Using AI in a Meaningful and Responsible Way

At 5 by 5 Design we believe it’s possible to change the world by posing the right questions, listening to the honest answers, and following the path that emerges from the dialogue. Today’s discussion focuses on using AI as part of your marketing strategy.

Noelle Langston believes authenticity is paramount in today’s information age. For over 15 years, she’s focused on crafting brands and experiences that genuinely connect with people. Her expertise integrates design with years of consulting and a deep understanding of product design, UX/UI, and business management. This unique blend allows her to build products that solve real problems and help businesses offer greater value to their customers.

Her experience ranges from leading cognitive experience design at an AI product company to working on digital acceleration and product adoption at McKinsey & Company. Now, she leads Bold Type, a design and tech studio dedicated to helping brands build meaning in our deeply connected world. We’ve asked Noelle a series of questions about how to effectively use AI to aid marketing efforts. Here’s what she had to say.  

1. What is your experience using AI tools for marketing or communications specifically?

My primary AI tool for marketing and communications is Google Gemini, which I’ve trained to understand my business. I use it for quick first drafts accessing it in my browser with a chat window. Sometimes the blank page is intimidating! I like having something to react to because it often kickstarts better thinking and a quick first draft has a low impact on the environment. Using good prompts that are clear helps me to minimize my use of AI-related computational resources. 

While I am also building AI products, a more common experience is advising clients on responsible AI integration for their own marketing and communications. A key part of this is helping them define their brand identity. Depth and clarity directly impact how effectively any business can use AI tools. When clients have a strong, unique identity, they’re better equipped to leverage AI for consistent and authentic communication. Conversely, I’ve also seen firsthand how much time can be wasted trying to “coerce” AI to match a poorly defined vision, especially with images. It’s easy to misunderstand each other in human conversation, so clear communication is even more essential for AI to understand and deliver your vision.

These tools are a good starting point for most beginners to get acquainted with generative AI but it’s important to explore them slowly over time before any work with real stakes. Measure their efficiency against your human processes to ensure there is a true advantage to delegation but give it time to be sure. It’s easy to be romanced by the potential so make sure to critically evaluate any tool.

• Jasper: If your brand vision is strong, try Jasper for first drafts of marketing content, such as blog posts or social media captions.
• Adobe Firefly (integrated into Adobe Creative Cloud): Use Adobe Firefly for rapid image generation in early stages but rely on human refinement for brand-accurate visuals.
• Canva’s Magic Studio: Canva’s AI speeds content creation, but poor prompts can slow you down with revisions and all those iterations take a toll on the planet. Work with brand designers to define your brand so that you can use this tool responsibly.
• Mailchimp’s AI-Powered Features: Mailchimp’s AI can help you edit and automate emails to help you trigger messaging at pre-defined intervals, but it requires thoughtful integration with your customer experience strategy and overall operations.

2. What are some best practices for incorporating AI tools into your marketing?

More than anything, it’s important to know these tools’ strengths and limits. I use generative AI, like Gemini, to test audience perception. For example, asking a low-stakes question like “Is this blog post too technical?” I trust Gemini’s training to accurately approximate how a broad audience might react. 

Human expertise is still vital, especially since AI won’t challenge a poor prompt or request more information. For sensitive or legal content, or anything needing absolute accuracy, you’ll often spend more time reviewing the AI outputs than just doing it yourself. View AI as a well-meaning assistant, not a replacement. This balanced approach maximizes AI’s value while maintaining control and accuracy.

3. What precautions should you take when using AI?

There are a few key things I really want to emphasize. Keep in mind that because AI is so complex, what works best really depends on your specific situation. That being said, it’s vital to remember that AI’s output is a great starting point, but it’s not the final word—always bring in that human touch to review it and avoid overuse because of the toll on the environment.

AI can be a fantastic helper, but it’s not here to replace our creativity. And please, be mindful of the legal and ethical side of things, especially copyright, privacy, and bias. Also, let’s protect your valuable ideas—be careful about what you feed into AI, as it could end up training future models. Use AI where it shines, like basic content creation, and let your team handle the more nuanced, context-specific work.

Finally, and this is so important, make sure AI works with your existing processes. Don’t let it operate on its own; that’s a recipe for inconsistencies and headaches. Imagine AI giving customers service replies that contradict your website—that’s just going to create confusion. AI is at its best when it’s part of a cohesive whole.

4. What sorts of checks and balances should be employed to ensure AI tools are being incorporated strategically, ethically, and holistically into existing plans?

Introducing AI into your business requires careful consideration, as it’s neither a rushed decision nor a quick process. Innovation, particularly with transformative technologies like AI, is akin to exploring uncharted territory. While a map can be helpful, you must be prepared for the unexpected because there aren’t always guardrails to protect you from making mistakes. The more complex the terrain, the more essential it becomes to bring in an experienced guide, who can help you anticipate and mitigate challenges, ensuring a smoother journey. 

To be holistic, think of it like adding ingredients to a recipe. Start small, testing and observing how each element interacts with the others. There’s a logic to which AI components work best together and the order in which they should be introduced. Just as a seasoned chef understands the nuances of flavor combinations, we must carefully consider the compatibility and sequence of AI tools and use cases to ensure a harmonious and successful outcome.

Measuring success is also a big deal, and performance metrics are key to understanding the true impact of your AI. While sales figures and customer satisfaction scores provide valuable insights, they don’t capture the entire picture, especially with AI. Consider an AI chatbot that sees a surge in popularity, yet customers remain frustrated because their problems are unresolved. This disconnect would be missed if you rely solely on quantitative data.

5. Taking into account AI’s impact on the environment and biases, how can people balance their interest with this new technology with their concerns for its impact on the planet and people?

The seductive promise of AI’s possibilities masks the very real and often unacknowledged costs of its deployment. The energy demands of large-scale AI models are not merely “substantial;” they constitute a direct contribution to an unsustainable carbon footprint, exacerbating the climate crisis. Furthermore, the datasets upon which these models are trained are not neutral repositories of information; they are deeply biased, reflecting and amplifying existing societal inequities, particularly harming marginalized communities.

Therefore, we must move beyond mere calls for transparency. Demand, not merely “consider,” AI tools and services from providers who rigorously disclose their energy consumption and data provenance and subject such disclosures to critical evaluation. My favorite idea is introducing “nutrition labels” for datasets to bring transparency into a dataset’s composition, potential biases, and intended use, empowering users to make informed decisions and fostering responsible AI development.

AI offers us a potential chance to refocus our efforts. While I’m optimistic it could free us to explore creativity and hone skills like better communication and stronger community ties, this future isn’t automatic, and AI is also a threat we need to manage. We’ll need to be vigilant about biases and face difficult conversations. We can steer AI towards enhancing our capacity by tackling these issues, but it will require time, patience, and a keen awareness of our own egos.

Imagine AI being used to provide real-time translation for immigrants navigating essential services like healthcare or legal aid, bridging communication gaps that often lead to hardship. Or picture it automating the tedious data entry that consumes hours of a teacher’s week, freeing them to spend more time directly engaging with students who need extra support. We could create AI-powered tools that analyze public data to expose local environmental hazards, empowering communities to advocate for cleaner air and water. That’s the kind of connected and meaningful world I envision. By focusing on these concrete outcomes and addressing the very real risks, we can shape AI to enrich our lives in tangible, impactful ways.