Gartner doesn’t usually traffic in alarm. When the world’s most influential tech analyst firm publishes a forecast saying a quarter of enterprise GenAI applications will face recurring security breaches by 2028, it’s worth reading carefully.

The new prediction: 25% of all enterprise GenAI applications will experience at least five minor security incidents per year by 2028, up from just 9% in 2025. And the culprit the analysts are pointing to most explicitly isn’t prompt injection or model vulnerabilities — it’s MCP, the Model Context Protocol, and the broader architectural patterns of agentic AI.

The MCP Problem Is a Design Problem

MCP — the protocol that lets AI agents interact with tools, data sources, and external systems — was designed with a clear priority: interoperability and developer speed. Security was not the first design constraint.

Gartner Senior Director Analyst Aaron Lord put it directly: “MCP was built for interoperability, ease of use and flexibility first, so security mistakes can manifest without continuous oversight for agentic AI.”

The problem isn’t that MCP is broken. It’s that the protocol’s defaults and design patterns make it easy to create configurations where agents can access sensitive data, ingest untrusted external content, and communicate externally — sometimes all in the same workflow.

Gartner identifies this combination — sensitive data access + untrusted content ingestion + external communication — as the high-risk pattern that software engineering leaders should treat as a “no-go zone.” When all three factors are present in a single agent workflow, exfiltration risk is significantly elevated.

The Numbers Tell a Stark Story

  • 9% of enterprise GenAI apps experience 5+ minor security incidents per year today (2025)
  • 25% will hit that threshold by 2028 — nearly 3x growth in three years
  • 15% of enterprise GenAI apps will experience at least one major security incident per year by 2029, up from 3% in 2025

That last number is particularly striking. A 5x increase in major security incident rates over four years is not a gradual drift — it’s a compounding risk curve that tracks directly with MCP adoption and the deployment of agentic systems at scale.

Why Traditional Security Practices Fall Short

The challenge is structural. Most enterprise security practices were developed for traditional web applications: authenticate users, validate inputs, encrypt in transit, patch known CVEs. Those practices aren’t wrong — they’re just incomplete for agentic systems.

Agents introduce several new failure modes:

Ambient authority. An agent acting on behalf of a user often inherits that user’s permissions. If the user has broad access, the agent has broad access. A compromised or manipulated agent can act with legitimate-looking authority.

Chained actions. Agents don’t just respond to single requests — they chain multiple actions, often across multiple tools and data sources. A single misconfiguration can propagate through an entire workflow before detection.

Untrusted content ingestion. Agents that browse the web, read emails, or process external documents are ingesting untrusted content as part of their normal operation. This creates natural prompt injection vectors — an attacker can try to influence agent behavior by crafting content the agent will eventually read.

Continuous operation. Unlike a one-shot API call, agents may run for extended periods. Security oversight designed for discrete transactions doesn’t naturally extend to long-running autonomous processes.

What Gartner Recommends

The analyst firm’s recommendations for software engineering leaders are practical:

  1. Establish formal security review processes for MCP use cases. Don’t let agents be deployed with the same casual review process used for internal tools. MCP configurations deserve dedicated security assessment.

  2. Prioritize low-risk use case patterns. Explicitly identify which agent patterns are acceptable and which combinations are off-limits. The three-factor risk pattern (sensitive data + untrusted input + external communication) should be a hard stop.

  3. Use authentication and authorization designed for agents, not inherited from humans. Agent identity management is different from user identity management. Agents need scoped, auditable permissions — not inherited ambient access.

  4. Empower domain experts to define guardrails. Security teams alone can’t define what “normal” agent behavior looks like for a business workflow. Domain experts — legal, finance, HR — need to participate in defining what an agent should and shouldn’t be able to do in their context.

Paired with Unit 42: A Security Double-Header

Today’s Unit 42 research on Vertex AI Agent Engine misconfigurations and this Gartner forecast are painting the same picture from different angles. Unit 42 showed the specific mechanism — how over-permissioned agents behave like insider threats. Gartner is showing the scale — this isn’t an edge case, it’s an industry trend on an accelerating curve.

The practitioners who are taking agent security seriously today — treating agents as identity principals, applying least privilege, auditing agent behavior — are building institutional muscle that will be table stakes by 2028. The ones who aren’t are building up risk.

Sources

  1. Gartner: 1 in 4 GenAI Enterprise Apps to Face Recurring Security Breaches by 2028 — CXOToday
  2. Gartner MCP security forecast — VarIndia

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