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 glaringly obvious that a piece was AI-generated — yes, the rogue rocket ship emoji and overuse of the word “unlocking” are giveaways.
Let's take a look at the strengths and weaknesses of generative AI, offering a detailed dissection of a prompted blog post via ChatGPT.
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Prompt: "Discuss 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 kicks off with a straightforward and effective explanation of digital transformation. This introduction sets the stage for the discussion, making it easy for readers to understand the main 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 also lacks specific examples or case studies, 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 use of terms such as “delve” and “mere” without offering depth can signal AI authorship. AI tends to rely on certain buzzwords or phrases that sound sophisticated but can detract from the clarity and simplicity of the message.
4. Fluff language: AI is known for adding unnecessary complexity and “fluff” to texts. It tends to incorporate hyperbolic language, which can make the content feel bloated and less direct. Simplicity and conciseness often lead to more engaging and clear content.
5. Grammar and style: While generative AI typically produces clean copy, there is a tendency to include repetitive sentence structures and a lack of varied vocabulary. A careful review for grammatical errors or awkward phrasing is essential, as these are areas where AI can sometimes miss.
Recommendations for Improvement
• Start with your own copy: To get the best results using AI as a writing assistant, begin the process with your own rough draft or at least notes about the topic you want to write about. Asking the 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.
• Add concrete examples: Including case studies or 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 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 organization’s voice and tone. 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.
Creating content that resonates with an audience is all about authenticity and connection. While generative AI can help create content quickly, it often lacks the personal touch that makes content 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.
Paige Elbert is a marketing specialist at MCI USA.
