AI Creativity Unlocked: Making Anything Seem Possible

Interested in how AI can transform your creative process? Looking for practical tips to use AI to expand your creativity and drive marketing innovation?

In this article, you'll discover how to use AI to unlock your creativity.

Why Marketers Should Embrace Artificial Intelligence for Creativity

In the past, innovative marketing ideas were often difficult to sell to stakeholders due to high costs and uncertain ROI.

However, these barriers are lowered significantly with generative AI, particularly tools like custom GPTs.

The cost, time, and platform investment have been de-risked, opening up new possibilities for creative marketing experiments and innovation.

Still, generative AI is not a magic solution that will do all the creative work for you. Instead, it's a tool that amplifies and extends human creativity. If you want to get something creative out of the model, you have to put something creative in; you can't just sit back and push a button and have the AI do your thinking for you. 

It's the same as working with or collaborating with a creative partner. You still have to bring your own creativity.

This collaborative approach with AI tools has allowed Jenny to expand her creative output significantly. “I can just do so much more than I could before,” she says. “I can set a thought into motion, have my AI friend pick it up, and riff on it while I'm setting a second idea in motion. Then I'm setting a third idea in motion.”

A Step-by-Step Guide for Using AI Models to Fuel Creative Marketing Campaigns

Jenny Nicholson envisions a future where brands use AI-powered tools not just for content creation but as a form of marketing, customer experience, engagement, and R&D. 

She encourages marketers and brands to embrace this technology and the experimental mindset it enables. 

Here are three use cases to get you started.

#1: Reveal Deep Consumer-Centric Insights

The first step in Jenny's creative process is to uncover deep insights about the target audience. This approach shifts the focus from what the brand wants to say to what the consumer cares about.

Instead of starting from what you want people to know about you, start by zeroing in on what it's like to be the customer. Then, look for interesting places where the brand and what the person cares about can intersect.

To illustrate this point, Jenny uses a party analogy: “Advertising is basically constantly showing up to a party that you didn't get invited to… You can't show up at that party and stand in front of the bar, blocking access to the snack table and telling everybody how great you are. That's not what makes people want to have you at the party; you must be interested in them. You have to understand what's going on in their lives.”

When using AI for this step, Jenny cautions against a common mistake. Many people, she notes, might simply ask the AI to “generate a social media campaign that gets Gen Zers to want to drink this kombucha.” This approach typically results in mediocre output.

Instead, Jenny suggests the following approach:

1. Provide context to the AI about your brand, target audience, and campaign goals.
2. Ask the AI for strategic frameworks to understand the challenge from different angles.

For example: 

I have a kombucha brand. [brand details] I'm trying to reach Gen Z. I want to do a social media campaign around summer and kombucha. Can you give me ten strategic frameworks to help me understand the challenge and develop inventive ways of addressing this?

But Jenny's process continues beyond receiving the AI's initial output. She often pulls one point from strategic framework number eight and one thing from strategic number seven and then adds an idea of her own. Then, she prompts the AI to consider a campaign based on these three nodes.

In this way, she's using AI as a tool for inspiration and idea generation rather than relying on it for complete solutions, leading to more innovative and tailored strategies.

#2: Consider Creative Perspective Shifts

Once you have initial insights, the next step is to explore them from various angles and perspectives. This is where AI's ability to embody different viewpoints becomes particularly valuable.

This process is not linear. Look at the output of AI as a mind map. When you see interesting points, ask the AI to expand on them. Then, look for a connection between those sub-nodes you had yet to consider.

Jenny explains that large language models are essentially perspective-less, timeless, feeling-less, knowledge graphs–similar to mind maps, made up of every human perspective. For example, if you ask an AI to consider a lemon, it will connect these conceptual dots:

• The word lemon is close to the word/concept fruit. 
• It's close to the color yellow. 
• A lemon is closer to citrus than it is to fruit
• A lemon is close to a pie because there's lemon meringue pie. 
• It's close to but not as close to cars.

