Join us for an exclusive webinar led by ProcessUnity's Chief Trust Officer Dave Stapleton as we dive into how ProcessUnity transforms Third-Party Risk Management (TPRM) with AI. Together, we’ll explore the evolution of TPRM - past, present, and future - to better understand the role AI plays in shaping the field. See how tools such as predictive analytics and automated evidence reviews help you automate tedious assessment work, while future capabilities such as agentic AI will monitor and mitigate risks on your behalf. Leave with ideas from a seasoned TPRM and security expert on how to incorporate AI into your program and elevate your role as a subject-matter expert overseeing your organization's risk management strategy.

Key Takeaways: 

• Explore the innovative AI advancements and their use cases driving the future of TPRM. 
• Discover how to responsibly integrate and scale AI across your vendor portfolio. 
• Learn how AI integration is redefining the role of risk analysts, empowering them with deeper insights and expertise. 
• Communicate the ROI of AI in TPRM with important metrics to track 

Don’t miss this opportunity to prepare your organization for the future of TPRM and stay ahead with AI as your second-in-command.

Hear from security leaders as they reveal their cutting-edge strategies for managing cloud risks. Our panel will share insights on how they’re tackling the unique challenges of cloud security, including how they protect critical assets, measure risk reduction, and track progress with meaningful metrics. We’ll explore real-world success stories, examine how AI and automation play a role in improving efficiency, and discuss priorities for the year ahead. You will learn actionable steps to elevate your risk management strategy.

Cybersecurity has long relied on global models—threat intel feeds, vulnerability rankings, behavior baselines—built on the aggregation of telemetry across organizations. But the shift to cloud-native architectures, the explosion of software supply chains, and the operational limits of probabilistic prioritization (e.g., CVSS and even EPSS) are exposing the brittleness of these global models. The next frontier in defensible security decision-making is the integration of local models—statistical and causal models grounded in the specific configurations, assets, behaviors, and exposures of an individual environment.

This talk presents a practical framework for building and operationalizing local models in production environments. We’ll explore where local inference is outperforming global heuristics in vulnerability management, alert triage, and identity risk. Drawing from recent advances in telemetry-based modeling and on-premise LLMs, the talk will demonstrate how teams can move beyond generic scoring toward dynamic, environment-specific assessments—with measurable gains in precision and reduced mean-time-to-decision.

The audience will leave with a clear understanding of:

• Why global models are structurally limited in high-variance environments
• How to architect and deploy local models on real-world security data

Please visit our sponsors in the Exhibit Hall and explore their resources. They're standing by to answer your questions.

In large universities and colleges, cybersecurity governance often must span dozens of semi-autonomous academic departments, research units, student organizations, satellite campuses, and third-party collaborations. This complexity mirrors many enterprise environments undergoing decentralization through acquisitions, business-unit autonomy, or cloud-driven diversification. In this session, I’ll draw from my experience leading security in higher education and local government to show how we designed and evolved a governance model that enabled both alignment and flexibility. You’ll hear about our approach to defining guardrails, assigning risk ownership, enforcing standards, driving adoption across distributed units, and iterating governance over time.

Along the way, we’ll surface the trade-offs, cultural challenges, political dynamics, and architectural levers that shaped our journey. Whether your organization is formally decentralized today or headed in that direction, the lessons from academia offer a rich testbed for refining governance in complex environments.

Learning Objectives (What Attendees Will Learn):

By attending this session, you will be able to:

1. Map governance layers — Identify appropriate roles, responsibilities, and decision rights across central, domain, and unit-level stakeholders in a decentralized organization.
2. Design guardrails and adaptations — Define security standards, policy guardrails, and differentiated controls so units retain autonomy while staying within risk boundaries.
3. Drive adoption and alignment — Tactics for influencing, persuading, and partnering with semi-autonomous units to embed governance without friction.
4. Evolve governance over time — Mechanisms for feedback, course correction, and maturity in a shifting environment.
5. Anticipate pitfalls and trade-offs — Common tensions (e.g. flexibility vs uniformity, speed vs control, resource gaps) and strategies to mitigate them.

Models ingest unclassified data, generate unlogged decisions, and create new audit liabilities that most organizations aren’t tracking.

In this session, we’ll expose how AI adoption has outpaced the governance frameworks meant to protect it, and what CISOs must do now to regain visibility and control.

Key takeaways:

• The hidden risk stack: How AI pipelines bypass established data protection controls (DLP, encryption, access governance) and create new exfiltration vectors.
• Auditability vs. Accountability: Why model transparency and data provenance are becoming the new compliance frontier.
• Control by design: How to extend your existing governance, risk, and compliance (GRC) frameworks to cover AI lifecycle stages from data acquisition to model retirement.
• The path to assurance: Practical steps to implement AI auditing without slowing innovation.
• Executive framing: How to communicate AI governance readiness to boards, auditors, and regulators.

This session empowers CISOs to identify and close the “AI governance blind spot” before it becomes the next headline breach or regulatory failure.

Every vendor promises AI will transform cybersecurity, but the reality is more complex. Automation can scale detection and accelerate response, but it cannot replace the uniquely human ability to interpret context, challenge assumptions, and orient under uncertainty.

In this presentation, we will explore how AI is reshaping the threat landscape, why over-reliance leads to brittle defenses, and how CISOs can leverage AI as a force multiplier without outsourcing their judgment.

The result: security programs that are faster, smarter, and resilient, without the false promise of “fully autonomous security.”

As cyber threats escalate in frequency, severity, and financial impact, cyber insurance has emerged as a critical risk-transfer mechanism for organizations of all sizes. Yet many CISOs still struggle to understand how insurance intersects with cybersecurity strategy, governance, and incident response. This panel brings together leading experts in cyber insurance, legal risk, and security governance to decode the core concepts that CISOs must know. Topics will include what cyber insurance covers (and what it doesn’t), evolving underwriting requirements, incident response obligations, and the implications of claims disputes and litigation. Attendees will gain a practical roadmap for aligning cybersecurity programs with insurance expectations, optimizing coverage, and ensuring resilience when—not if—a cyber incident occurs.

See how Wiz secures everything you build and run in the cloud.

Please visit our sponsors in the Exhibit Hall and explore their resources. They're standing by to answer your questions.