Disinformation security: the three pillars, and where narrative threat intelligence fits
Disinformation security is the enterprise discipline Gartner organises around three pillars: content authenticity, impersonation prevention and narrative intelligence. AI Uniti works across all three, because a narrative-driven attack is one event: a synthetic asset, the accounts posing as you, and the coordinated network pushing both. Narrative threat intelligence is our name for that combined capability.
One attack, three pillars
Gartner treats disinformation security as its own enterprise discipline and organises it around three pillars. Each answers a different question about the same attack. Our lead category is narrative threat intelligence; Gartner’s vocabulary is the bridge buyers now search with, so this page maps one to the other.
Content authenticity
Is this image, video, voice or document genuine or synthetic? Content authenticity judges the asset. It matters because synthetic media is now cheap to produce and convincing enough to pass a casual look, and because an attack often starts with one synthetic asset.
Impersonation prevention
Is this account, domain or voice who it claims to be? Impersonation prevention detects accounts, domains and media that pose as your organisation or your people, from a lookalike support account to an audio call in your chief executive’s voice.
Narrative intelligence
How is this story forming, who is driving it, and is the spread organic or coordinated? Narrative intelligence reads the behaviour behind a narrative rather than the wording of it: timing, synchronisation, account history and network structure.
The convergence: digital trust and authenticity platforms
Gartner’s research now describes these tools converging into a wider category, digital trust and authenticity platforms (Gartner, “Emerging Tech: AI Vendor Race: Eroding Digital Trust Threatens the Global Economy, Forcing Adoption of Digital Trust and Authenticity Platforms”). Gartner describes integration with the wider security stack as the direction of the market.
For buyers, that means two things:
- Fewer, wider platforms. Separate point tools for deepfakes, impersonation and narrative monitoring give three partial views of one attack. Consolidation puts them in one picture that security, finance, legal and communications can all work from.
- Behavioural evidence becomes the differentiator. When every platform can flag a suspect asset, the question that separates them is whether the verdict traces to evidence you can defend: who pushed the asset, when, and whether the spread was organic or coordinated.
What the numbers say
Every figure below is Gartner’s, attributed to the public source it comes from.
| Figure | Source |
|---|---|
| 41% of CISOs reported at least one social engineering incident involving a deepfake on an employee audio call in the previous 12 months; 36% on a video call | Gartner, “Gartner Survey Finds 41% of CISOs Reported At Least One Social Engineering Incident Involving a Deepfake in the Past 12 Months”, press release, 22 September 2026 |
| By 2027, more than 70% of all digital content will be synthetic | Gartner, “Understand the Deepfake Detection Market” |
| In 2030, enterprises will spend more than US$25 billion authenticating digital content | Gartner, “Understand the Deepfake Detection Market” |
| By 2027, 50% of enterprises will be investing in disinformation security, up from less than 5% | Gartner, “Gartner Predicts 50% of Enterprises Will Invest in Disinformation Security and TrustOps by 2027”, press release, 20 November 2025 |
How Gartner’s terms map to ours
| Gartner term | AI Uniti term | Product |
|---|---|---|
| Narrative intelligence | Narrative threat intelligence | Signal |
| Impersonation prevention | Executive and brand impersonation detection | Signal and PulseCheck |
| Content authenticity | Synthetic media verdicts | The authenticity layer inside Signal |
Disinformation security vendor, narrative intelligence vendor, or deepfake detector?
All three, because the attack is one thing. A deepfake of a chief executive on its own is a content question. The same deepfake, pushed by a coordinated network across three platforms before market open and amplified by accounts posing as the company, is a security, financial, reputational and executive-protection event. Signal is the behavioural evidence layer of that picture: deepfake detectors judge the asset; Signal shows the network pushing it, when, and whether the spread is organic or coordinated, with verdicts that trace to evidence.
Narrative intelligence is also not social listening. Listening tools count mentions and score sentiment, which is exactly what a coordinated campaign is built to imitate. We set out the difference in behavioural intelligence versus social listening.
Where to go next
- The full argument, with the four risk domains and five questions for the board: our September 2026 white paper, Narrative-Driven Attacks, free to read on the page.
- The June analysis of the category and Gartner’s 2027 forecast: disinformation security is now enterprise risk.
- The operating model that owns the response: TrustOps.
- How detection, intelligence and defence fit together: the unified narrative-threat stack.
Frequently Asked Questions
What is disinformation security?
Disinformation security is the enterprise discipline of detecting and countering coordinated narrative manipulation, impersonation and synthetic media that target an organisation's market, brand or leadership. Gartner organises it around three pillars: content authenticity, impersonation prevention and narrative intelligence.
What is a digital trust and authenticity platform?
It is the category Gartner uses for the convergence of disinformation security tools into fewer, wider platforms that establish whether content, identities and narratives can be trusted. In our words: one platform that answers whether the media is real, whether the account is who it claims to be, and whether the spread is organic or coordinated.
Is narrative intelligence the same as social listening?
No. Social listening measures the volume and sentiment of what is said. Narrative intelligence, and narrative threat intelligence as AI Uniti practises it, measures the behaviour behind the conversation: who is driving it, whether the accounts act in concert, and whether the spread is organic or manufactured.
How does AI Uniti map to Gartner's three pillars?
Narrative intelligence maps to narrative threat intelligence in Signal. Impersonation prevention maps to executive and brand impersonation detection in Signal and PulseCheck. Content authenticity maps to the synthetic media verdicts in the authenticity layer inside Signal, assessed alongside the network pushing the media.
Do we need all three pillars?
A narrative-driven attack usually uses all three at once: a synthetic asset, accounts posing as the organisation or its executives, and a coordinated network that pushes both. Covering one pillar leaves the other two parts of the same attack unseen, which is why the market is converging on platforms that combine them.