Billions of images are uploaded to Instagram and other social media channels every day. That’s a huge number! But why? What’s the reason behind it? It’s simple: there is fierce competition for our attention. Visual content (images and videos) contribute the most to this competition. Quantity isn’t everything; quality is equally important.
Many companies and businesses are trying to improve the quality of their content to have a stronger online presence. They work to implement the latest technological trends to produce the most engaging, unique content possible.
However, creating this type of content is expensive, and challenging to come up with new ideas and concepts needed to create unique materials. Artificial intelligence (AI) and its derivative – generative AI – are gaining more and more traction nowadays as they can provide a practical solution to this problem.
In this article, we will talk about generative AI and try to find generative AI applications in digital marketing. But before we can answer the question “What is generative AI?” first, we must understand how artificial intelligence works.
What’s Artificial Intelligence?
Artificial intelligence (AI) is the ability of machines, especially computers, to perform tasks associated with human users. AI can be attributed to all intellectual processes that involve discovering things, drawing conclusions, generalizing, and learning from past “mistakes.”
AI has several aspects: It can heal itself or learn from a data set. Or it can create artificial content such as photos, audio, and text. Here we focus on its content creation capabilities.
What Is Generative AI?
While we are good at analyzing and producing things, machines are better. And while machines are good at thinking up new things, we are better. And that defines generative AI in the simplest of terms.
It becomes even more critical when it comes to saving time and being cheaper. Every industry needs creativity and productivity – in unique ways. And digital marketing is no exception. Creativity and productivity require a lot of effort. Sometimes they are fruitful, but most of the time, they are futile. Creativity comes naturally; you can not buy it.
From social media to games, from programming to graphic design, from visual marketing to law, it’s all about rapid reinvention, i.e., something we can not achieve on our own.
Generative AI opens up excellent opportunities for companies needing a complete digital transformation.
Generative AI by Numbers
- By 2025, generative AI will generate 10 percent of all data. Compare that number to one percent today, and you’ll see its significance!
- An estimated 33.2%compound annual growth rate for AI between 2020 and 2027 suggests that we’re entering an “AI-enhanced” era.
- By 2027, 30% of manufacturers will use generative AI to make product development more effective.
These figures show that generative AI is laying the groundwork for a future that requires less employee training. Yet greater efficiency in creating unique content will be faster and less costly.
Generative AI & Visual Marketing
As colorful art, generative AI is finding its way through various forms of marketing. And when it comes to digital marketing, our story gets even more interesting as we see more and more generative AI applications in content marketing – especially visual marketing.
For example, German automakers have recently tried using generative AI. BMW, for example, uses this art to link many data points in its advertising campaigns. This includes BMW images, descriptions, and content created for each vehicle.
The company has been instrumental in developing or using AI software to link more than 500,000 photos.
Examples of Generative AI in Digital Marketing
Generative AI may sound like a scientific or computational research field. It is a valuable tool that companies, enterprises, and businesses can use.
Startups are using generative AI to create promotional blogs and other marketing content in an automated way. These – generated or supported by generative AI – are new products that can provide valuable services.
Regardless of how carefully these codes and programs are written, there are undoubtedly some flaws and vulnerabilities. Moreover, it is not easy to collect a complete set of training data. An incomplete data set will lead to biased results and predictions.
Generative AI programs are built based on huge datasets and various libraries, making them difficult to interpret and fully understand. This poses numerous risks associated with these codes, such as generating incorrect or misleading text.
Generative AI: Challenges & Risks
Generative AI requires a large amount of training data, i.e., a subset of data used to train the machine learning model. And the behavior of the algorithm depends largely on this data set. In some formats of generative AI, these behavioral variations get completely out of control.
For example, a generative adversarial network (GAN) is a model in which two neural networks compete to make more accurate predictions. This model may result in some predictions that do not match expectations.
In addition, generative AI may have security issues. Some models can be used fraudulently, leading to increased identity theft. Remember that generative AI can easily be used to create fake photos that resemble real images.
So now you can answer the question, “What is generative AI, and why should I care about it as a digital marketer?”
As digital marketers, we are constantly working and trying to keep up with the latest trends and technologies, including generative AI media – text, images, music, etc. AI-generated content has many advantages: it’s fast and can create unique material at a reasonable cost. But there are also some risks, including inappropriate content and pseudo-image generation.
Contact GTECH if you want to drive your company’s digital transformation using AI.