NIST AI RMF

The STRIDE framework is a structured approach to threat modeling that helps organizations identify and prioritize the most common and impactful cybersecurity threats. Originally developed by Microsoft, STRIDE remains widely used today to assess risks across modern systems, including AI-driven environments.

For organizations pursuing ISO/IEC 42001 compliance, STRIDE framework threat modeling plays an important role in AI risk identification, mitigation planning, and governance alignment. It supports proactive security decision-making while also helping organizations meet overlapping requirements found in other cybersecurity and risk management frameworks.

Is your organization prepared to apply STRIDE framework threat modeling effectively?
Schedule a consultation to assess your readiness and strengthen your AI risk management program.

Organizations implementing AI technologies must stay ahead of rapidly emerging governance and compliance requirements. Two of the most important frameworks are the NIST AI Risk Management Framework (NIST AI RMF) in the United States and the ISO/IEC 42001:2023 AI Management System standard used internationally. While each framework- serves a different regulatory environment, starting with the NIST AI Risk Management Framework provides a strong foundation that makes aligning with—and ultimately certifying against, ISO 42001 significantly easier.

Is your organization preparing for NIST or ISO AI compliance? Schedule a consultation to get expert guidance.

As artificial intelligence (AI) becomes increasingly embedded in government operations, cities across the U.S. face a critical challenge: ensuring these systems remain fair, safe, transparent, and trustworthy. The City of San José, California, one of the country’s leading technology hubs, has emerged as an early model for responsible public-sector AI. San José is one of the first municipalities to formally evaluate its AI programs using the NIST AI Risk Management Framework (AI RMF). Through a collaboration with the National Institute of Standards and Technology, the city applied the AI RMF to assess its AI governance maturity, identify risks, and strengthen safeguards across all AI-related activities.

This NIST AI RMF case study reveals not only what San José is doing well, but also where public-sector organizations must continue improving to deploy trustworthy, risk-aware AI systems.

Generative Artificial Intelligence offers organizations across industries significant productivity and efficiency gains, but it also introduces new risks. The NIST AI RMF (AI Risk Management Framework) provides a structured approach to identify, assess, and mitigate these risks while maximizing the benefits of generative AI.
Is your organization prepared for secure and compliant AI adoption? Schedule a consultation today to ensure your AI initiatives are safe, responsible, and aligned with industry standards.

Organizations embracing artificial intelligence (AI) to streamline operations must also prepare for the unique risks it. The NIST AI Risk Management Framework (AI RMF) provides a structured, trustworthy approach to identifying, evaluating, and mitigating these risks across the AI lifecycle. Implementing this framework helps internal teams establish clear governance and gives external stakeholders confidence in your organization’s responsible AI practices.

Is your organization ready to align with the NIST AI Risk Management Framework? Schedule a consultation to get started.

Artificial intelligence (AI) is transforming every industry, from healthcare and finance to manufacturing and national security. As adoption accelerates, lawmakers are racing to keep pace. New AI legislation in 2025 aims to address growing concerns around privacy, bias, transparency, and accountability.

Organizations that leverage AI must now prepare for stricter AI compliance and regulatory requirements in the U.S. and abroad. Is your business ready for the next wave of AI legislation and enforcement?
Schedule a call to assess your readiness and stay ahead of regulatory changes.

Artificial Intelligence (AI) is transforming industries worldwide, from healthcare and finance to manufacturing and national security. However, with these opportunities come significant challenges such as bias, data privacy concerns, regulatory noncompliance, and potential system failures. The NIST AI RMF Playbook provides organizations with a structured approach to managing these AI risks responsibly and promoting trustworthy innovation.

To address these risks, the National Institute of Standards and Technology (NIST) introduced the NIST AI RMF Playbook, a strategic framework that helps organizations identify, assess, and manage AI-related risks responsibly. This guide promotes ethical, transparent, and secure AI adoption across sectors.

In this blog, we’ll explore what the NIST AI RMF Playbook is, how it’s structured, and why it’s becoming the go-to resource for building trustworthy and compliant AI systems.

Artificial Intelligence (AI) is transforming how businesses operate—but with innovation comes risk. From biased decision-making to security vulnerabilities, AI systems introduce a new frontier of ethical, operational, and regulatory challenges. That’s where the NIST AI Risk Management Framework (AI RMF) comes in.

Artificial Intelligence (AI) is revolutionizing industries worldwide, offering remarkable advancements and efficiencies. However, with its widespread adoption, concerns about AI bias have surfaced. AI systems, which are increasingly integrated into key decision-making processes such as hiring, healthcare, and financial assessments, can inadvertently perpetuate biases, leading to unfair or discriminatory outcomes.