When it comes to building a strong content strategy, one truth stands out: research is the foundation on which everything else is built.
But doing research manually? Yuck. Time-consuming. Tedious. Draining. And sometimes it can be so overwhelming that you feel like you are missing the mark.
That’s where AI comes in.
Content strategists are increasingly using AI to streamline the research process. In fact, Content Marketing Institute has found that 62% of marketers are now using AI to brainstorm new topics. AI tools can dramatically speed up your topical research process by:
- identifying relevant keywords
- analyzing audience sentiment
- suggesting new content ideas
All in a fraction of the time it would take manually. If you’re not yet using AI for topical research, what are you waiting for—a sign from the heavens? You might be missing out on one of the most powerful advantages in content marketing today!
In the following, we’ll look at how AI can supercharge your topical research and help you build a more targeted, effective content strategy.
Use AI-Powered Keyword Research at Scale
How to Use AI for Keyword Research
Despite numerous early proclamations of the death of the keyword, keyword research remains the foundation of any SEO content strategy. After all, how can you tailor a strategy if you don’t know exactly what people are seeking?
At its core, keyword research involves identifying the search terms and phrases that your target audience uses to find information, products, or services online. By understanding what people are actively searching for, you can create content that matches their intent. This makes it easier to drive organic traffic, build topical authority, and convert readers into customers.
Traditionally, keyword research meant manually combing through search engines and using static databases. Yawn. Now, just like the New York Mets are bolstering their lineup with Juan Soto, AI-powered tools like Ahrefs and SEMrush take things in a content strategy to a whole new level.
AI-powered SEO platforms, such as these, use artificial intelligence to analyze massive datasets. This includes search engine trends, user behavior patterns, and competitive landscapes. They then help surface the most relevant keywords that align with your goals. AI also helps predict how keyword popularity may shift over time, giving you a strategic edge and helping you get ahead of the curve.
Long Tail Keywords and Content Topics
Another way these tools can help you is by identifying valuable long-tail keywords. Where short-tail keywords like “dry cleaners” or “comic book store,” are broad and highly competitive, long-tail keywords are more specific. They usually consist of three or more words, such as “wash and fold laundry service near me” or “silver age comic books in Portland Maine.”
While short-tail keywords might have higher search volume, they’re often much harder to rank for—and often too general to attract your ideal customer. Long-tail keywords help you niche down, reach a more targeted audience, and frequently convert better.
That said, it’s important not to get stuck thinking about keywords in isolation. Effective content strategy today is about topics and intent, not just individual keywords.
Google’s algorithms are getting smarter. They care about how well your content answers questions, solves problems, and fits into broader topic clusters, not just whether you sprinkled in the “right” phrase a few times.
Use AI-driven keyword research as a guide to what your audience is interested in, but focus on building deep, comprehensive content that truly serves your readers.
Achieve Deeper Audience Insights with AI
What Machine Learning Can Do
Knowing your audience isn’t just about identifying demographics like age, location, or job title anymore. To create content that resonates, you need a much richer understanding of your audience’s motivations, concerns, habits, and emotions.
This is where AI, specifically machine learning, can help you gain an edge.
Machine learning models are designed to analyze massive amounts of real-world data like social media conversations, customer reviews, search behavior, and even comment sections. It then finds patterns that would be impossible for a human to detect manually.
These machine learning models can:
- recognize emerging topics people are talking about
- uncover common frustrations or pain points
- identify seasonal shifts in interests
- and even detect how sentiment toward brands, products, or ideas changes over time
For example, by analyzing thousands of conversations across platforms like Reddit, LinkedIn, or product review sites, machine learning can surface that your target audience is suddenly much more concerned with topics like green dry cleaning methods or new science fiction comic books. This enables you to stay ahead of the curve and produce timely, relevant content on these topics.
Putting ML Research Into Practice
To put machine learning into practice in your topical research, start by using AI-powered social listening tools or audience intelligence platforms to monitor industry conversations and trends. Then, look for recurring themes, unanswered questions, or emotional hotspots that your brand can authentically address.
Regularly updating your audience insights — even monthly or quarterly — ensures that your content strategy remains aligned with what your audience truly cares about at the moment. Not just what you assumed six months ago. You may have noticed things change quickly these days, folks!
The result? Content that feels timely, thoughtful, and deeply connected to the real conversations your audience is already having right now.
AI Means Instant Content Idea Generation
One of the biggest challenges for marketers is keeping the content engine running with fresh, relevant ideas. AI can be an invaluable brainstorming partner.
