As businesses strive to stay ahead in today’s competitive market, innovation and creativity have become crucial elements of success. However, the traditional process of content creation can be time-consuming and resource-intensive, leaving little room for experimentation and innovation. This is where Artificial Intelligence comes in. Generative AI is a groundbreaking technology that is transforming the way businesses think about content creation and experimentation. With its ability to produce original and creative outputs in a matter of seconds, generative AI tools can enable businesses to work at a faster pace, experiment with new ideas more easily, and ultimately stay ahead of the competition. Because the technology has advanced so quickly, with last year’s ChatGPT3 having 100 billion parameters and the newly released ChatGPT4 having 100 trillion parameters, for example, generative AI has gone from gimmicky to disruptive in a matter of years. But how can we take this technology and apply it in real, meaningful ways?
When we first entered this new wave of digital transformation, we experimented with fun applications of generative AI. While we see this technology being utilized on social media platforms and online, there must be a better use of this technology than generating an image of a gecko in a Renaissance painting style, right? 
We’ve all heard of “digital first,” then “mobile first.” We are now truly in the era of “AI first.” Because the technology is so advanced and continuing to evolve each and every day, there is a huge opportunity for businesses in creative content generation. From visual content to audio, speech, text, and even code writing, generative AI is impacting all businesses in some way or another.
Visual Content
While the example of the Renaissance Gecko is one example of an image generated by artificial intelligence, businesses and creatives have a huge opportunity to implement this technology today. For example, these tools have the power to generate multiple versions of a new business logo in seconds. They can also help build content for social media, digital ads, and even web content. Because of the speed and efficiency, this technology is great for exploring concepts and ideas as a starting point that can later be refined.
Audio Content
Generative AI tools are powerful in creating audio content in various ways. The most common use case we’ve seen so far is Text-to-Speech (TTS). TTS technology uses machine learning algorithms to convert text into synthesized speech. TTS models can be trained on large amounts of audio data to produce high-quality and natural-sounding speech. There’s also huge potential in both speech synthesis and voice cloning. Speech synthesis refers to the process of generating speech from non-speech audio sources, such as text, images, or gestures. AI models can analyze the audio sources and generate speech that corresponds to the content. Voice cloning is a process of creating a digital replica of a person’s voice. AI models can analyze recordings of a person’s voice and generate a synthetic voice that sounds like the original speaker. There are hundreds of potential use cases for AI-generated audio content that is indistinguishable from human-generated content.
The Customer Journey
Where we see AI being significant for many businesses is in the planning process when it comes to the customer journey. For example, we can utilize AI to create different personas for one product. Let’s take car shopping: we can very quickly and easily generate a persona for a Gen Z car shopper and a persona for a mom with two teens. These personas will look very different, but because they are generated with such speed, it’s a great starting point. It’s important to note that these are not perfect for taking straight away, and that the customer journey will always require subject matter expert input. Eve Sangenito, Principal at Perficient, believes that “delivering effective AI-generated experiences requires careful considerations and should involve humans in the loop in order to review, revise, and finalize outputs.”
The real power, however, is when we combine multiple AI technologies and try to create something new. But how do we make it real and apply it to real-world scenarios? One use case to leverage Generative AI is in Journey Science. This is a proprietary discipline within Perficient to help organizations design customer-driven, frictionless experiences that are journey-focused. This practice combines researched-based insights with data-driven evidence to understand, predict and optimize the customer journey at every touchpoint. We see two specific applications within the Journey Science discipline that can help deliver individualized customer experiences.
Personalization
When we think of how AI can help personalize the customer journey, there are four main areas to consider: context, persona, behavior, and journey. Context considers the environmental factors and circumstances that surround an individual user story. Personas align a user’s needs and motivation with a pre-defined target. Behavior takes into consideration a user’s previous interactions to provide an evolving experience over time. And finally, journey drivers help determine where a particular customer fits within that journey. But how do we apply AI to these areas?
One example is by writing a product description targeting a specific persona, like “moms,” and comparing it to how it differs when requesting it to target “dads.” Based on features of the product, AI tools can help write product descriptions that will resonate with different audiences. For example, we had AI generate a product description for a lawn mower targeting moms. It highlighted features of the mower, including ease of use, how smooth it runs, and its reliability. Compared to the description targeting dads, we see different points being highlighted. This description calls out its power, how it’s built to last, and how durable it is. This can help you begin to ideate how you as a marketer may want to speak to your different audiences.
Experimentation
Because the technology is making tasks so quick and efficient, it becomes easier to experiment with web pages and learn what may resonate most with the customer. We can use AI technology to ask “what experimentation hypotheses can I create for this web product page?” to learn more. It can also generate ideas based on crawling a page and will call out things that are not relevant. Finally, it also helps answer questions like “what type of test can I perform on the page to increase conversions” and “what headlines can I test on this page for different audience?” This technology helps marketers think creatively and in new ways about their customer journey and how to best reach their target audience with efficiency.
Challenges and What’s to Come
However, this technology is not without its challenges. First, it is important to ensure accuracy in generated content as it may not always be of high quality and may contain errors or inconsistencies. Additionally, the quality of generated content is dependent on the quality and diversity of the data the AI model is trained on, which could result in bias or lack of originality. Credibility also comes into question as Google and other content evaluation tools are detecting AI-generated content, which may negatively impact SEO over time. Furthermore, outputs may require multiple attempts and still be difficult to understand and use, making it challenging to identify and correct errors or biases. Finally, ethical concerns must be considered as models can be used to generate harmful or offensive content, which can be damaging to brands or individuals. However, platforms such as OpenAI and Bing have prioritized ethical concerns, and we have seen significant improvements as each model evolves.
Generative AI is a groundbreaking technology that has the potential to transform the way we think about content creation and experimentation. With the ability to produce original and creative outputs in a matter of seconds, generative AI is allowing creatives and businesses to work at a faster pace and experiment with new ideas more easily than ever before. The potential applications of generative AI are vast and varied, and we are only beginning to scratch the surface of what this technology can do. As AI continues to evolve, it will be exciting to see how generative AI will transform the way we create and interact with content in the future.
