Executive summary
AI Uniti detects narrative-driven attacks that create security, financial, reputational and executive-protection risk.
Gartner now treats this problem as its own security discipline. It calls the category disinformation security, describes three pillars (content authenticity, impersonation prevention and narrative intelligence), and predicts that by 2027, 50% of enterprises will be investing in disinformation security products or services and TrustOps strategies, up from less than 5%. In June 2026 it published an Emerging Market Quadrant dedicated to narrative intelligence vendors.
The threat has kept moving. A Gartner survey published on 22 September 2026 found that 41% of CISOs reported at least one social engineering incident involving a deepfake on an employee audio call in the previous 12 months, and 36% on a video call.
The language has caught up with what risk teams already see. Share prices, deposit bases, licences to operate and senior executives are being targeted by engineered narratives: seeded by coordinated accounts, amplified across platforms, reinforced with synthetic media, then exploited for money, leverage or harm.
Most organisations still meet this threat with tools built for something else. Social listening counts mentions and scores sentiment. Cyber threat intelligence watches infrastructure. Neither answers the question that matters in the first hours of an attack: is this real, or is it manufactured?
This paper sets out how narrative-driven attacks work, the four risk domains they hit, why conventional monitoring detects them late, and what a narrative threat intelligence capability needs to do. It closes with the questions boards and executive teams should be asking now.
The category now has a name
For several years, coordinated online manipulation sat between functions. Communications saw the noise, security saw the phishing that followed, and finance saw the market move. No one owned the cause.
Gartner’s framing changes that. Disinformation security is positioned as an enterprise capability, not a media monitoring add-on, and it is organised around three pillars:
- Content authenticity. Establishing whether an image, video, voice or document is genuine or synthetic.
- Impersonation prevention. Detecting accounts, domains and media that pose as your organisation or your people.
- Narrative intelligence. Understanding how a story forms, who is driving it, how it spreads and whether the spread is organic or coordinated.
Alongside this, Gartner’s marketing practice has advanced TrustOps: the operating model that connects marketing, communications, security, legal and risk around a shared view of trust threats. Gartner has specifically flagged the rapid rise of bot-generated fake brand outrage as a driver.
The implication for buyers is clear. Evaluating this capability through a marketing lens alone will under-scope it. The attack surface is the organisation’s reputation, but the impact lands on the balance sheet, the security team and named individuals.
Anatomy of a narrative-driven attack
A narrative-driven attack is a deliberate effort to create, accelerate or weaponise a story about an organisation or person, using coordinated and often inauthentic activity to make that story appear more credible, more widespread or more urgent than it is. Most follow a recognisable sequence.
- Seed. A claim, leak, rumour or synthetic asset is placed in a small number of channels, often low-visibility ones.
- Amplify. Networks of coordinated accounts engage in tight time windows to manufacture the appearance of organic interest.
- Correlate. The same narrative surfaces on other platforms within hours, giving the impression of independent confirmation.
- Launder. Journalists, analysts, retail investors or activists pick up the story in good faith. It now looks legitimate.
- Exploit. The attacker extracts value: a short position, a fraudulent payment, a phishing campaign, a policy concession, or pressure on a specific executive.
The critical period is between steps two and four. Once a narrative is laundered into mainstream coverage, the organisation is responding to a story, not an attack. Before that point, the coordination is detectable and the response options are far wider.
Four risk domains, one attack
The defining feature of a narrative-driven attack is that a single campaign creates risk in several domains at once, each owned by a different executive.
| Risk domain | How it shows up | Typical owner | Cost of late detection |
|---|---|---|---|
| Security | Phishing, fraud and social engineering that ride on a trending narrative; inauthentic support accounts; credential harvesting against staff and customers. | CISO | Breach, fraud loss, incident response cost |
| Financial | Coordinated claims timed against results, capital raises, M&A or short positions; deposit or customer flight triggered by manufactured panic. | CFO, CRO | Market value, funding cost, deal risk |
| Reputational | Manufactured outrage, fake reviews and coordinated activism that appear organic and set the media and stakeholder agenda. | CMO, Corporate Affairs | Brand equity, licence to operate, regulator attention |
| Executive protection | Deepfake audio and video of executives, impersonation accounts, fabricated statements, and targeting that can escalate from online to physical threat. | Security, General Counsel | Personal safety, authorised payment fraud, legal exposure |
Because ownership is split, response is split. Each function sees a fragment, and the organisation reacts in sequence rather than in concert. Detection has to produce one shared picture that every owner can act on.
Why conventional monitoring detects late
It measures what is said, not who is saying it
Social listening and media monitoring are built to track volume, reach and sentiment. A coordinated campaign is designed to look like organic volume and genuine sentiment. Measuring the output of a manipulation campaign does not reveal the manipulation.
It looks at one platform at a time
Campaigns are run across platforms deliberately, because apparent independent confirmation is what makes a narrative credible. Single-platform tools see several unrelated spikes. They do not see one operation.
It classifies content, and content is now cheap
Generative AI has made persuasive, varied and on-message content effectively free to produce at volume. Detection that depends on judging each post or asset individually will always be one step behind. Behaviour (timing, synchronisation, account history, network structure) is far harder to fake at scale.
