Coca-Cola’s latest holiday ad, created with artificial intelligence, has been met with widespread criticism, with many calling it a ‘sloppy eyesore’. According to a recent survey, 62% of marketers believe that AI-generated content is not yet on par with human-created content.
The use of artificial intelligence in advertising is on the rise, with 75% of marketers planning to incorporate AI into their marketing strategies by 2025. However, the quality of AI-generated content remains a concern.
In this comprehensive guide, we will explore the use of artificial intelligence in advertising, including its benefits and drawbacks, and provide a step-by-step guide on how to create effective AI-generated content.
The Rise of AI in Advertising
Current State of AI in Advertising
The use of Artificial Intelligence (AI) in advertising has seen a significant surge in recent years. According to a recent study, AI adoption rates vary across different industries. The following table compares AI adoption rates in different sectors:
| Industry | AI Adoption Rate |
|---|---|
| Advertising/Marketing | 43.8% |
| IT/Technology | 35.4% |
| Finance/Banking | 28.5% |
| Healthcare | 22.1% |
As shown in the table, the advertising and marketing industry has one of the highest AI adoption rates. Tools like ChatGPT, Claude, and Copilot are among the most used AI tools by companies, with ChatGPT being the clear winner at 83% adoption rate among enterprises 1.
Coca-Cola’s AI Holiday Ad: A Case Study
Coca-Cola, a brand known for its iconic holiday commercials, has once again used generative AI to create its latest holiday ad. The ad, which reimagines the classic Coke caravan, has received backlash for its poor quality and lack of festive joy. Critics have called it a « sloppy eyesore » that fails to capture the magic of the brand’s traditional holiday commercials 2.
The use of AI in Coca-Cola’s holiday ad highlights the growing concern over the quality of AI-generated content. While AI can be a powerful tool for creating engaging ads, it requires careful curation to produce high-quality content that resonates with audiences.
As companies like Coca-Cola continue to adopt AI in their advertising strategies, it’s clear that the technology is here to stay. However, the key to success lies in striking the right balance between AI-generated content and human creativity. By doing so, brands can harness the power of AI to create innovative and engaging ads that captivate their audiences.
1Source: Business Insider – https://www.businessinsider.com/ai-tools-used-most-by-companies-chatgpt-claude-copilot-gemini-2025-11
2Source: The Verge – https://www.theverge.com/news/812559/coca-cola-ai-holiday-christmas-commercial-2025
Creating Effective AI-Generated Content
Step-by-Step Guide to Creating AI-Generated Content
Creating effective AI-generated content requires a combination of the right tools, training, and refinement. Here’s a step-by-step guide using Lumen5, a popular AI video creation platform:
1. **Choose the Right AI Tool**: Select Lumen5 or a similar platform like InVideo that fits your content needs. For example, Lumen5 is ideal for creating short-form videos.
2. **Train the AI Model**: Input your script or text into Lumen5. The AI will analyze the content and suggest visuals, animations, and music. You can choose from various templates and styles to match your brand.
3. **Refine the Output**: Customize the AI-generated video by adjusting the visuals, animations, and audio to better fit your brand. Lumen5 allows you to edit the video directly within the platform.
Best Practices for AI-Generated Content
To ensure high-quality AI-generated content, follow these best practices:
* **Ensure Quality and Coherence**: Review and edit the AI output to ensure it aligns with your brand voice and message. For instance, Coca-Cola’s AI-generated holiday ad received backlash for being a « sloppy eyesore, » highlighting the need for human oversight.
* **Use Human Oversight and Editing**: Implement a review process to catch any errors or inconsistencies in the AI-generated content.
Here’s an example code snippet in Python for post-processing AI-generated content using the OpenCV library:
import cv2
# Load the AI-generated video
video = cv2.VideoCapture('ai_generated_video.mp4')
# Apply filters or edits as needed
while True:
ret, frame = video.read()
if not ret:
break
# Example: Apply a grayscale filter
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('Edited Video', gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video.release()
cv2.destroyAllWindows()According to a Business Insider study, companies are increasingly adopting AI tools like ChatGPT, Claude, and Copilot. By following these steps and best practices, you can create effective AI-generated content that resonates with your audience. For example, Microsoft’s in-house AI image generator, MAI-Image-1, is now available in Bing Image Creator and Copilot Audio Expressions, demonstrating the growing capabilities of AI in content creation.
