Technology

Managing unstructured data in the era of AI

July 30, 2025
5 minutes

What’s stopping organizations from understanding 80% of their own data?

Unstructured data, everything from emails and meeting transcripts to PDFs and chat logs, accounts for the majority of enterprise information—as much as 90% of all data, by some estimates. Yet most organizations still struggle to make sense of it.

During Linkurious Days London, we sat down with Aidan Troy, Executive Vice President, EMEA at Nuix, to discuss how businesses can better gain value from their unstructured data. In this interview, he shared practical insights on why managing unstructured data has been so hard for so long, how AI is changing the game, and why off-the-shelf tools are key to staying ahead.

What makes unstructured data so hard to manage? 

Unstructured data holds valuable insights about how decisions are made, how teams collaborate, and where risks might be hiding, but it’s often locked away in formats that aren’t easy to process. That’s a missed opportunity, especially in fields where speed, accuracy, and context matter, like anti-fraud investigations, intelligence use cases, or law enforcement activities.

As Aidan Troy, Executive Vice President, EMEA & APAC at Nuix, points out:

“Many of our customers have been investing for years on managing the 20% of their data that is structured. The unstructured data space is less well invested, less well understood.”

That 80% includes the messy, human side of business: decision-making trails, documents, correspondence, recordings, and context that live in formats like emails, videos, PDFs, or transcripts. And the problem isn’t just scale, it’s complexity and fragmentation.

Three major challenges make unstructured data difficult to work with 

  • It’s everywhere: Unstructured data lives in countless tools and platforms. “I join you on one call on Zoom, I go to another on Teams… the fragmentation of tools is the second big challenge,” Troy notes.
  • It lacks structure by definition: Unlike rows and columns, unstructured data has no predefined format. That makes it hard to search, store, or query without specialized technology.
  • No one-size-fits-all analysis: “The insights, the questions, and the interrogation that an organization would like to do with their unstructured data varies enormously, even within an industry,” Troy explains.

The impact of AI on unstructured data analysis 

AI promises to make unstructured data analysis scalable, but only if paired with the right infrastructure. One of the key technologies driving this promise is natural language processing (NLP).

NLP has opened up new possibilities for understanding unstructured data. It allows machines to parse human language, extract meaning, and detect patterns in formats like emails, PDFs, chat logs, and more.

That means businesses can now search, classify, and make sense of vast amounts of messy, human-generated content, something that would have been too resource-intensive or inconsistent to tackle manually.

But AI alone isn’t enough. Without the right infrastructure, even the most advanced models can fall short. To turn raw text into real insights, organizations need tools that can handle the complexity of unstructured data at scale: storing it securely, processing it efficiently, and ensuring outputs are trustworthy and traceable.

Build vs. Buy: Why DIY approaches fall short 

As Aidan Troy points out, many organizations fall into the trap of trying to build their own solutions:

“You can always do the proof of concept using your development teams. making it industrial scale, fit for purpose, so that it doesn't break, and it can always be tracked, that's where the real difficulty is.”

To truly scale AI for unstructured data, businesses need platforms that are built for the job. Here's why purpose-built solutions outperform DIY efforts:

  • They’re secure and auditable: With built-in governance, security, and compliance, they reduce operational and regulatory risk.
  • They’re ready for production: No need to reinvent the wheel or rebuild prototypes into scalable tools.
  • They evolve with AI: As Troy puts it, “Two years ago, nobody had ever heard of ChatGPT… Now, the world is using it.” Platforms must be able to adapt as new models and technologies emerge.

From raw content to real insight 

For Nuix, the priority is clear: “We’ve had 20 years building up our expertise and our technology to deal with unstructured data,” says Troy. That includes indexing, categorizing, and making it usable for human investigation and analysis.

Nuix Neo provides an unstructured data intelligence foundation for this process. Its AI-powered processing engine can ingest and process more than 1,000 file types, transforming complex structured and unstructured information into clean, analysis-ready data.

But Nuix doesn’t stop at structure, they now enable analysts and investigators to visualize and analyze the connections hidden inside the mess to uncover meaningful information.

With Linkurious inside, Nuix Neo, Nuix’s unstructured intelligence platfom, combines cutting-edge natural language processing with intuitive graph technology to help investigators make sense of complex, connected data. It’s designed to lower the barrier to advanced link analysis, eliminating the need for large teams or niche technical skills. Nuix takes care of ingesting, processing, and enriching unstructured data, while Linkurious brings those relationships to life through interactive graph visualization.

“More and more, people are looking to use visualization as a much more human-centric way of interacting with data,” Troy explains. 

From knowledge gaps to clarity 

The real goal? Combine the 20% of structured data with the 80% of unstructured content, at scale, with speed, and without needing a team of experts.

When organizations fail to connect these dots, “it leaves gaps in understanding, gaps in knowledge, gaps in execution,” Troy says. But with the right tools, those gaps become opportunities.

By combining Nuix’s unstructured data intelligence capabilities with Linkurious’ graph visualization and analytics, organizations can transform fragmented structured and unstructured information into connected intelligence. Investigators can explore relationships alongside the underlying context, uncover hidden connections and make faster, more defensible decisions based on a more complete picture of their data.

Watch the full interview with Aidan Troy 

Want to hear more about how AI and graph technology are transforming unstructured data analysis? Watch the full interview. You can also access the white paper “From raw data to rich insights: Unlocking the power of unstructured data”.

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