It produces alerts that cannot be defended
A score from an opaque model is difficult to escalate to a board, a regulator, a platform or a court. Risk, legal and compliance teams need evidence they can explain, trace and repeat.
How AI Uniti detects narrative-driven attacks
AI Uniti is a narrative threat intelligence company. Its platform, Unite, includes Signal by AI Uniti for enterprise narrative risk intelligence and PulseCheck for account-level bot and scam detection. The approach rests on five principles.
1. Behavioural intelligence, not content scoring
Signal analyses how accounts behave: posting rhythm, synchronisation with other accounts, account age and history, engagement patterns and behavioural anomalies. It tells you who is driving a narrative, not only what the narrative says. Because it is not dependent on the wording of posts, it holds up as attackers change their content.
2. A bot-to-human spectrum
Accounts are not forced into a binary label. Each is placed on a spectrum from automated to authentic, which reflects how modern campaigns actually operate: a blend of automation, paid operators and genuine participants who have been drawn in.
3. Cross-platform correlation
Signal correlates activity across social platforms, video and news sources to identify when the same narrative, in the same time window, is being pushed through different channels. This is the pattern that single-platform monitoring cannot see.
4. Deterministic and explainable verdicts
Every verdict traces back to specific behavioural evidence. Risk, legal and security teams can see why an account or cluster was flagged, reproduce the finding and use it in escalation, platform takedown requests, regulatory engagement or legal action.
5. Detection linked to action
Unite adds an autonomous action layer to Signal, with fully audited and explainable working, so detection flows into a governed response rather than an inbox.
Mapped to the three pillars
| Gartner pillar | AI Uniti capability |
|---|---|
| Narrative intelligence | Signal: coordinated narrative detection, cross-platform correlation, clustering, alerting and reporting. |
| Impersonation prevention | Detection of accounts posing as the organisation or its executives, with behavioural evidence to support takedown. |
| Content authenticity | Synthetic media verdicts on suspect images, video and audio, fed into the same behavioural picture so a deepfake is assessed alongside the network pushing it. |
The value is in the combination. A deepfake on its own is a content question. A deepfake of your CEO, pushed by a coordinated network across three platforms in the hour before market open, is a security, financial, reputational and executive-protection event. It needs to be seen as one.
How the pillars fit together, and the platform category they are converging into: disinformation security, the three pillars.
Implications for executive teams
- Chief Risk and Chief Compliance Officers. Narrative manipulation belongs in the enterprise risk register with an owner, appetite statement and indicators. Explainable evidence is the prerequisite for reporting it credibly.
- General Counsel. Defensible, reproducible evidence of coordination strengthens takedown requests, disclosure decisions, regulator engagement and litigation.
- Chief Financial Officers. Results days, capital raises, transactions and short interest are predictable attack windows. Monitoring for coordination around them is a financial control.
- Chief Information Security Officers. Narrative campaigns are frequently the delivery mechanism for fraud and social engineering. They belong in the threat model and the SOC workflow.
- Chief Marketing and Corporate Affairs Officers. Knowing whether outrage is organic or manufactured changes the right response entirely. Responding to a bot network as if it were customers can amplify the attack.
- Executive protection. Impersonation and synthetic media now sit alongside physical security. Named executives need monitoring that covers both.
Five questions for the board
- Who owns narrative risk across security, finance, legal and communications, and is there a single picture they all work from?
- Could we tell, within hours, whether a surge of negative attention is organic or coordinated?
- What would we do in the first hour if a convincing deepfake of our CEO or CFO appeared before market open?
- Are our highest-risk windows (results, transactions, disputes, leadership changes) covered by active monitoring for coordination?
- Is the evidence we would rely on explainable enough to put in front of a regulator, a platform or a court?
If any answer is uncertain, the capability gap is real, and it is the gap attackers are designed to exploit.
About AI Uniti
AI Uniti is an Australian narrative threat intelligence company. It helps organisations understand whether digital behaviour is real, coordinated or manufactured, and act on that understanding before a narrative takes hold. Unite, the full AI Uniti platform, includes Signal by AI Uniti and PulseCheck.
Notes
- The 6 to 12 hour figure is based on AI Uniti’s analysis of 793,000 videos, the same basis as the detection window stated on our home page. Back to text
Sources
- Gartner, “Gartner Predicts 50% of Enterprises Will Invest in Disinformation Security and TrustOps by 2027”, press release, 20 November 2025.
- Gartner, “Gartner Says AI-Powered Disinformation Is Becoming a Brand Risk Marketers Can’t Ignore”, newsroom, 9 June 2026.
- Gartner, “Emerging Tech: The 3 Pillars of Disinformation Security Solutions”, 2025.
- Gartner, “Emerging Market Quadrant for Narrative Intelligence: Startup Vendors”, 26 June 2026.
- 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.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally. References are to publicly available Gartner material and do not imply endorsement of AI Uniti or its products. Gartner does not endorse any vendor, product or service depicted in its research publications.