Artificial intelligence (AI) has been around for about 7 decades, constantly sprouting advanced concepts like machine learning (ML), robotics, natural language learning (NLP), computer vision, deep learning, and sentiment analysis, among others, over time.

All these powerful AI technologies have helped businesses dive into market trends and peek into customers’ brains to make accurate, mission-critical decisions.

Cut to November 2022, generative AI (GenAI) stormed onto the scene. It’s been just about 2 years, and answer engines like ChatGPT, Gemini, and Perplexity have already become central to boardroom discussions and everyday workflows.

Read the latest tech news, and you’ll find GenAI hogging more than half of them. 

Of course, GenAI has been a welcome addition to the business ecosystem. You use it to brainstorm specific topics and ideas, conduct quick research, generate stunning images, and convert lengthy content into easy-to-understand summaries.

But, there’s one area where GenAI has truly shone for businesses, where traditional AI technologies have somewhat struggled: Making sense of the unstructured data.

Buried Insights: The Massive Challenge of Unstructured Data

Every organization produces tons of unstructured data—say, meeting notes, emails, chat logs, customer-facing calls, PDFs, customer reviews, and product roadmaps. Unlike structured data, these insights don’t fit nicely into rows and columns, making them difficult to store, search, and analyze.

For years, businesses have turned to traditional AI solutions to house customer and industry-related information. While many captured it, few managed it well or made sense of it. That said, employees have had to dig for relevance and meaning from unstructured data and consistently update the systems. That was not only cumbersome but also created minimal value.

Imagine this: Valuable insights from team meetings scattered in meeting docs, emails, or even personal notebooks. Key conversations are siloed in call recordings, proposals, presentations, or support logs because employees can’t understand the key concepts well. All this crucial data remains buried in systems and documents that could illuminate strategic business needs.

So, what’s so big deal about it?

Here’s a quick reality check: In 2022, unstructured data made up a whopping 90% of the overall organizational data—only 10% was structured.

And get this: the world will store a staggering 200 zettabytes (ZB) of data by 2025.

This screams a massive gap in how businesses use data, leading to missed opportunities, frustrated customers, and business strategies that simply fall flat. 

Generative AI To The Rescue!

Organizations are swimming in data. While this “messy” data hides incredible insights, unlocking its real value is no cup of tea.

Fortunately, generative AI (GenAI) has changed all of that. Now, businesses can use unstructured data in countless ways, inventing new use cases every single day.

So, How Exactly Does Generative AI Help Here?

GenAI feeds on a huge corpus of data to learn and interpret how we humans communicate. Thanks to this immense training, coupled with its existing capabilities, it analyzes the context—tone, meaning, and intent—within the data. And that too within a few minutes.

This cutting-edge capability opens a plethora of use cases for your business:

• Quick Summaries: Get crisp, clear takeaways from lengthy reports, meetings, audios/videos, or feedback.
• Key Insights: Easily pull out important terms, keywords, topics, and subtopics from large bodies of text like news articles and research papers.
• Smart Organization: Automatically sort transcripts, reviews, or responses into predefined categories based on sentiment and intent.
• Spotting Trends: Analyze customer-facing conversations to find gaps in your processes, predict what they’ll need, and explore growth avenues. 
• Understanding Emotions: Find out how customers actually feel from their feedback—rant or compliment—across social media and news aggregator platforms.
• Personalized Experiences: Use captured insights to deliver at-scale personalized experiences to customers. 
• Creating Drafts: Turn raw notes from docs, meetings, and even handwritten scribbles into polished drafts.
• Breaking Down Silos: Organize scattered inputs from multiple teams into actionable outputs, keeping everyone on the same page.

Here are some examples:

Content Writing

• Unstructured data: Jotted-down notes and rough ideas.
• GenAI Output: Polished blog drafts, clear content outlines, and ready-to-publish social media posts.
• Example: You’re brainstorming with Gemini on a topic. You share your thoughts, notes, and ideas, and instruct Gemini to create a structured outline for a 1000-word article.

Digital Marketing

• Unstructured Data: Raw survey results, customer reviews, and campaign feedback.
• GenAI Output: Deeper insights, common customer questions (FAQ), and refined branding strategies.
• Example: You instruct ChatGPT to find out why people love your customer service software based on the reviews (squeezed out from a PDF file).

