AI Compliance: The New Business Imperative
Organizations are adopting AI at a breathtaking pace, often without adequate governance or oversight. As employees integrate generative AI tools into daily workflows and businesses embed AI into core services, a new and intricate web of risks is taking shape. In response, regulators and industry bodies are racing to establish rules and standards to ensure AI is developed and deployed responsibly.
For MSPs and MSSPs, this shift represents a significant opportunity. You are uniquely positioned to guide clients through the complexities of AI governance, helping them operationalize early controls before the full regulatory wave hits. By taking a proactive stance, you can move beyond a reactive security posture and establish your firm as a strategic advisor, turning AI risk management into a scalable, high-value service.
This blog explores the current state of AI governance, including landmark initiatives like the EU AI Act, the NIST AI Risk Management Framework, and other global standards. We’ll examine essential compliance obligations, highlight critical gaps in existing frameworks, and outline practical steps that MSPs must take now to guide and protect their clients in a rapidly changing regulatory environment.
The EU AI Act and Its Global Ripple Effects
The European Union’s AI Act stands as the world’s first comprehensive law governing AI. Its impact extends far beyond Europe, setting a global precedent for AI regulation. The Act establishes a risk-based framework, categorizing AI systems into four tiers including unacceptable, high, limited, and minimal, with stricter obligations for systems that pose a greater threat to safety and fundamental rights.
A key feature of the EU AI Act is its extraterritorial reach. Any U.S.-based company offering AI-powered services in the EU or processing data from EU residents must comply. With a staged rollout from 2025 to 2027, the clock is ticking for businesses to prepare. As major U.S. technology vendors adapt their products to meet these standards, a “soft compliance” expectation is emerging worldwide. Clients will increasingly expect their partners to align with these principles, making familiarity with the EU AI Act essential for MSPs.
The U.S. Landscape: Fragmented, but Moving Quickly
The United States previously relied on voluntary frameworks, but the environment has changed. States are now leading with enforceable laws, and the federal government is integrating AI requirements into procurement at a broad scale.
State-Level Patchwork Laws
- Colorado AI Act (SB24-205): Effective June 30, 2026. This law covers “high-risk” AI systems that impact areas like employment, lending, insurance, and healthcare. It requires annual impact assessments, public disclosures, and consumer opt-out rights. Fines can reach $20,000 per violation. There is a safe harbor for organizations that document alignment with NIST AI RMF or ISO/IEC 42001.
- Texas Responsible AI Governance Act (TRAIGA): Effective January 1, 2026. This law applies to AI involved in consequential decisions and mandates semi-annual risk impact assessments. Fines can reach $200,000. Documentation aligned with NIST standards provides a safe harbor.
- California and Others (Draft): California’s privacy regulator is developing rules for automated decision-making. Human-review opt-outs for credit and lending models may be required as soon as late 2025. States are adopting differing rules, so MSPs must prepare to address shifting requirements.
Federal Procurement: OMB Directives and Executive Orders
OMB directives (M-24-10 and M-24-18) now put AI compliance at the center of federal contracts. As of March 2025, all suppliers to U.S. government agencies need to provide:
- AI and data inventories/model cards
- Independent red-team and risk assessment reports
- 72-hour incident notifications
- Provenance, watermarking, and carbon emissions data for generative AI
- Key performance indicator dashboards for fairness, robustness, and reliability
These requirements are being picked up by commercial buyers and large enterprises, making them informal standards across the private sector.
Standards and Sector Frameworks
NIST AI Risk Management Framework (AI RMF)
The NIST AI RMF, which focuses on governance, risk mapping, measurement, and management, remains fundamental. Though still voluntary, it forms the basis for safe harbor provisions in federal and state regulations and is a backbone for many U.S. and international AI programs.
ISO/IEC 42001:2023—The AI Management System Standard
ISO/IEC 42001 is the first certifiable management system standard for AI. Adoption is increasing, especially when combined with ISO 27001, as this approach can reduce audit complexity and streamline enterprise sales. MSPs who align with ISO 42001 can deliver audit-ready, standardized governance to clients looking for advanced security and compliance.
Industry-Specific Controls: HITRUST, FFIEC, FDA, and More
- HITRUST AI Risk Management Assessment: Now a baseline for healthcare, financial services, and SaaS providers, with 51 mapped controls that align with NIST and ISO and are certifiable through defined scorecards.
- HITRUST AI Security Assessments: Includes 27 to 44 controls, depending on model type, bridging vendor and cloud responsibility models.
- Financial Services (FFIEC, OCC): Emphasize model inventories, validation, fairness audits, and ongoing monitoring.
