Using AI for content research: Dos and don'ts

Want to get a quick round-up of some obscure topic? Ask AI. Want to come up with some basic interview questions without thinking too hard? Ask AI. Want to get all the necessary content research for your next post at your fingertips? Yep, you can ask AI.

AI is transforming content research, along with how we do marketing generally. Here are all the dos and don'ts of using AI for content research (including common mistakes you're definitely guilty of):

✅ Dos: How to use AI for content research

1. Topic exploration

   
   You can sit back and watch AI tools reel out content research in seconds. They do this through web scraping, trend analysis, and uncovering niche topics that you might otherwise remain hidden. By analyzing search patterns and content engagement across platforms, AI can identify gaps in your existing content and suggest directions that might get you winning big.
   
   And yes, these are things you could do as a marketer, but would take up a significant amount of your time. Time you could spend doing more of the fun stuff.
   
   Example prompt: "Analyze the top 10 trending topics in [your industry] over the past six months and identify three underserved subtopics with high engagement potential. For each subtopic, suggest three possible angles that haven't been extensively covered"
   
   
   

2. Dataset breakdown

   
   One of AI's most powerful applications is its ability to break down huge amounts of data... data that could contribute to your content research. AI not only does this quickly (yay), but can also extract key insights and present information in more digestible formats to inform your content strategy and make sure everyone is aligned. We heart team alignment.
   
   Example prompt: "I have survey data from 2,500 customers about their experience with our product. Please analyze the responses, identify the three most common themes in the feedback, extract meaningful quotes that represent each theme, and suggest how these insights could inform our next content series"
   

3. Diverse perspectives

   
   Finding out how you can contribute to current conversations requires understanding and consideration of multiple viewpoints.
   
   You can use AI to help map out different perspectives on a topic, identifying common ground and points of contention to ensure your content adds genuine value to ongoing discussions. You know, instead of fading into a sea of things-that-have-already-been-said.
   
   Example prompt: "Show me the different perspectives in the current debate about [topic] across academic, industry, and consumer viewpoints. Highlight areas of consensus and disagreement, and suggest three unique angles that aren't being adequately addressed in current content"
   
   

4. Efficient background research

   
   When you just need to get going with some background research (whether you're short on time or suffering with a bit of creative burnout), AI is great go-to.
   
   With a good prompt, you can get the information you need in a matter of seconds. It can summarize key concepts, historical context, and foundational knowledge in your topic area, helping you to quickly build a solid understanding before diving deeper into the realms of a new topic. 🤿
   
   Example prompt: "Provide a comprehensive overview of [topic], including its historical development, key milestones, current state, and future projections. Include important terminology I should understand and identify the most influential thinkers or organizations in this space"
   
   

5. Relevant statistics, examples, and studies

   
   Use AI to save you from scrolling (forever and ever and ever) to find quotes, statistics, and supporting evidence for your own content. Adding examples and evidence grounds your work with credible information rather than mere opinion... plus, people love a good statistic (we've got a bunch of marketing statistics if you're interested).
   
   Example prompt: "I'm writing about the impact of remote work on company culture. Find me five recent studies with statistics on productivity, employee satisfaction, and retention rates in remote vs. office environments. Also provide three examples of companies that have successfully implemented innovative remote work policies with measurable positive outcomes"

❌ Don'ts: Where AI falls short for content research

1. Facts and accuracy

   
   Risk: AI tools can generate content that *sounds* like it could be real, but is actually factually incorrect. This is especially likely when you're asking about recent events, more niche topics, and when making specific claims about statistics or studies.
   

   Solution: Always (please) verify facts, statistics, and specific claims generated by AI using trusted sources.

2. Straight-up deep dives

   
   Risk: AI often lacks the nuance and depth that you need for more specialized topics, which is not-so-good for when it comes to expert knowledge, historical context, or cultural sensitivity.
   

   Solution: Use AI to build your foundation of knowledge, then build on top of that with expert interviews, company insights, or references to specialized publications and other primary sources for true depth.

3. Source quality

   
   Risk: There's a chance that your AI tool might get confused between high-quality, authoratative sources and less reliable ones, unless specifically instructed.
   

   Solution: Explicitly ask AI to prioritize peer-reviewed studies, established publications, and recognized experts when gathering information. Hey, you could even input external data that includes information about Domain Authority if you're feeling fancy.

4. AI-only research

   
   Risk: Relying exclusively on AI for content research creates echo chambers and repetitive content that screaming out for some originality and fresh perspectives.
   

   Solution: Use AI as one tool within a more diverse approach to your content research that includes human interviews, firsthand experiences, customer testimonials and quotes, original data collection, and creative thinking.

5. Ethical research

   
   Risk: Without realising, AI tools can break the rules a bit when it comes to copyright, privacy, and biased representation of topics. The current issue of AI removing watermarks from copyrighted images with next-to-no effort from us just shows it.
   

   Solution: Develop clear ethical guidelines for AI use in your content process and, when using images, always verify their licensing status and avoid the tools that circumvent copyright protections.

AI for content research best practices

• Consider AI-generated information as a starting point rather than definitive resource.
• Implement a multi-stage verification process for key facts in your content.
• Partner up with subject matter experts who can really enhance your AI-generated research.
• Develop clear guidelines for evaluating source credibility and apply them to all AI research.
• Set aside dedicated time for non-AI research methods to make sure your content is valuable.

Using AI for content research: What's next?

So, it's clear: AI can complement human research skills pretty well.

Embrace an AI tool like Optimizely Opal, totally embedded into your content workflow, to help with content research and create on-brand content in a matter of seconds. But ultimately, don't lose sight of unique human elements that really make the difference to how your content is perceived.

Learn more about Opal here.