Agentic AI: The Future of Exposure Management

For enterprise security leaders, validating vulnerabilities and maintaining effective exposure management are among the hardest and most resource-intensive challenges.

But this step is critical: 68% of security leaders use the number of vulnerabilities identified and resolved as the top metric to prove the success of their testing programs*. Validation is key to realizing ROI for exposure management.

As attack surfaces expand, teams face growing volumes of findings to verify, prioritize, and remediate. False positives, duplicates, and incomplete context slow decision-making and stretch already limited resources.

Traditional automation can help at scale, but it lacks the judgment and context needed to separate the critical from the irrelevant. That’s where agentic AI changes the game.

How Agents Transform Exposure Management

Validating vulnerabilities has always been a challenge in security operations. Traditional tools can detect issues, but they often create more noise than clarity.

Agentic AI reshapes exposure management by filtering noise, surfacing priorities, and structuring vulnerability data into contextual, actionable insight.

Most importantly, these agents don’t replace human expertise—they amplify it. With humans in the loop for oversight, agentic AI accelerates validation without sacrificing trust or accuracy. The result is faster fixes, less wasted effort, and a security team focused on real risks rather than false positives.

Introducing Hai as an Agentic AI System

HackerOne AI, Hai, has evolved from a single copilot into a coordinated team of AI agents that transform findings and complex data into clear, actionable guidance for continuous threat exposure management.

Together, these agents run 24/7 to keep exposures visible, validated, and under control. Each one tackles a critical challenge security teams face:

• Deduplication Agent: cuts the noise by flagging duplicates before they drain time and resources.
• Priority Escalation Agent: moves teams faster by surfacing high-risk exposures with business context beyond CVSS alone.
• Report Assistant Agent: helps teams fix smarter by turning submissions into validation-ready reports and reducing back-and-forth.
• Insight Agent: enables confident decisions by adding context, credibility, and impact analysis in seconds.

"Hai cut our validation time from 20 minutes to just 5. By replacing manual steps with clear context, we validate faster, clarify impact, and stay aligned."

—Connor Knabe, Application Security Architect at Veterans United Home Loans

Why It Matters for Exposure Management

The impact is clear:

• Focus: Eliminate noise so teams concentrate only on verified risk.
• Speed: Shorten validation cycles and accelerate developer coordination.
• Confidence: Enrich every decision with business context and precedent.
• Control: Align on top exposures to balance business impact, workflows, and ROI.

Over 70% of users cite time savings as Hai’s biggest impact, with some saving a full work week per month.

When teams have a clear view of true risk and confidence in their data, they move from reacting to issues to preventing them.

"Hai feels like having someone who knows every report that’s ever come through our program."

— Clara Andress, Bug Bounty Ops Manager at Zoom

Secure AI by Design

Speed means nothing without trust. That’s why Hai is built with security and privacy at its core, inheriting the same standards that safeguard the rest of the HackerOne platform: ISO 27001, SOC 2, FedRAMP, and GDPR compliance.

Hai never trains on or fine-tunes LLMs with customer or researcher data. Each response is scoped to the permissions of the user interacting with Hai; it can only access what you’re authorized to see.

And while agents work at machine speed, humans stay in control. Hai suggests, but you decide. Every action requires approval and is logged for transparency. To ensure constant assurance, Hai is also in-scope for HackerOne’s own bug bounty program, inviting security researchers to continuously test its authorization boundaries.

The Future of Offensive Security Testing

As AI reshapes software development and security, HackerOne is expanding that intelligence across the full offensive testing lifecycle from discovery to validation to proof of exploitability.

With HackerOne Code, now generally available, organizations can discover and fix vulnerabilities before applications are deployed. Built for the AI development era, it works like a developer and thinks like a researcher scaling vulnerability discovery with AI and human oversight.

Agentic Pentesting will take validation a step further. This breakthrough extends exposure management into adversarial validation, continuously proving exploitability at an AI-driven scale, while keeping human ingenuity at the core. 

Together, these advancements signal a shift in how enterprises approach exposure management from one-off testing and validation to a continuous, intelligent system of defense.

At the center of that evolution is Hai, the agentic AI system that connects insight, validation, and prioritization into one coordinated flow.

The Next Era of Validation

Today’s challenge isn’t just validating vulnerabilities, it’s understanding them in context, aligning teams, and taking decisive action before risk grows.

Agentic AI transforms how enterprises manage that complexity.

By connecting validation, prioritization, and insight, Hai strengthens every layer of defense, turning findings into confident, coordinated action.

This is the future of exposure management: human expertise amplified by AI, with trust at the center.

Learn more about Hai

*Survey methodology: HackerOne and UserEvidence surveyed 99 HackerOne customer representatives between June and August 2025. Respondents represented organizations across industries and maturity levels, including 6% from Fortune 500 companies, 43% from large enterprises, and 31% in executive or senior management roles. In parallel, HackerOne conducted a researcher survey of 1,825 active HackerOne researchers, fielded between July and August 2025. Findings were supplemented with HackerOne platform data from July 1, 2024 to June 30, 2025, covering all active customer programs. Payload analysis: HackerOne also analyzed over 45,000 payload signatures from 23,579 redacted vulnerability reports submitted during the same period.