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How Generative AI is Shaping Brand Marketing: Case Studies and Future Trends

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Generative AI (GenAI) is a type of Artificial Intelligence that can create a wide variety of data, such as images, videos, audio, text, and 3D models. According to the latest McKinsey Global AI Survey, the use of GenAI surged from 33% in 2023 to 65% in 2024, with companies increasingly deploying generative AI in their marketing and sales strategies.

Source: mckinsey.com

For marketers, GenAI is often used for automation and efficiency improvements, but it also holds significant potential for customization, enhancing personalized marketing, boosting creativity, increasing engagement, and creating novel and unique experiences. This issue will explore the roles these increasingly popular technologies play in brand creative marketing through specific case studies and future trends.

Best Examples of GenAI for Marketing Campaign Activation

1. Chupa Chups - AI World of Lollipops

A remarkable example of AI-driven user-generated content (UGC) is Chupa Chups' "AI World of Lollipops."

Users can customize their Chupa Chups fantasy world using their favorite elements, creating a unique and immersive experience with their own names. The generated images are easily shareable on social media, allowing friends and family to join in the magic. Chupa Chups fans can interact with the campaign, turning their sweetest dreams into reality and building a deeper connection with the brand.

Interactivity is a key element of modern marketing. GenAI significantly enhances user engagement by creating interactive and immersive experiences. Campaigns like Chupa Chups' 'AI World of Lollipops' enable users to create and share personalized content, sparking more interaction and discussion on social media.

2. Cadbury - My Cadbury Era

Cadbury UK launched a GenAI tool as part of its "200 Years of You" campaign. This innovative tool celebrates Cadbury's long history and cherished relationship with the British public. "My Cadbury Era" allows users to become stars in classic Cadbury ads from the past, integrating users into Cadbury's 200-year history.

3. Coca-Cola - Create Real Magic

Coca-Cola invited digital artists to use a new AI platform, "Create Real Magic," leveraging iconic creative assets from its archives to generate original artworks. Developed with OpenAI and Bain & Company, this platform combines GPT-4 and DALL-E functionalities. Artists can submit their works for a chance to be displayed on Coca-Cola’s digital billboards in Times Square and Piccadilly Circus.

4. Barbie AI Selfie Generator

Warner Bros. and PhotoRoom’s "Barbie" selfie generator is a prime example of marketers using AI to capture consumer attention. Consumers can upload their photos, which are instantly featured in Barbie movie promotional posters. This filter went viral on social media, demonstrating AI's capability to quickly create engaging, shareable content.

5. AI Camera for AWE

For the 15th anniversary of the Augmented World Expo, a custom AI camera application was created, offering users the chance to generate imaginative portraits from future "realities." This AI camera web app encourages exploration of AI technologies by transforming consumers into protagonists of untold stories.

AWE EU 2024 | The World's #1 XR Event
Source: awexr.com

6. Prompts of Love – Canal+

CANAL+ Poland launched a promotional campaign for its new series "The Love Algorithm." As part of the campaign, a special landing page was created where users can discuss the series and their heart-related issues with the help of AI.

Source: signs.pl

Challenges and Considerations

Generative AI has revolutionized marketing strategies by driving innovation and boosting efficiency. However, it also introduces certain risks that need careful consideration. Here’s a closer look at some of the main challenges and how to address them:

  1. Inaccurate or Biased Content: While AI can produce vast amounts of content, it might generate information that’s incorrect or biased, potentially leading to poor marketing decisions or harming your brand’s reputation.
    • Solution: Fine-tune AI models with task-specific data, use context learning, and ensure there’s always human oversight to keep the content aligned with your brand values.
  2. Consumer Resistance: Some consumers may be skeptical or uncomfortable with AI-generated content, especially in areas requiring personal interaction, like customer service.
    • Solution: Focus on enhancing the AI’s human-like qualities and be transparent about its use, helping to build trust and acceptance among users.
  3. Copyright Concerns: The use of AI to generate content can raise complex copyright issues, leading to potential legal challenges.
    • Solution: Work with partners who actively address copyright concerns, and ensure that AI-generated content complies with intellectual property laws.
  4. Cybersecurity Risks: Generative AI can be misused to create sophisticated cyberattacks, increasing the risk of data breaches.
    • Solution: Regularly update cybersecurity protocols, collaborate with security experts, and build internal capabilities to stay ahead of potential threats.

While generative AI holds incredible potential, understanding and mitigating these risks will help you harness its power responsibly and effectively

Future Development Trends

Artificial intelligence is everywhere, and it’s reshaping our industry in ways we couldn’t have imagined—from creative content and data analysis to digital media and tech services. We might be riding the wave of AI hype, especially with generative AI, but its impact is real and game-changing. For many, this moment is a turning point—you either embrace the change, or you risk being left behind.

With the rise of tools like Stable Diffusion, we’re diving headfirst into training our own AI models. Our goal? To make AI a key tool for expanding creativity, helping brands and marketers tailor their own generative AI solutions. The future holds incredible opportunities—creating more with less, making marketing intelligence smarter, and even unlocking new value in intellectual property by training proprietary AI systems.

But these possibilities also challenge the roles of partners in creativity, data, and digital media. We need to keep evolving, or risk being outpaced by a wave of new startups that are emerging around AI. We’re not shying away from this challenge; in fact, we’re ready to lead the charge in this transformation. This is what we were meant to do.

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