This content was produced by AI: What worked and what didn’t

For many of us, generative AI has become part of our daily lives at work. How often do we find ourselves clicking into our platform of choice to help us write a social media caption, brainstorm event theme ideas, or gain inspiration for a graphic or illustration? The opportunities seem endless. However, this technology isn't without its flaws. Occasionally, the output can lack in quality, and certain telltale signs can make it obvious that a piece was AI-generated — yes, the rogue rocket ship emoji and overuse of the word “unlocking” are giveaways. 

For associations, incorporating the use of generative AI into activities such as content creation and design ideation can mean increased efficiencies, optimized operations and governance, and more time to get creative.

“Within associations, the biggest opportunity is to shift the content creation and drafting role to AI, with strong human prompting and review at both ends,” says Erin Fuller, FASAE, CAE, chief strategy officer at MCI USA. “MCI’s recent Association Engagement Index research highlights that the key to engagement lies in cocreation, contributions and collaboration — all areas that require robust professional support and direction. By understanding that, for instance, we can hold a committee meeting on how AI is impacting an association’s industry and then generate multiple pieces of content and professional development from that conversation by using AI, we can choose to leverage staff differently. This approach not only accelerates engagement opportunities but also fosters member-led content, addressing key challenges for associations.”

Let’s take a look at the strengths and weaknesses of using generative AI for content creation, offering a detailed dissection of a prompted blog post via ChatGPT. 

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Prompt: "Write a blog post about how companies need to use digital tech and change their approach to stay ahead in the digital world."

Title: "Embracing Change: Navigating the Digital Transformation Landscape"

In the ever-evolving world of technology, digital transformation has quickly gone from a buzzword to an indispensable strategy for companies aiming to keep their edge in a digital-first world. This transformation is about weaving digital technology into the fabric of a business, fundamentally altering operations and how value is delivered to customers. It's also a shift in culture that challenges organizations to constantly question the norm, embrace experimentation and become comfortable with the possibility of failure.

As we explore this subject further, it's clear that digital transformation is more than just adopting new technologies; it involves a deep change in how a business thinks and operates. Companies must rethink their business models, processes, and strategies to make the most of digital tools and technologies.

Customer experience is at the heart of digital transformation. Modern consumers demand smooth, personalized interactions across all channels. Businesses that can leverage digital technologies to meet these expectations not just survive but thrive.

Data and analytics are also crucial. The ability to gather, analyze and act on data is key to making smart decisions that fuel growth. Analytics help businesses understand trends, customer behavior and improve operations.

In conclusion, digital transformation is not a mere destination but a continuous journey. It requires a shift in mindset, an embrace of innovation and a commitment to ongoing improvement. By understanding the key aspects of digital transformation and focusing on vital areas like customer experience and data analytics, businesses can tackle the digital era's challenges and emerge stronger. 

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What Worked

1. Strong introduction: The blog post starts with a straightforward explanation of digital transformation. This introduction sets the stage for the discussion, making it easy for readers to understand the theme right away.
2. Clear structure: The post flows well, connecting ideas logically. This structure makes the blog post reader-friendly, guiding you through the content without any confusing jumps or gaps.
3.  Engaging content: It addresses current business trends such as enhancing customer experiences and leveraging data. The way these topics are presented is informative, highlighting why these issues matter in the digital transformation context. 

What Didn’t Work

1. Generic opening: Phrases such as “in the ever-evolving world of…” or “in today’s day and age…” are commonly seen in AI-generated texts. These phrases lack the ability to capture readers from the start and do not add any value to the copy.
2. Lack of examples: The article lacks specific examples, statistics or data points, which are crucial for explaining complex ideas clearly. This issue often happens in AI-generated content, skipping the details and making more general statements that don’t speak to a specific audience.
3. Buzzwords overuse: The overuse use of terms such as “transformation” or “shift in culture/mindset” without offering depth can signal AI authorship. AI tends to rely on certain vague phrases that sound sophisticated but can detract from the clarity and simplicity of the message.
4. Hyperbolic language: AI tends to incorporate hyperbolic language into the copy it generates, which can make content feel salesy, cliché and inauthentic.
5. Writing style: While generative AI typically produces clean copy, it may include repetitive phrases or messaging as well as details that aren’t necessarily true. Also, without a robust prompt that outlines what your association’s voice and tone is, the generated copy generally won’t be very compelling.

Recommendations for Creating Better Content Using AI

When using AI, consider it your writing assistant, not the sole creator. The following suggestions can help you get the best results when crafting content.

• Start with your own copy. Begin the process with your own rough draft or at least notes about the topic you want to write about. Asking AI to create a piece of content from scratch increases the opportunities for error and extensive rewrites.
• Incorporate storytelling. Starting with a compelling story or a specific example could make the introduction more engaging and relatable. Address your target audience from the start, so readers know the content is relevant to them. This is where the human perspective is critical.
• Add concrete examples. Including real-world applications of your topic would provide clarity and enhance the reader’s understanding. Readers want to get value from the content they engage with, as well as practical insights and examples they can understand. Tailor the content to their needs.
• Reduce fluff. Eliminating unnecessary language and focusing on clear, straightforward communication improves the overall readability. Ask yourself: Does my colleague or industry peer talk this way in an everyday conversation? If the answer is no, revisit the text and humanize it. You can also continue to prompt the AI tool to revise the copy, telling it to avoid using flowery, hyperbolic language and to get to the point.
• Vary language use. Avoiding overused phrases and introducing a wider range of vocabulary could help in making the content feel more original and less formulaic. When using AI as a writing assistant, edit copy to match your association’s voice and tone. It’s easy to upload brand documents to help the AI have a reference point when helping create content. Incorporate terms and verbiage that are familiar to your audience and will resonate.
• Fact-check often. A big concern with AI-generated content is the possibility of presenting incorrect or fabricated information. Sometimes details are mixed up or content is generated based on patterns in the AI’s training data rather than verified facts. This underscores the importance of fact-checking AI content often to ensure accuracy. Do not assume the data or information you entered was interpreted correctly or accurately summarized.

Considerations for Using AI for Graphic Design

Using AI can also enhance your design process, specifically through concepting and idea generation, but it should be seen as an aid rather than a replacement for human creativity. Kelsy McCarthy, MCI USA’s associate vice president, Design Services, says, “As a creative director, I see AI as a way to streamline the process and automate tedious tasks so we can focus on the fun part — being creative.”

McCarthy says her team uses AI in various ways for design work. For example, with publications, AI is used to summarize key article points and to generate conceptual ideas for cover and feature designs, which speeds up the inspiration process, allowing more time to execute the designs. This approach ensures that the initial stages of design are more efficient, giving designers more time to focus on refining and personalizing their work.

AI tools in programs like Photoshop, such as the generative fill and expand function, can be particularly useful. They enable designers to customize images beyond the limitations of stock photography, resulting in more tailored and impactful visuals. Many stock photography sites include AI-generated imagery that can be helpful as well.

McCarthy emphasizes, though, that it is crucial to maintain the human touch in all creative work. “Let AI enhance, not overshadow, your work. When using it for visuals and design elements, make sure your designs still feel authentic — and double-check AI images for any quirks like extra fingers!”

Producing content and design work that resonates with an audience is all about authenticity and connection. While generative AI can help you create quickly, it often lacks the personal touch that makes your work relatable and engaging. The best approach isn’t to use AI on its own, but rather as a tool that supports human creativity. By working together, humans and AI can produce content that’s effective, authentic and tailored to the audience’s needs.