- Healthcare and Life Sciences (FDA): Finalized protocols for monitoring AI-enabled medical devices and managing algorithmic bias.
Leading organizations in healthcare, finance, and public sector are adopting these standards, so MSPs offering industry-specific frameworks and compliance evidence will be positioned to lead.
The Governance Gap: Where MSPs Can Lead
While frameworks like the NIST AI RMF provide a solid foundation, significant gaps remain between high-level guidance and real-world implementation, creating a gray area where risk outpaces regulation.
What’s Missing in Current AI Governance
Despite growing regulatory activity, several challenges create complexity for MSPs and their clients:
- No Unified Federal Legislation: While state-level laws in Colorado and Texas mark progress, the absence of comprehensive federal AI law leads to a fragmented landscape, placing a heavy compliance burden on organizations.
- Limited Global Consistency: Variations between the EU AI Act, U.S. frameworks, and other country-specific regulations make it challenging for businesses operating across borders to maintain consistent compliance.
- Evolving AI Risks: The most pressing risks, such as data leakage from generative AI, supply chain vulnerabilities from third-party tools, and algorithmic bias, often fall outside formal compliance scopes.
- Operational Hurdles: Organizations struggle to meet increasing demands for ongoing monitoring, continuous KPI reporting, and audit-ready evidence. This challenge intensifies when managing third-party and supply chain oversight.
Why It Matters for MSPs
Organizations cannot afford to wait for laws to catch up. This is where MSPs must step in. By taking the initiative, you can fill the governance gap with proactive risk assessments, robust policies, and continuous monitoring. You have the opportunity to define what “good” looks like and help clients navigate uncertainty with confidence.
Action Steps for MSPs
To stay ahead in this new era, leaders should consider five key actions:
- Centralize Evidence Across Jurisdictions:
Build an evidence library containing AI inventories, model and data cards, risk and impact assessments, and red-team reports mapped to NIST, ISO 42001, Colorado and Texas statutes, and HITRUST controls. Centralization streamlines responses to audits, RFPs, and state-specific requirements.
- Develop Modular Policy Templates:
Use flexible templates that can be quickly adapted for notification timelines, assessment schedules, and rights statements in each state or sector.
- Monitor Supplier Compliance:
Regularly track upstream and third-party vendors for their compliance deliverables. Look for red-team results, provenance data, and model documentation to ensure you meet both federal and sector requirements.
- Offer Industry-Specific Starter Kits:
Create packages tailored to specific markets:- Healthcare: Coverage for HITRUST AI, ISO 42001, FDA rules, and HIPAA alignment.
- Finance: Frameworks mapped to FFIEC/OCC, and EU DORA for global operations.
- Public Sector: OMB requirements and FedRAMP overlays, plus records management tools.
- Automate KPI Monitoring:
Deploy dashboards that provide live metrics on bias, robustness, reliability, and energy usage. Align these with ISO 42001, federal, and industry guidelines for performance and reporting.
Looking Ahead: What 2026 Holds for AI Governance
2026 is set to become a pivotal year for AI governance, moving risk management from voluntary frameworks to statutory requirements. Here’s what service providers can expect:
- State-Level Enforcement: The Colorado AI Act and Texas Responsible AI Governance Act will come into effect, mandating that organizations conduct periodic AI impact assessments, maintain transparent documentation, and provide consumer disclosures.
- Evolving Federal Standards: Federal procurement standards will require MSPs targeting public sector contracts to meet OMB deadlines by providing detailed model documentation, incident reporting, and ongoing risk metrics. These requirements will likely influence standards across the broader commercial landscape.
- Acceleration of Global Frameworks: Adoption of frameworks like ISO 42001 will continue to grow as businesses seek certifiable, efficient ways to future-proof their AI practices against emerging regulations.
- Federal Legislation on the Horizon: Lawmakers are advancing bills aimed at unifying national standards for AI accountability and safety, which could create a more consistent regulatory environment.
- SEC AI Risk Disclosure Requirements: Public companies will likely face new expectations for transparency in reporting AI-related risks. MSPs serving these clients should prepare for enhanced documentation and risk oversight processes.
- Updated Sector-Specific Frameworks: The anticipated introduction of a dedicated AI layer in HITRUST CSF v12 and other supply chain certifications will require providers to align their controls and audit artifacts with new expectations.
The Path Forward for MSPs
As 2026 approaches, MSPs face increasing complexity and heightened expectations. Anticipating these changes will give your organization a distinct advantage. By investing early in scalable, standardized compliance practices, you can ensure operational readiness, protect clients, and capture growth opportunities as AI governance matures. The next year will reward proactive preparation and a continuous commitment to delivering value in a shifting landscape.