Comparing Human and AI Content Quality

An Oxford study just confirmed what most of us have been saying all along: AI-generated ads can outperform human-made ones, but only when they don't obviously look AI-generated. The secret? Human refinement. The best marketing campaigns aren't purely AI-driven or entirely human-made. They're like pizza. Dough alone is just bread, toppings alone is chaos. The magic happens when everything works together. Want to collaborate with AI effectively? 1) Use AI for rapid ideation, humans for emotional depth Take your worst-performing ad copy and feed it into ChatGPT or Claude with this prompt: "Rewrite this to evoke [specific emotion: frustration, curiosity, nostalgia]. Use conversational language. Surprise me." It'll give you variations you'd never think of. Then your human brain picks the best concept and refines it until you think: "We'd never have written this ourselves." 2) Let AI spot patterns, humans craft the story AI's really good at combing through customer feedback, support tickets, and social mentions for trends. But humans make those insights into stories that actually matter. Say AI finds that most support tickets mention setup frustration. Humans craft that into: "Setup shouldn't feel like assembling IKEA furniture blindfolded." 3) AI scales the testing, you choose the winners Generate multiple variations with AI, but you decide which ones are worth spending money on. AI can create 50 headlines in minutes, your judgment tells you which 3 are worth testing. 4) You set the rules, AI fills the gaps Define your brand voice, values, and no-go zones. Then let AI work within those boundaries to fill content calendars, generate product descriptions, or create email variations. Platforms are making this easier: - Microsoft’s Ads Studio has AI-powered creative tools built into campaign workflows - Google Cloud rolled out AI marketing tools for personalized experiences - Or start simple with ChatGPT/Claude and the prompt above Stop thinking AI vs. humans. Start thinking AI + humans. Your move: This week, pick your worst-performing content. Run it through AI with a specific emotional prompt. Refine the best result with your gut instinct. That's how you make sure your marketing isn't just dough or just toppings, but complete, irresistible pizza. P.S. I'm team pineapple on pizza 🍕 + 🍍 = 🤤 (Sorry to my Italian friends! At least there's no ketchup involved... 😂) #hicm #AI #AIinAdvertising

Human content outperforms AI content 94% of the time. This doesn’t mean what you think it means. Neil Patel Digital (a massively successful marketing agency) tested AI articles vs. human articles across many companies, websites, and industries. The human-written blogs generated more traffic almost every time. And not by a little. They won by a landslide in 94% of cases. But Neil Patel himself said that these results don’t mean “AI doesn’t work”. They are an example of how “Humans vs. AI” is a false dichotomy. ✅ It is a bad question, an unhelpful construct. Neil’s study concluded something many people suspected 👇 Letting AI write articles on its own is a bad decision. But he says that not using AI to help research, write, and publish more efficiently is also a huge mistake. Basically when we put ourselves in the position of “this or that”, everyone loses. 👎 In marketing the future isn’t AI vs Humans. It is AI + Humans. But don’t take my word for it. Neil Patel says it too. And he knows a lot more about marketing than me. But this conclusion is also true for translation. The question isn’t “Does AI translate better than humans?” This question gets us nowhere (except into arguments on LinkedIn!). The important question is “What can translators do with AI?” The answer: Translate with improved efficiency and accuracy, without losing quality. We need to move past the dichotomy of humans vs. AI. Because the future doesn’t look like humans vs. AI. The future is humans working WITH AI. In translation, marketing, and just about everywhere else. So what do we do now? Neil summed it up simply ⤵ “Relying fully on AI is bad. Ignoring it and not using it at all is also bad.” Are you ignoring it?

In my Forbes article on the future of #ai and #datastorytelling (https://lnkd.in/gk4C2BWw), I included a breakdown of some of the key elements in the data storytelling process. I scored humans 👩🏼💻 and AI 🤖 on each of them. With data storytelling being a combination of art and science, the table shows there are clear strengths on each side. 🤖 AI is well-suited to the ‘science’ 🔬 aspects that are tied to the more technical and structured tasks. For example, AI can process large, complex datasets to discover potential anomalies, trends, and patterns. 👨💻 On the other hand, humans excel in the ‘art’ 🎨 aspects that depend on contextual understanding, emotional intelligence (empathy), and creativity. Often, where one side is weak, it’s a complementary strength of the other side. For example, in advanced data analysis, AI offers powerful data exploration capabilities. However, its interpretation and conclusions will be weak without adequate contextual understanding. This is where humans can offer help. In the case of data visualization, each side offers different strengths. While AI can rapidly generate data charts, humans better understand what needs to be communicated in each data scene and how best to visualize it for specific audiences. I see AI suggesting an initial set of charts for a story and then having a human customize them for context, clarity, and visual impact. As I mentioned in the article, the future of data storytelling is augmented, not automated. I’m excited to see what insights are unlocked by partnering with AI increasingly in our data storytelling. Do you agree with my scores? Are there other issues or synergies I overlooked?