Instead of pulling ideas out of thin air like a cheesy Las Vegas magician, AI uses machine learning to scan search trends, online conversations, competitor sites, and emerging news. It then suggests topics, formats, headlines, and even new angles.
AI doesn’t just generate random ideas—it identifies patterns in what audiences are engaging with and surfaces suggestions based on real-time interest.
For example, it might notice that searches for “recent Superman comic books” have spiked with a new Superman film on the horizon (we’re excited!), and recommend several Superman-comic-book-related blog post ideas you could pursue immediately.
To put this into practice, experiment with AI writing assistants and idea generation platforms to explore the possibilities. You can even use tools like Google Trends and AnswerThePublic with an AI layer added.
Start a brainstorming session by asking for variations on a topic you want to own. Then, add your own strategic filter. The goal isn’t to copy and paste AI ideas, but to refine them into high-quality, on-brand content that stands out.
Competitive Analysis Made Easy
Your competitors aren’t just fighting for the same customers — they’re also offering valuable clues about what’s working (and what isn’t) in your space. AI makes it much faster and easier to analyze competitor websites, blogs, and SEO performance without spending hours manually combing through everything.
Machine learning tools can scan large volumes of competitor content and identify patterns, such as:
- topics they frequently cover
- content gaps they’re leaving open
- keywords they’re ranking for that you might want to target
AI can also compare backlink profiles and engagement metrics to spot opportunities for differentiation. You can put this into action by setting up automated competitor monitoring through SEO tools that integrate AI analysis.
Look for areas where your competitors are thinner than the plot of the latest dating reality show—underserved subtopics, outdated guides, and unanswered customer questions. Then use that intel to strategically build content that fills the void and positions you as the better, fresher, and more authoritative option.
Finding Your Own Content Gaps with AI
Even if you’ve been publishing consistently, chances are there are valuable topics you’re missing. Content gap analysis, powered by AI, can quickly identify where your site is missing opportunities compared to competitors, trending search queries, or audience interests.
Machine learning scans your current content inventory, compares it against what’s ranking well, and highlights topics, questions, or themes you haven’t fully addressed. It can also help you identify whether you’re thin on specific stages of the buyer’s journey. For example, too much top-of-funnel awareness content and not enough bottom-of-funnel conversion material.
To put this into action, audit your existing blog posts, landing pages, and resources using an SEO tool that offers content gap insights. Then, map out a few priority clusters you could strengthen.
Filling content gaps isn’t just good for SEO — it also makes your brand a more comprehensive resource, which builds audience trust and topical authority over time.
Real-Time AI-Driven Sentiment Analysis
Creating content that resonates means understanding not just what people are saying, but how they feel. AI-driven sentiment analysis scans thousands of:
- brand mentions
- product reviews
- comments
- social media posts
to detect emotional tone. It then classifies mentions as positive, negative, or neutral.
Behind the scenes, machine learning models are trained to recognize emotional language patterns, such as excitement, frustration, skepticism, or gratitude. Even when the words aren’t obvious. This gives you a real-time window into customer attitudes, pain points, and brand perceptions.
Use AI to monitor sentiment around your brand, your competitors, and your broader industry. If you notice rising anxiety around a topic your company addresses, consider creating reassuring content that directly addresses those concerns. If you see growing enthusiasm for an innovation, you can lean into that trend and position yourself as a forward-thinking leader. After all, sentiment data doesn’t just guide what you say, it can also influence how you say it.
Other Ways to Use AI for Your Content Strategy
Topical research is just one part of the content planning puzzle. AI can also play a much bigger role in shaping your overall content strategy.
By using AI-driven tools, you can not only uncover great ideas but also
- organize them into smart topic clusters
- build long-term editorial calendars
- repurpose content for optimized use across other channels (like social media or email)
Machine learning models can analyze past engagement data, competitive trends, and search volume forecasts to help you make more informed, data-backed decisions at every stage of the planning process.
Check out our blog post on how AI can support your whole content strategy.
Why AI is a Game-Changer for Topical Research
Incorporating AI into your content topic research process doesn’t just save you time and hassle—it sharpens your strategy and amplifies your results. With AI doing the heavy lifting on data analysis, you can focus more on creating high-value, human-centered content that connects with your audience.
That said, remember: Generative AI is still experimental. Use it to assist and enhance your work, not to replace your creativity and critical thinking. When you strike the right balance, AI becomes a powerful partner in creating smarter, more effective content strategies.
Want help with incorporating AI into your content marketing strategy? Let’s talk!