This interconnected network of concepts allows AI to generate diverse and sometimes unexpected perspectives.

The AI's ability to generate these diverse perspectives is particularly valuable as we get older or more entrenched in our professional roles because our brains tend to become locked into familiar thought patterns and pathways. By leveraging AI, we can open up new avenues of thinking, explore fresh pathways, and venture into directions that we might not have discovered on our own.

To get started with using AI for perspective shifts, Jenny suggests these approaches:

Time Travel: Ask the AI to imagine future scenarios or explore historical contexts. For example: 

Imagine it's five years in the future. We are the number one kombucha brand on college campuses across the country. Detail the step-by-step choices that got us from now to 2029.

Unusual Perspectives: Prompt the AI to take on unexpected viewpoints. For example:

Tell the story of a bottle of kombucha sitting in the refrigerator case, waiting for somebody to pick it up.

Push the AI Beyond Anthropocentric Thinking: For example:

Why are you centering humans? I will bring the human perspective; I don't need you to have an anthropocentric perspective. That's what I'm for.

#3: Rapidly Build and Test Prototypes

According to Jenny, one of the most powerful applications of AI in marketing is the ability to quickly prototype and test creative ideas without significant investment. She shares an example of a custom GPT she created for Zola, a wedding planning platform, which illustrates this potential perfectly.

The project originated from insights gathered in Zola's yearly “First Look” survey, where they reach out to newlyweds to understand their experiences and challenges. Two key findings from this survey inspired the creation of the custom GPT:

1. The number one thing that surprised people during the wedding planning process was the sheer volume of decisions they had to make. Most couples were unprepared for this aspect of planning.
2. In heterosexual relationships, the bulk of these numerous decisions often fell disproportionately on one partner.

Based on these insights, Jenny and her team developed a custom GPT called “Split the Decisions.”

The GPT asks couples questions about their wedding plans and preferences. 

You and your fiancé sit down and answer some questions about the wedding.

• Where is the wedding to be held?
• How many people will attend? 

Then, each partner answers a few questions on their own: 

• In a few words, describe your emotional state regarding wedding planning. 
• What are you most excited about? 
• What are you most worried about? 
• What is your number one priority for this wedding? 
• When your guests leave the wedding, what do you want them to say?

After these initial questions, the GPT digs deeper with a series of “which of you” questions designed to uncover each partner's strengths and preferences in relation to various wedding planning tasks. For example:

• Which of you is most likely to enjoy negotiating with a vendor for the best deal? 
• Which of you is most likely to have a meltdown over the color of the napkins?

The GPT generates a personalized task list for each partner using the couples' responses. This process's output is a downloadable CSV file that includes not only the task assignments but also links to relevant Zola resources, tools, or articles to help the couple get started on each task.

What's remarkable about this project, Jenny notes, is how quickly and inexpensively it was developed. “In less than a month from start to finish…it was out in the world. We could test it and see if it worked,” she says. This rapid prototyping ability allows brands to test innovative ideas with minimal risk and investment.

Jenny is particularly excited about this approach for brands because it allows for the creation of new products or experiences without significant infrastructure investment.

It allows companies to experiment with new ideas and gather real-world feedback without the traditional barriers of high development costs and extended timelines.

Leverage Multiple AI Models to Get a Final Output

Each AI model has its strengths and unique characteristics and you should experiment with using multiple AI models throughout the creative process.

Jenny says she regularly uses ChatGPT, Claude, Google's Gemini, and image generation tools like Midjourney and Idiogram for different stages of the creative process.

For example, she might use ChatGPT to break down processes, take the output to Gemini or Claude for more creative exploration, and finally bring it back to ChatGPT for editing and refinement.

Other Notes From This Episode

• Connect with Michael Stelzner @Stelzner on Facebook and @Mike_Stelzner on X.
• Watch this interview and other exclusive content from Social Media Examiner on YouTube.

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