How Disinformation Became a $417 Billion Enterprise Risk

QUICK ANSWERS

• What is the global economic cost of disinformation? Sopra Steria’s 2026 study estimates the global economic impact of disinformation at $417 billion for 2024, using an open, reproducible methodology modeled on IPCC-style scenario analysis, the same framework used to assess global climate risk.
• What is actually driving that number? $393 billion of the total comes from fraud, market manipulation, and commercially motivated disinformation.
• How is generative AI changing the economics of disinformation? Generative AI added an estimated 15–20% to the cost of financial fraud and manipulation in 2024, according to the Sopra Steria study’s median and exploratory scenarios. AI continues to lower the cost of running large-scale disinformation campaigns.
• Which industries face the greatest financial exposure to disinformation? According to the study, the financial sector bears a disproportionate share of the impact. Finance relies on trust and information, and those are two assets disinformation is designed to erode.
• Is $417 billion the full picture? Sopra Steria’s estimates range from $356 billion in its conservative scenario to $516 billion in its exploratory scenario. The $417 billion median is likely an undercount, as many losses leave no traceable origin.

Narrative attacks are now a financially material enterprise risk, and most organizations are measuring them too late. The damage can show up for organizations as fraud losses, market moves, and consumer pullback long after underlying harmful narratives begin circulating.

A new Sopra Steria study published in April 2026 quantifies what most organizations have only estimated: the global economic cost of disinformation. The report sets the figure at $417 billion for 2024, built on an open, reproducible methodology modeled on IPCC-style scenario analysis, the same framework used to assess global climate risk. $393 billion of that total is direct financial losses from fraud, market manipulation, and commercially motivated disinformation. Sopra Steria notes that the estimated $417 billion is conservative because the study can only count losses that can be tied to identified disinformation narrative attack campaigns.

The study measures economic consequences, not whether content is true or false. Truthfulness and factuality are not the primary variables in disinformation campaigns. What drives harm to organizations is information manipulation, threat-actor coordination, and the way narratives spread. Perception moves markets, customers, and stakeholders, regardless of whether the underlying content is factually true.

READ: The RAV3N Report: 2026 State of Disinformation Narrative Intelligence

In the report, the costs of information manipulation and narrative attacks fall into three distinct categories, each representing a different way it damages the economy.

1. Financial losses: fraud, market manipulation, and commercially motivated disinformation account for $393 billion.
2. Social costs: health consequences and the erosion of institutional trust, estimated at $9.8 billion.
3. Political costs: electoral interference and response spending, estimated at $14 billion.

These three categories do not operate in isolation. The political erodes the social. The social erodes the financial. Narrative attack campaigns behave like systems, not singular events. Financial damage is the endpoint of a long chain. Before that endpoint, there are months or years of narrative seeding, coordinated amplification, cross-platform migration, and trust erosion. Organizations that measure only the financial hit are measuring the last five minutes of a two-year campaign.

What is the global cost of disinformation, and what is driving it?

The global cost of disinformation reached $417 billion in 2024, with $393 billion of that driven by fraud, market manipulation, and commercially motivated information manipulation, according to Sopra Steria’s study.

The $393 billion in financial flows breaks down across several vectors. According to Sopra Steria’s analysis, commercially motivated manipulation is the largest, with fake online reviews alone accounting for an estimated $227 billion in distorted consumer spending globally. Online ratings influence 89% of e-commerce revenue. Manipulation at this scale shapes which products succeed and which do not.

AI-enabled deepfake fraud contributes $11 billion. In 2024, a major organization lost $25 million in a single synthetic-video transaction, with a CFO-level executive deceived during a deepfake video call. Romance investment fraud, where bad actors build extended relationships with victims before directing them into fraudulent schemes, accounts for another $5.5 billion in the crypto sector alone. The study also notes that 50% of businesses experienced deepfake attacks that year. Synthetic media has moved from an edge case to an operating condition.

Coordinated narrative attacks on markets are also a significant vector. Stock market losses attributable to disinformation reached $60 billion, equivalent to 0.05% of global market capitalization. These are the attributable cases. Many more sit outside the estimate because the narrative cannot be tied back to an identifiable campaign or actor, even when the market impact is clear.

How is generative AI increasing the cost of disinformation?

Generative AI lowered the cost and raised the accessibility of running disinformation campaigns. Sopra Steria’s analysis estimates that the economic impact of disinformation increased by 15–20% in 2024 as a result. The shift is not only in volume. It is in who can run a campaign and at what cost.

Generative AI has not simply made spreading disinformation quicker. It has made it accessible at a scale that was previously impossible. A single operator can now manage what previously required a coordinated team, using AI for content generation, persona management, and cross-platform amplification. Campaigns now adjust themselves as they run, shifting tactics, personas, and platforms based on what is gaining traction. The quality of synthetic content is now capable of passing casual human verification, which raises the need for verification platforms and the cost of AI verification across organizations and executives. The report states that AI-facilitated fraud is also increasing at 32% per year, with projected losses in the United States alone reaching $40 billion by 2027.

How do narrative attacks produce reputational and financial damages across an organization?

Narrative attacks cause reputational and financial damage across an organization because they operate as systems, not events, and the damage does not operate in silos. A coordinated narrative attack campaign shifts how stakeholders perceive an organization, which can lead to lost revenue and market moves that lead to financial and long-lasting reputational damage. The Sopra Steria study traces how eroded institutional trust drives consumer pullback, which then also shows up as fraud losses, market moves, and revenue impact months or years later. The study models the three categories of financial, social, and political costs independently to prevent double-counting, but in practice, they do not stay separate.

THE WAY FORWARD: Key Takeaways for Leaders

Narrative intelligence belongs alongside cybersecurity and fraud strategies in enterprise risk planning. Twenty years ago, cybersecurity moved from technical and marginal to strategic, budgeted, board-visible, and regulated. Narrative intelligence is on the same curve, but on a faster timeline due to the scale and speed of AI. Organizations that treat narrative attacks as a financially material enterprise risk, with the same rigor applied to cyber and fraud, will be positioned to navigate narrative risk with a proactive, strategic response.

• Invest in a narrative intelligence platform before a crisis hits. The cascade from narrative seeding to trust erosion to financial loss plays out over months. Narrative risk signals must be identified early. Organizations that invest in narrative intelligence enable themselves to respond strategically to narrative risk rather than absorb losses reactively.
• Treat narrative risk as an enterprise risk discipline. Executives across CISO, CRO, and Communications teams must integrate narrative intelligence into existing risk frameworks to separate organizations that navigate narrative attacks from those that absorb them. Resilience requires monitoring and a defined response plan established before a crisis, not assembled during one.
• Plan for what is not yet visible. The $417 billion figure from Sopra Steria is a median scenario built on attributable, documented cases. The true cost of disinformation is likely higher. Losses without traceable origins sit outside the estimate, even when their market impact is clear. Sopra Steria puts the choice plainly: “Act or endure”.

A response built on the full picture of who is driving a narrative and how it spreads enables organizations to act strategically rather than reactively. Organizations that adopt narrative intelligence and build response capabilities now will be better positioned to protect their executives, brands, and bottom lines.

“Unlike deepfake detection, it monitors narratives, identifies adversaries’ intent and pinpoints audience vulnerabilities before AI disinformation attacks can cause significant damage.“