It’s easier than ever for bad actors to manipulate public opinion, damage reputations, and destabilize institutions. Thanks to generative AI, hundreds of convincing articles, fabricated social media posts, or deepfake videos can be produced in a single day, in any language, quickly and cheaply.

Countering narrative threats requires a new way of thinking. Typically, organizations use some form of social media monitoring to protect themselves—but these tools pick up on the wrong signals. By the time you get an alert, a divisive narrative  

Increasingly, the perpetrators of these campaigns targeting organizations are growing more sophisticated, often using the same methods and infrastructure as a cyber attack. Your tools, too, have to keep up.

What is Narrative Intelligence?

Narrative Intelligence seeks to answer “who” is attempting to influence an organization’s information landscape, how they are doing it, and why. It seeks to determine whether any narratives are coordinated and engineered. In other words, are these narrative threats?

Behavior is the key, not necessarily the content of the narrative itself.

Here are some behavioral signals Narrative Intelligence picks up on:

• Who's behind the account: Their history, their patterns, and whether their behavior looks like a real person or something more manufactured

• How accounts work together: Whether there’s any coordination that points to something manufactured rather than organic activity

• What's artificially boosting the content: Likes, shares, and engagement that looks inflated beyond what the content would naturally earn

• How far and how fast it's spreading: The path a piece of content takes across platforms, and whether that movement looks organic or engineered

• What's running underneath it: Bots, fake accounts, and synthetic activity that exists purely to make a narrative look more credible or more popular than it actually is

The information landscape is filled with noise, but organizations that measure who or what is shaping their information environment, through which channels, and toward what action can respond before a false claim moves a stock price, a synthetic video of an executive defrauds customers, or a manufactured controversy makes it to mainstream news outlets.

Read more about LetsData’s methodology for detecting narrative threats in the Narrative Intelligence Framework.

Answering the right questions

There are several adjacent terms in this space that describe useful work, but none of them is sufficient for the problem narrative intelligence addresses.

Social listening is designed for marketing teams who want to know how a campaign that they’ve launched is landing with their audience. It counts mentions and measures sentiment. It is not designed to determine whether a wave of mentions or reposts is organic. That requires real intelligence methods.

Brand monitoring tracks the appearance of trademarks, product names, and executive identities. It is a useful input, but a narrow lens. Coordinated operations by bad actors can harm an organization without mentioning its name directly—by targeting the industry category, the country of origin, specific regulatory stances, or particular customer demographics.

Open-Source Intelligence (OSINT) names a method of collecting information from open sources. This describes how information is gathered, not what is being looked for or why. Narrative intelligence uses open-source collection as one input among many.

Cyber Threat Intelligence tracks malware families, infrastructure, and intrusion techniques. It is built for a different threat class. The conventional enterprise security stack—SIEMs, EDR, vulnerability management—is designed to detect intrusions or attempts to breach their attack surface. A narrative attack can run at full tempo without triggering a single alert. CTI and narrative intelligence share tradecraft and frequently share adversaries, but they analyze different data objects and should not be collapsed into a single function.

One Framework for National Security and the Enterprise

There is a temptation to treat geopolitical influence operations and financially driven attacks against companies as separate problems requiring separate frameworks. They are not.

Coordinated inauthentic accounts, fabricated outlets, synthetic amplification, impersonation, seeding narratives across platforms, and the rented infrastructure underneath all of it do not belong to any single domain. The same tradecraft that prepares the ground for an electoral interference operation also funnels victims into an investment scam.

A government strategic communications team and a corporate security team are looking at one phenomenon through two windows. The underlying mechanics are the same: assets producing publications, coordinated activity advancing a narrative, incidents compiling into an operation. The target populations may differ, a national electorate versus a customer base, but the analytical model holds in both contexts.

Narrative threats are tools used by state actors, criminal networks, and commercial operators alike. The question for any organization with a public presence is no longer whether this applies to them, but whether they can see it coming.