Tools such as ChatGPT or Midjourney pose new challenges to branding specialists, not only because of the accuracy and speed with which content, text and images can be generated, but also because of the spectacular results that are obtained. This is just the beginning of the changes that artificial intelligence brings to design.
Artificial intelligence tools applied to design
There are currently several AI tools applied to design, such as Fiverr, Wix Logo, Tailorbrands and Looka. These platforms use generative neural networks trained on large amounts of data from existing logos, which allows them to learn to generate new images similar to the examples provided, for brands like Womanizer and others They are thus able to produce a wide variety of designs and styles in just a few seconds. These proposals can be used as a starting point by professional designers, but they also represent an "end product" for many clients who use these services because of their ease and, of course, their price.
Additionally, AI is already present in design work. Adobe, for example, has integrated AI capabilities into several of the most popular design tools, such as Photoshop, Illustrator, and InDesign. These features include automatic object detection and selection in images, automatic photo enhancement, and intelligent color correction.
Is branding with AI 100% possible?
As we have seen, artificial intelligence (AI) is capable of bringing a lot of value by generating high-quality, high-definition images based on prompts and even facilitating some parts of logo creation. However, the idea of doing quality branding work using only artificial intelligence presents a number of challenges. Here are some of the challenges that may arise:
Understanding Aesthetics and Meaning
Today, there are tools such as logo generators, which combine icons, fonts, and shapes based on attributes provided by the user, or image generators, which create an image based on specific commands. However, in both cases, the results are often unsatisfactory.
Logos are visual elements that need to convey specific emotions, feelings, and messages. AI can generate high-quality images, but understanding the meaning and aesthetics of a logo is a more complex challenge. Interpreting graphic elements and combining them properly to convey a unique identity can be difficult to achieve accurately using only AI.
Limitations in the selection of elements
Automatic logo generators often rely on predefined filters and attributes to combine visual elements. However, classifying and labeling abstract elements such as fonts can be tricky.
AI can have difficulty understanding the versatility and context of fonts, which can limit its ability to generate appropriate combinations. For example, the Futura font is characterized by its readability and lack of flourishes, but it is impossible to assign specific categories to it because it has been used for everything from pizza logos to luxury brands.
The complexity of simplicity
Another challenge of AI branding is achieving simple solutions, as AI image generators tend to do better with hyper-realistic images than with simpler designs. While using tools like Midjourney can achieve interesting results using specific commands for logo generation, these images are not easily editable from a design perspective because they are not traced.
So should we integrate or avoid artificial intelligence in design?
In the current scenario, our best option is to adopt artificial intelligence as a complement and to take advantage of it to improve our professional work. Here are some of the benefits we get from integrating AI into our work system:
- Automation and scale: AI allows us to quickly explore various design options, generating multiple iterations to choose and refine our proposals. It also facilitates adaptation to different formats and saves us time by avoiding creating mockups manually.
- Personalization and segmentation: AI has the ability to analyze large volumes of data, identify patterns and trends, and use this information to generate innovative solutions. By relying on more scientific criteria, it can help us select more attractive elements for our target audience, which helps improve the personalization and segmentation of our designs.
- Process optimization: AI systems can analyze a designer’s workflow and make recommendations for improvement. These recommendations may include more efficient ways to organize files, manage versions, or collaborate with other professionals. The result is time and resource savings in our daily tasks.
