Businesses must establish a distinct and recognizable brand voice in the age of generative artificial intelligence (AI) that resonates with their target audiences. Even before AI changed marketing forever, ensuring an authentic and consistent brand voice that was heard above today’s marketing chatter was difficult at best. Now, with so much generative AI content being produced and consumed online, it’s even harder and more crucial for businesses to establish a distinct and recognizable brand voice in the age of AI that resonates with their target audiences.

Today, marketers and public relations professionals are challenged to ensure that their AI-generated content aligns with their brand’s distinct voice and personality. The rising use of AI for content creation and the growing list of AI tools to aid the process poses both opportunities and challenges for content creators trying to ensure an authentic and consistent brand voice across every communication platform.

AI writing tools like ChatGPT, Gemini, Claude, Jasper.ai and Perplexity can produce high-quality content rapidly at scale, but if not properly trained and managed, that AI-generated content risks coming across as plain vanilla “marketing speak” – generic and impersonal. Their often robotic tone is drowned out by other more authentic brands with a distinct voice and personality.

So how can brands leverage the rapid-fire content production benefits of AI while ensuring the generative AI content that’s produced presents an authentic brand voice with a unique personality and style?

Not surprisingly, this requires both a strategic and a hands-on approach to arrive at the best results. It starts with the strategic training of the large language models (LLMs) to understand and generate human language and continues and ends with the human touch — ongoing human oversight of the content strategy and content creation processes – to humanize the AI content.

In the previous blog, I looked at the simplest training method to ensure brand voice in the age of AI. In this approach, the AI model is provided with a single prompt – the one ideal piece of content that encapsulates the brand’s desired tone and voice. This could be a blog post, marketing copy or any other written material that best represents the brand.

However, this simple method of relying on a single text sample may not always capture the full depth of a brand’s voice no matter how well one provides clear context.

Advanced Training with a Curated Collection

The more advanced approach to AI model training simply involves more data. By curating a collection of high-quality content that exemplifies brand voice across different topics and platforms formats, the better the AI model can learn the brand’s voice and communication style. This will be more time consuming, but this more comprehensive training method enables the AI model to develop a more nuanced understanding of the brand’s communication style across different use cases.

The advanced process is a little more complex:

• Gather 10-15 exemplary content samples, such as blog posts, marketing materials, social media posts and any other content that represents the brand’s voice.
• Provide context and clear instructions: When inputting your content into the AI model, frame it with clear context and instructions on the desired output. For example: “I want you to analyze the following content samples and learn to generate new content that matches the distinct voice and style exemplified in these pieces.”
• Review and refine: Expect that that initial content generated will not be perfect. Review the text and highlighting aspects that don’t align with brand voice. Provide this feedback to the AI model and ask it to refine the output accordingly. Repeat as necessary until the output is satisfactory.
• Review and reinforce: Positively reinforce the AI model’s understanding by pointing out examples where it successfully captured brand voice to help solidify the learned patterns.
• Humanize the AI Content: Utilize a human AI content editor to review the final output and make any necessary changes to ensure originality, accuracy, relevance and a personal point of view.

Automating Brand Voice Analysis

If manually curating and feeding content samples to AI models seems too time consuming, some AI writing tools offer automated brand voice analysis capabilities. 

Tools like Jasper.ai leverage web crawlers to scan an existing website and digital content to discern a brand’s unique tone and language patterns. There isn’t any need to manually compile examples and feed them to the AI model. The language model self-learns your preferred tone, writing styles, word choices and more. This automated analysis is then applied to ensure all AI-generated content maintains consistency with brand voice, theoretically without any additional training inputs required.

However, as one can expect, the quality of this automated analysis depends on the strength of the existing online content. If the website doesn’t fully reflect your desired brand voice, the AI model’s content won’t either.

Finding the Balance

Whichever training method is chosen, and no matter how well one provides clear context, it is vital to combine AI with human oversight to ensure brand voice in the age of AI. While AI can produce quality rough drafts, human management and input into the process is essential. This human content review and revision – with additional checkpoints prior to publication — helps to guarantee a brand voice that is distinct and authentic – one that can build trust, recognition and a lasting connection with the brand’s audience.  

Remember, that in the end we are all writing for humans. The ultimate goal is to create content that resonates with humans.

Interested in finding out how Writing For Humans™ can ensure brand voice in your generative AI content? Contact us today at randy@writingforhumans.co or (203) 571-8151 for a free consultation on tailoring this powerful technology to your unique brand personality.

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