Brands have long been built around static assets like logos, slogans, advertising campaigns, and websites. Companies have built brand awareness by defining their brand identity and consistently expressing it across various channels. This approach hasn't changed much in the digital landscape, and brand assets are still managed based on design systems and content guidelines.

However, recent advances in generative AI are transforming the very concept of brand equity. AI technology, capable of generating diverse content in real time—text, images, videos, music, and more—is transforming not only how brands communicate with customers, but also how brand assets are created and expanded.

Brands are no longer a collection of fixed assets, but are evolving into digital asset systems that are continuously generated and evolved based on AI and data.

Market needs

In the digital environment, the brand touchpoints companies must manage are becoming increasingly diverse. Brand experiences are created across diverse channels, including websites, social media, advertising platforms, communities, and AI search services, requiring the continuous production of content tailored to each channel.

In this environment, the following demands are increasing:

• Producing brand content for various channels
• Maintain consistency in your brand message
• Responding to rapidly changing content trends
• Providing personalized brand experiences

Generative AI technology, in particular, is emerging as a crucial tool to address these needs. AI can generate new content based on brand guidelines, enabling companies to build scalable brand asset systems.

Problems to be solved and directions for their resolution

There are several important challenges for generative AI to be utilized in the production and management of brand assets.

First, the brand's core identity must be clearly defined. Since AI generates content based on learned data and rules, the brand's philosophy, message, and visual identity must be systematically organized.

Second, brand assets must be structured into data format. Design systems, content guidelines, brand messages, and more must be organized into a structure AI can utilize.

Third, a strategy is needed to manage AI-generated content to ensure brand consistency. Indiscriminate content creation can weaken brand identity.

Therefore, companies need to go beyond simply using AI as a content creation tool and develop new brand operation strategies that combine AI with brand asset management systems.

Challenges from a technology, design, and security perspective

1) Technical perspective

Building a generative AI-based brand asset system requires a variety of technical elements, and this technological foundation provides an environment in which brand assets can be continuously created and managed.

• Building a brand database
• AI content creation system integration
• Designing creation rules based on brand guidelines
• Integration with content management systems (CMS)

2) Design perspective

In AI-powered brand asset systems, the role of the design system becomes increasingly important. A brand's visual elements, such as color, typography, icons, and layout, become crucial criteria for AI to generate new content.

This requires the following design strategies, which will help ensure that your brand assets remain consistent across different environments.

• Building a Scalable Design System
• Refining the Brand Style Guide
• Defining visual elements that can respond to various channels
• Quality Control of AI-Generated Content

3) Security and brand reliability

When generative AI is used to create brand assets, brand credibility and content management also become important issues.

Companies should consider the following factors. These management systems play a critical role in maintaining the reliability and stability of brand assets.

• AI-generated content verification process
• Brand Asset Management Policy
• Data Security and Access Management
• Brand Misuse Prevention Strategies

Iropke's approach

Iropke proposes a new brand asset strategy suited to the era of generative AI. This approach goes beyond simply creating content, managing and expanding brand assets with AI-based systems.

First, we design a brand data structure based on the company's brand philosophy and message. This establishes a foundation for systematically managing brand assets.

Second, we structure our design system and content guidelines to fit the AI ​​environment. This allows AI to generate new content based on brand guidelines.

Third, we design our website and content platform as a brand asset management hub. This allows for integrated management of content generated across various channels.

This approach is crucial for helping companies build scalable and continuously evolving brand asset systems in the era of generative AI.