requirements and the generated output regarding product appearance, environment rendering, and camera movements. (-3 points)
- Preservation of product / brand-specific features: The side clips and the rings on the front are distorted as the point of view is rotated. (-1 point)
Check out our methodology and evaluation metrics to see how we decided on these ratings.
Wan AI

Figure 4: An example image of a perfume bottle.
Prompt: Show a slow rotation of the perfume bottle against a white background. Add a soft mist spray effect while keeping the bottle’s reflections and transparency intact.
Output of Wan AI:
This video is rated 7/10 due to these issues:
- Prompt compliance: The tool failed to generate the video as specified in the prompt. For instance, while the prompt requested a mist spray effect, the resulting video does not depict it. (-3 points)

Figure 5: An example image of a coffee mug.
Prompt: Add soft steam rising from the coffee mug. Keep the motion subtle and natural, with a slight lighting shift for warmth.
Output of Wan AI:
This video is rated 10/10 for fully meeting all criteria, including prompt accuracy, realism, physics, lighting, product integrity, and brand-specific details.
Methodology
Products used
- Kling AI KLING 1.6 (March/2025)
- Wan AI 2.1 (March/2025)
- Kling AI KLING 1.5 (December/2024)
- Hailuo AI I2V-01-live (December/2024)
- Hailuo AI I2V-01-director (March/2025)
- Runway Gen3 Alpha Turbo (December/2024)
- OpenAI Sora (December/2024)
- Veo2.ai (March/2025)
Test Image Classification and Objectives
Our study utilized three distinct categories of product images, each designed to test the specific capabilities of AI video generators:
White Background Products
Purpose: Evaluate dual capabilities
Basic manipulation: Product movement and rotation in a neutral setting
Environmental adaptation: Integration of products into new contexts
Test focus: AI’s ability to maintain product integrity while adding or changing environments.
Contextual Product Images
Purpose: Assess environmental animation capabilities
Scene-to-video conversion accuracy
Maintenance of existing lighting and atmosphere
Adding dynamic elements to an established setting
Test focus: AI’s ability to bring static environmental product shots to life.
Multi-Product Scenes
Purpose: Test complex product relationships and interactions
Inter-product physical interactions
Consistent scale maintenance
Group movement dynamics
Collective lighting effects
Test focus: AI’s ability to handle multiple products while maintaining individual integrity and natural interactions.
This three-category approach enables us to evaluate not only individual product rendering and environment creation but also the AI’s capability to manage complex multi-product scenarios, providing a more complete assessment of real-world e-commerce applications.
Our evaluation metrics are:
Prompt Compliance: (3 points)
Consistency between prompt requirements and generated output for the product
Consistency between prompt requirements and generated output for the environment
Consistency between prompt requirements and generated output for the camera and shooting.
Physical Accuracy: (3 points)
Adherence to real-world physics
Accuracy of object interactions (surface contact, movement)
Lighting and shadow behavior
Product Integrity: (4 points)
Consistency in product appearance throughout the video
Preservation of product / brand-specific features and details
Maintenance of product proportions and scale
Texture, color, and material rendering accuracy
Each generated video is rated out of 10 based on these metrics.
Dataset: We used stock images from pexels.1
What are the issues with AI video generators?
We tried these video production tools to promote a product on e-commerce sites using only its photograph and a prompt, but the outputs showed us that this was not possible.
In most cases, these AI tools could not:
- Communicate accurately to the buyer the product’s features, brand-specific details, size, color, texture, etc.
- Generate a video that is 100% compatible with the prompt.
Tips: To address these issues, we recommend enhancing prompts and contextualizing AI video generators through LLM fine-tuning, contextual RAG, or Agentic RAG.
AI video generators
Product | Price* |
---|---|
Kling AI | Starting from $10/month |
Wan AI | Starting from $20/month |
Hailuo AI | Starting from $10/month |
Runway | Starting from $12/month |
OpenAI Sora | ChatGPT Plus/ChatGPT Pro subscription |
Veo2.ai | Starting from $30/month |
*Tools provide a credit system, and the credits spent depend on many factors, like the resolution, the duration of the video, and the model used in creation.
Kling AI
Kling AI’s KOLORS 1.5 model in image generation introduced the “AI Model” feature, enhancing image quality and portrait aesthetics, which can benefit advertisers and e-commerce users.
Wan AI
Wan AI’s flagship model, Wan 2.1, enables text-to-video, image-to-video, and video editing with cinematic effects.
It supports multilingual text generation (Chinese & English) and runs on consumer GPUs (8.19GB VRAM for 5s 480p videos).
Hailuo AI
Hailuo AI is designed for artists and creators to transform static images into animated videos.
Its key features include Image to Video (I2V), which animates 2D images with smooth motion; Text to Video (T2V), which converts text descriptions into video content; and Live Animation (I2V-01-Live), which creates fluid, lifelike animations from illustrations.
Runway ML
Runway ML allows users to train custom models to help reflect corporate identity.
OpenAI Sora
Sora can be used with the ChatGPT Plus and Pro subscriptions, with an increased video generation limit in the Pro.
Veo2.ai
Veo2.ai offers tools for automated video analysis, visual search, object detection, and scene understanding.
CapCut Commerce Pro
CapCut Commerce Pro takes product images, text descriptions, and brand assets as input and uses AI to generate promotional videos.
The tool applies templates, motion effects, auto-captioning, and voiceovers to create engaging content optimized for platforms like TikTok, Instagram, and e-commerce stores.
Note: We did not include CapCut Commerce Pro in our benchmark study because, unlike other AI video generators we tested, it does not create videos from an image and a prompt.
Instead, CapCut relies on structured templates and automated editing features, making its workflow fundamentally different from the generative AI approach used by other tools.
FAQ
What are AI video maker tools?
AI video production tools include AI video generators, video content creation tools, and AI-driven video editing tools.
These tools enable businesses to create high-quality videos, personalize content, and optimize video performance. An AI video maker can help businesses get rid of the costs and create more abstract videos. Video creation can take just minutes with the help of these tools. AI image generators and video editors have evolved into advanced AI tools for creating videos.
Video projects can now incorporate personalized videos and explainer videos, enhanced with AI voices. Background music can be added to enrich the content, and instant voiceovers can be created using text-to-speech technology. These other elements make it possible to produce diverse types of content with varying complexity levels.
Text prompts and picture inputs can be used in the generation process. AI video generator simplifies generating stunning videos.
What are the benefits of using AI-generated video for business?
The use of AI-generated video offers several benefits for businesses, including cost-effectiveness, personalized content creation, and scalable production. AI-generated video content reduces the need for extensive manual labor and expensive resources. AI algorithms can automate various aspects of the video creation process, such as video editing, saving businesses valuable time and resources. To generate AI videos, companies can use an AI video generator app.
What are the potential challenges and solutions in implementing AI video creation?
While AI video creation offers numerous benefits, there are also challenges that businesses may face when implementing this technology. Businesses must ensure they have robust data privacy policies in place and adhere to legal regulations about data protection. Implementing AI-generated video production may require technical expertise and investment in AI infrastructure. Studio-quality videos may be hard to achieve with AI-powered video generator tools. To create AI videos, text-to-video, picture-to-video, or both can be used. Companies can also use AI avatars in their video clips with the help of AI video generators.
Further reading
Discover more on generative AI capabilities, use cases, and tools by checking out:
- Top 100+ Generative AI Applications with Real-Life Examples
- Top 35+ Generative AI Tools by Popularity & Category
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