Tools and APIs for AI-Generated Content
As seen in Coca-Cola’s recent AI-generated holiday ad, the use of AI tools for content creation is becoming increasingly popular. However, the result can be a hit or miss. To help you navigate the landscape of AI-generated content, we’ll compare different AI tools and APIs, and provide examples of how to integrate them into your workflow.
Overview of AI Tools and APIs
Several AI tools are available for content generation, each with its strengths and weaknesses. Here’s a comparison table of some of the most popular options:
| AI Tool | Type | Key Features | Price |
|---|---|---|---|
| Google Cloud AI Platform | Cloud-based | AutoML, custom model training, online predictions | Custom pricing |
| Microsoft Azure Machine Learning | Cloud-based | Automated ML, model interpretability, data prep | Custom pricing |
| DeepAI | API-based | Text-to-image, image editing, AI model training | $5/100 credits |
| MAI-Image-1 (Microsoft) | In-house image generator | Text-to-image, image generation | Available in Bing Image Creator and Copilot |
When choosing an AI tool, consider factors such as the type of content you want to generate, the level of customization required, and your budget.
Using APIs to Integrate AI-Generated Content
To integrate AI-generated content into your application, you can use APIs provided by AI tool vendors. Here’s an example API call using DeepAI’s text-to-image API:
curl -X POST \
https://api.deepai.org/api/text2img \
-H 'api-key: YOUR_API_KEY' \
-F 'text=Generate an image of a festive holiday scene' \
-F 'grid_size=1'
This API call generates an image based on the provided text prompt. You can modify the API call to suit your specific requirements, such as changing the grid size or adding additional parameters.
When using APIs, consider factors such as API endpoint, request parameters, and response formats. Be sure to check the documentation for the specific AI tool you’re using for more information.
According to a recent study, companies are using a variety of AI tools, with ChatGPT and Claude being among the most popular. By choosing the right AI tool and API, you can create high-quality, AI-generated content that enhances your brand and engages your audience.
Measuring the Success of AI-Generated Content
Key Metrics for Evaluating AI-Generated Content
To determine the effectiveness of AI-generated content, it’s crucial to track key performance indicators (KPIs). According to a recent study, AI-generated content can achieve impressive engagement metrics, such as click-through rates (CTR) of up to 20% and conversion rates of 5-7%. These statistics demonstrate the potential of AI-generated content to drive user interaction and conversions.
Some essential metrics to evaluate AI-generated content include:
- Engagement metrics: CTR, time on page, bounce rate, and social shares
- Conversion metrics: conversion rate, lead generation, and sales
Implementing AI-Generated Content in Your Marketing Strategy
To successfully integrate AI-generated content into your marketing strategy, follow these steps:
1. **Identify opportunities for AI-generated content**: Analyze your content pipeline and determine areas where AI can augment or automate content creation, such as social media posts, product descriptions, or email newsletters.
2. **Develop a content strategy**: Define your goals, target audience, and content themes to ensure AI-generated content aligns with your overall marketing objectives.
3. **Choose the right AI tools**: Select platforms like Microsoft’s MAI-Image-1 or tools that integrate with your existing content management systems (CMS).
A successful example of AI-generated content is a campaign by a leading e-commerce brand, which used AI to generate personalized product recommendations, resulting in a 30% increase in sales. By leveraging AI-generated content, businesses can improve efficiency, enhance customer engagement, and drive revenue growth.
When implementing AI-generated content, consider the following best practices:
- Monitor and adjust: Continuously track performance and refine your AI-generated content strategy
- Human oversight: Ensure AI-generated content is reviewed and edited to maintain brand consistency and quality
By following these guidelines and leveraging AI-generated content effectively, marketers can unlock new opportunities for growth and engagement.
Conclusion
Key takeaways on creating effective AI-generated content, including the importance of human oversight and editing, and the need to choose the right AI tool for your needs.
Start experimenting with AI-generated content today, using tools like Lumen5 or InVideo, and measure its success using key metrics such as engagement and conversion rates.
