Charting a Better Brand Course – Part 3

Charting a Better Brand Course – Part 3

In Part 2 of our series on brand communication, we looked at the differences between brand voice and copy tone, and explored how you could achieve communication consistency using organizational style guides and document-specific style sheets. In this final installment, we set our sights on one of the biggest disruptors on the horizon: artificial intelligence, or AI.

Balancing challenges and opportunities in AI-powered brand expression

AI-powered tools like ChatGPT and Claude, as well as image generators such as Midjourney and DALL•E, are revolutionizing communication, with businesses facing both exciting opportunities and significant challenges. We’ve seen firsthand how these tools can reshape brand expression, so let’s explore 7 critical areas in which the challenges and opportunities of using AI in communications intersect.

1. Writing for context and specific audiences

Challenge: AI struggles with understanding nuanced contexts and specific audience needs, sometimes leading to generic or off-target communication. AI tools, while proficient in generating content, often lack the deep understanding of the specific cultural, social, or emotional contexts that human writers naturally grasp. This gap can lead to content that may seem out of touch or irrelevant to particular audience segments.

Opportunity: AI can analyze large volumes£ of data, ¢including customer feedback and market trends, to help you understand audience preferences more systematically. This can aid in creating content that resonates better with different audience demographics, leading to more effective and targeted communication strategies.

2. Confidentiality and data security

Challenge: Using AI tools raises concerns about confidentiality and data privacy, as these systems often learn from large datasets that may include sensitive information. AI systems, especially those trained on public data, might inadvertently incorporate or reveal confidential information. This poses significant risks in terms of data security and client trust. Another consideration is copyright protection. 

While the content that you input into an AI-powered tool might be protected, the altered version generated is out of your control. It can feature elements pulled from other sources, even possibly content from one of your market competitors. What’s more, the final content version will become part of the open pool of data into which the AI tool can dip at any time and for any user.

Our tip: If you are worried about where the content that an AI tool generates comes from, add references to your query. For example, if you are asking ChatGPT to create an outline for a grant application, literally write something such as “include references” in your query. If the tool cannot generate a precise list of references, it might still list its sources. Another tactic is to simply copy the AI-generated content and paste it into Google or another search engine to see which results come back. It is good practice, especially if you use a free version of ChatGPT. 

Opportunity: AI systems can be programmed to adhere to robust data security protocols and trained on encrypted or anonymized data for handling sensitive information, ensuring client confidentiality while benefiting from advanced data processing and analytical capabilities. 

A greater conversation needs to take place about the very concept of content uniqueness and creative ownership, preferably outside silos. As uncomfortable as it might be to consider, we are likely moving toward a new era of AI-powered content co-creation in which audience engagement as well as personalized access and delivery of information and cultural products of all sorts will be the points of business differentiation, and not the content itself.

3. Maintaining a unique brand voice

Challenge: AI-generated content might default to more generic language and lack the unique tone or style that characterizes a brand, leading to a loss of distinctiveness in the market. Ensuring that AI-generated content aligns with a brand’s unique style and voice is challenging.

Opportunity: By training AI models on specific brand guidelines and existing brand content, the AI can learn to mimic and reinforce the brand’s unique voice. This consistent brand voice across all communications can strengthen brand identity.

4. Appropriate copy tone and cultural context

Challenge: AI may not always grasp the subtleties of cultural context and appropriate tone, potentially causing miscommunication or offense. AI may not fully understand the nuances of different cultures or subcultures, leading to communication that can be perceived as insensitive or inappropriate

Opportunity: With careful programming and guidance, AI can help identify cultural trends and adapt messaging to align with diverse cultural norms, enhancing global communication strategies. AI can be equipped with cultural intelligence by training on diverse datasets. This allows for more culturally aware and sensitive content generation, which is crucial in global marketing and communication.

Our tip: If you are generating content focused on or involving cultures that are not your own, don’t rely on AI to ensure the language you use is appropriate. Good practice is to hire a sensitivity reader to review the content.

5. Idea generation and creativity

Challenge: There’s a risk that reliance on AI for idea generation could lead to homogenization and stifle human creativity. Over-reliance on AI for content generation could lead to a lack of originality, as AI tends to replicate patterns it has learned from existing data.

Opportunity: AI can be used as a tool for sparking new ideas and perspectives, augmenting rather than replacing human creativity. AI can be used as a brainstorming partner, offering new perspectives and ideas based on its vast knowledge base. This can inspire human creativity, leading to more innovative and diverse content.

6. Industry/sector relevance

Challenge: AI might produce content that is not fully aligned with industry-specific terminology or trends, affecting relevance and accuracy. This could result in content that lacks depth or accuracy in a particular field.

Opportunity: By tailoring AI models to specific industries through specialized training, the content produced can be more relevant and informed. This targeted approach ensures that the AI’s output aligns with industry-specific norms and knowledge.

7. Brand position and expression consistency

Challenge: Ensuring a consistent brand message across various channels and platforms can be difficult when using AI, as different models might interpret the brand’s voice differently.

Opportunity: AI can analyze content across all platforms to ensure consistency in messaging and brand positioning. This holistic approach can reinforce a coherent brand narrative, strengthening brand recognition and trust.

While AI presents its set of challenges, it also offers significant opportunities for enhanced audience targeting and data-driven tailored insights. As businesses navigate this landscape, the key lies in leveraging AI as a complementary tool while maintaining a strong human oversight to ensure effective and ethical brand communication.

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