The Catch: Where Generative AI Still Needs Work

It’s not all that rosy with GenAI. Here’s why:

The “Messiness” Makes Mapping Difficult

Unstructured data has unlimited variants due to its non-formatted nature. Take invoices, for example. You think an invoice is just a list of items and prices, right? Ummm…No. That’s not how GenAI sees it.

If you get 50 invoices from your vendors, no two might look the same. They’ll have their own schemas. What’s more, every invoice has various types of discounts. Some are for buying a specific quantity, others for being a long-time customer, or even special deals for specific products.

These aren’t just a simple “Discount: 10%.” The generative engine needs to understand why there’s a discount and how the vendor has calculated it. This often involves reading the surrounding text and understanding the context.

So, automatically pulling out these insights becomes one hell of a task than just looking for a simple “total.”

You’ll need to consistently and accurately map them to a common schema (most notably JSON schema) every single time. In other words, you have to enter very detailed instructions—sometimes hundreds of lines long.

That’s a lot of business logic and human expertise.

Still In Its Early Days

GenAI bridges the gap between messy data and the neat, structured systems businesses use. But let’s not double down on it. Right now, it’s still slow, not worth the money, and only handles small data chunks at a time. This is a challenge, even for small businesses, which generate data in terabytes (TB).

Plus, GenAI has much smaller context windows than the enormous volumes organizations need to sift through regularly.

Time to Dig Into The Underutilized Asset

Data is the fuel that drives AI engines. But that tank has mostly been empty because an enormous portion of enterprise data is unstructured—and for too long, it has sat largely untapped. Most businesses couldn’t figure out how to “fill the tank.”

Thanks to GenAI, an unexploited treasure trove is now up for grabs, with more and more organizations making it a crucial component of innovative and analytical enterprise applications. Tap into this incredible opportunity before that ship sails!

That said, unstructured data boasts varied complexity—a wide-ranging spectrum. At its lower end, traditional AI solutions work pretty accurately and without hurting the bank balance. GenAI is yet to tick that checkbox.

But, for workflows that demand human expertise due to the complexity and the unlimited data variance, GenAI is a promising technology to automate such agentic systems and free humans.

So, the question is: are you ready to harness more of your enterprise data, and especially that rich human-generated unstructured goldmine, as you implement AI-enabled systems? The answer should be a big fat “Yes.”

SEO has done a full 180!

Almost a year ago, people focused solely on improving their brand’s SEO, looking for “7 Organic Strategies to Boost Site Rankings.”

But now? My LinkedIn and Instagram feeds are brimming with posts like “How to Get Your Brand Into Gen AI Responses” and “How Zero-Click Searches Are Changing SEO.”

SEO isn’t just about dropping well-placed keywords/phrases, evenly sprinkling hyperlinks/backlinks throughout an article, or updating the content with recent statistics and better examples.

It’s also about ensuring that generative AI platforms—large language models (LLM)—like ChatGPT, Perplexity, and Gemini understand and recommend your brand in their answers. Otherwise called generative engine optimization (GEO) or LLMO.

The question is, how to improve your brand’s GEO? I’m about to show you how with these five simple strategies. Use them to rewrite your SEO playbook, and your traffic metrics will thank you.

Stamp Your Authority

Authority matters more than ever in Gen AI platforms. You need to prove you know your stuff to pop up in AI-generated responses. Authoritative elements boost the odds of a content getting pulled into AI-powered search tools by 30-40%.

How to make your content a trustworthy information source?

• Add a fact or quote from a reliable source. For instance, in pieces associated with history, culture, society, and people.
• Drop in relevant stats to strengthen your arguments, for example, when writing on law and government or expressing opinions that might spark a controversy.
• Share valuable industry insights through your own research-heavy thought leadership content pieces or personal experiences.
• Include subject matter experts (SME) within your business in the writing process. Ask them for fresh insights and quotes, or maybe numbers to make your article stand out. Have them review your article. They’re the ones who’ll walk you through the ground reality of the topic you’re writing on.

Remember, always ensure the statistics you add are up-to-the-minute. I’m talking about the primary sources of the statistics here, not those hyperlinks that trap you into a loop of clicks and redirecting, only to find out that the numbers are years old. I prefer adding data that’s at max a year old or maybe two. Not before that.

Also, take stats from high domain-authority (DA) websites, think Forbes, IDC, McKinsey, Deloitte, and Wall Street Journal, to name a few.

In a nutshell, a nuanced understanding, a thunderbolt insight, a personal experience, and a playful choice of words—these elements uplift a content piece from mind-numbing to mind-blowing.

