Vendor-Provided Resources

When it comes to assessing AI risk, third party risk management teams are challenged on two key fronts: the proliferation of AI that has outpaced the ability of traditional risk frameworks to keep up, and existing AI risk assessments that are fragmented and unique to specific industries, geographies, or regulatory bodies.

Black Kite's Global Adaptive AI Assessment Framework (BK-GA³™) is designed to address these challenges by providing a unified and truly global open standard for assessing AI risk. This effort reflects a commitment that has been deeply ingrained in our culture since the very beginning, a value instilled by Black Kite’s Co-founder, Candan Bolukbas, and expressed through the resources and research we regularly release to empower the community and strengthen the security of the entire ecosystem.

Ready to turn your cybersecurity investments into real outcomes? Discover the new HITRUST ROI Calculator—a strategic tool that visualizes how certification can boost revenue, streamline operations, lower cyber-insurance costs, and reduce risk. Backed by real-world data and a remarkable 464% ROI benchmark, this is the clarity your business case needs. Read the full blog to see what your organization could unlock.

In February 2024, a ransomware attack on a critical player in the US healthcare infrastructure sent shockwaves through the US and globally. Pharmacies were unable to process prescriptions using patients' insurance, leading to delays in medication dispensing and highlighting the fragility of the healthcare supply chain. Hospitals and medical offices faced severe operational disruptions, struggling to provide patient care, submit insurance claims, and receive payments. The American Hospital Association called it "the most significant and consequential incident of its kind against the US health care system in history."

Third-party attacks have emerged as one of the most critical threats in the modern cyber landscape. Adversaries increasingly exploit vulnerabilities within external vendors, suppliers, contractors, and service providers to gain indirect access to target organizations, often with severe consequences. These breaches can lead to significant data loss, operational disruption, regulatory penalties, and reputational damage. As a result, third-party risk management (TPRM) is no longer just an IT concern, it’s a board-level imperative essential to protecting sensitive data and maintaining customer trust.

For leading enterprises, Third-Party Risk Management is mission-critical. Yet many programs struggle with scalability and efficiency, relying on manual processes and reactive approaches to Cyber Threat Intelligence. The typical workflow – where incidents are escalated after discovery – creates delays, consumes resources, and leaves organizations blind to emerging risks.

Bitsight advances TPRM maturity with an Intelligence-Driven Prioritization Funnel. This approach integrates real-world CTI into the TPRM lifecycle, exposing risks such as leaked credentials, ransomware targeting, vulnerability exposure, and dark-web chatter. By embedding intelligence at scale, organizations shift from reactive, manual investigation to proactive, data-driven risk management – empowering teams to focus resources where they matter most.

As artificial intelligence (AI) adoption surges across industries, so too does the rising tide of regulatory attention. From the EU AI Act’s structured, risk-based framework to Japan’s more fluid, innovation-friendly guidelines, global regulatory currents are moving in different directions. China, Brazil, and the United States are also charting distinct courses, each reshaping the landscape of AI compliance in its own way.

For third-party risk management (TPRM) professionals, these shifting conditions present a growing challenge: how to manage AI-related risks while staying upright in a sea of contrasting values, oversight models, and definitions of responsible AI. To maintain balance, many organizations are turning to TPRM platforms that can respond with agility.

As TPRM professionals face growing complexity, evolving regulations, and tightening resources, AI can be a powerful co-pilot when deployed with intention. Much like the methodical work of crafting a Pinewood Derby car that performs, AI needs structure, guidance, and testing to truly enhance outcomes.

That’s why Aravo’s Intelligence-First platform stands apart. Guided by a deliberate roadmap and grounded in research from Gartner, McKinsey, Deloitte, and others, Aravo avoids the rushed, bolt-on approach to AI adoption. Instead, it focuses on a smart, phased implementation that strengthens resilience, increases efficiency, and builds long-term trust.

It’s the difference between simply racing and racing to win.

Artificial intelligence (AI) is transforming how organizations manage risk, shaping everything from daily workflows to long-term strategy. For Third-Party Risk Management (TPRM) teams, the challenge is cutting through the hype and applying AI in ways that truly strengthen resilience, decision-making, and governance. Our guide demystifies AI’s role in TPRM, offering a practical framework for adoption rooted in responsible AI principles.

This guide will equip you with the knowledge to:

• Understand why AI in TPRM matters more than ever: learn how today’s interconnected risk ecosystem makes AI essential for managing complexity, anticipating disruption, and building enterprise resilience.

• Recognize warning signs of GenAI fatigue and governance challenges: explore why many AI projects stall or fail, from unscalable pilots to gaps in oversight, and how to avoid common missteps.

• Navigate the four waves of AI in TPRM: see how AI adoption evolves from basic automation to trust-based ecosystems, with each wave bringing both new opportunities and governance demands.

• Apply Responsible AI principles as a new mandate: understand the core pillars of responsibility and why they are essential for building confidence in AI-driven risk functions.

• Prioritize the human factor in AI success: discover why people truly define AI impact and how talent, efficiency, and change readiness drive effective adoption.

Download the guide to explore how to cut through the hype, adopt AI responsibly, and build stronger, more resilient TPRM programs!

In the world of Third-Party Risk Management (TPRM), Artificial Intelligence (AI) is often seen as a powerful, transformative current. It carries us forward with promises of lightning-fast due diligence, predictive insights, and automated assessments.

But like any seemingly ‘perfect’ wave, what’s happening beneath the surface matters. Without a clear understanding of the currents and the ocean floor, we risk getting caught in an undertow. In TPRM, the consequences of irresponsibly adopted AI can be far more serious than a bad wipeout.

Let’s dive beneath the surface and examine the hidden forces behind the AI “waves” in TPRM, including the currents, the rogue swells, and the deceptive calm we need to watch for.

Offboarding third parties is a critical, yet often overlooked, stage in the third-party relationship lifecycle. If not handled carefully, it can carry significant operational, legal, financial, and reputational risks. To support a smooth and secure transition, there are several essential steps every organization should take.

A vendor’s financial stability directly impacts your operations. Financial health is a critical indicator of the vendor’s ability to deliver consistent quality and support when you need it most. That makes vendor financial health an important element to review during your vendor due diligence process. 

This infographic explores the impact of poor vendor financial health — and what your organization can do about it. 

Download the infographic to learn:

• Why vendor financial health matters

• What to do when a vendor has poor financial stability

"For years, security frameworks have served as essential tools for aligning cybersecurity practices, but they’ve also come with limitations. Designed primarily for compliance, many frameworks are rigid by nature, sometimes to the extent of being a checklist, making them ill-suited for today’s dynamic risk environments. But the threat landscape has evolved, and so too must our approach. In an environment where attacks unfold in hours and supply chain vulnerabilities cascade across ecosystems, organizations need more than compliance—they need real-time intelligence."