Write For Humans (Too)

Gen AI platforms run on natural language processing (NLP) to provide information summarized into easy-to-understand responses. That means your content should feel like a chat with a friend not a boring lecture.

Now don’t start writing “F-laced” content pieces or add dozens of “uhhh” and “ummm” to make them human-like. Don’t channel your inner “Sam Jackson” into writing content pieces. Absolutely not!

Your content’s tone and style should mimic how we humans speak and how we enter voice/text queries. If needed, break the rules of grammar and convention to change the content rhythm to avoid readers dozing off. (Don’t worship Grammarly like a God)

• Pose titles/headers/sub-headers as questions.
• Turn cliches into puns or humor.
• Use first- or second-person voice to strengthen your brand narrative.
• Pay special attention to intros and outros, where robotic and obvious statements could get skipped over by LLMs. Make the intros, in particular, engaging and thought-provoking that make the readers scroll down in interest.
• Include long-tail keywords as they are less competitive and satisfy user intent more specifically. For instance, for a generic keyword “Weight Loss,” you can add long-tail keywords like “How to lose weight fast for women over 40.”

Create Content That’s Easy to Skim

Keep your content simple and easy to read. People can’t follow information presented in an overly complex manner, nor do AI-enabled search platforms. They don’t read like us—they scan patterns and key points to interpret your message accurately.

Of course, many will still read an entire article, but when writing online, you want to hook readers and draw their interest to the sections they most want to read.

Here’s how you can organize your articles:

• Logical heading hierarchy from H1 through H4 to help readers skim and bots understand context.
• Bullet points and tables to summarize data at the end (key takeaways) or when explaining benefits, features, or how-tos in crisp sentences.
• Short sentences and paragraphs wherever possible for more clarity. I know it’s jarring, especially for those writers (including me) who enjoy a good, long, meandering sentence. But let’s not deny that trimming your texts helps both humans and LLMs follow your train of thought without derailing.
• A series of high-quality images with descriptive captions and alt texts in between sections helps readers digest your article quickly.
• Make your content visually appealing with infographics, graphs, and videos. The more media readers can gather information from, the better (within reason!).
• Add a dedicated FAQ section to get your content featured in the “People Also Ask.”

Don’t Underestimate UGC Platforms

People want to know what others are talking about your brand or offerings that they are interested in online. Community-based platforms, most notably Reddit and Quora, best serve the purpose. Reddit, for instance, hosted 108.1 million daily active users (DAU) during Q1 2025.

“Our content is particularly important for artificial intelligence (“AI”) – it is a foundational part of how many of the leading large language models (“LLMs”) have been trained.” – Reddit, S-1 filing with the SEC.

In fact, Reddit is one of the primary sources of user-generated content (UGC)—Google even tied up with the platform in early 2024 to use its answers to train its LLMs.

Multiple leading LLMs are already tapping into public web data when giving responses. And why not? Such online forums and news aggregators are a UGC goldmine. So, strengthen your brand footprint in these platforms by:

• Building a community of people who love your product/services
• Hosting transparent “Ask Me Anything” (AMA) regularly
• Partnering with niche influencers
• Publishing in-depth technical analysis of industry trends, challenges and opportunities
• Showcasing expertise in relevant industry discussions

These tactics work wonders only if you engage with users without any salesy ick. Remember, users quickly identify and reject it promotional content (like spamming subreddits with links to your website), but welcome valuable insights.

Don’t Ditch Traditional SEO (Please!)

Different Gen AI tools pull data from different search engines. For instance, ChatGPT banks on Bing search results, while Gemini and Perplexity use Google search data. So, don’t think that traditional SEO is dead or about to fade out soon, ever.

Still don’t believe me?

A 2025 study analyzed 10,000 high-search-volume, purchase-intent queries and found a strong correlation (~0.65) between organic rankings and LLM brand mentions. This correlation strengthened when filtering out forums, aggregators, and social media, focusing on solution-focused content.

Moral of the story? GEO builds on the core SEO principles.

Innovate, Adapt, and Lead The Traffic War

While the playbook to sneak into AI-generated responses is still being written, one thing is crystal clear: you need to plug into LLMs to make your brand visible.

Context is the real gold; it’s time to mine it.

When you create conversational, structured, and authoritative content and combine these efforts with solid technical optimizations, you’ll see your content popping up in both traditional search engine results and LLM-generated responses.

Mastering this shift isn’t just an upgrade—it’s the key to staying ahead in the race for relevance.