AI Governance & Compliance

    Governance built into the architecture — not bolted on after deployment

    Brandywine Consulting Partners helps healthcare, life sciences, and regulated organizations build AI governance into the foundation of their systems — before production AI scales risk. We evaluate your architecture, databases, security posture, and compliance readiness; audit models, data pipelines, and vendor contracts; and implement the controls, evidence trails, and operating procedures needed to satisfy strict governance standards including NIST AI RMF, ISO/IEC 42001, the EU AI Act, HIPAA, and ONC HTI-1. As governance contracting experts, we embed accountability into vendor agreements, data-use terms, and system design so your organization is built for the regulations of tomorrow, not just today's.

    What We Do

    Service overview and the core capabilities BCP brings to every ai governance & compliance engagement.

    AI/ML architecture and model inventory evaluation
    Data governance assessment — lineage, quality, retention, PHI/PII handling
    Security and compliance audits mapped to NIST AI RMF, ISO/IEC 42001, EU AI Act, HIPAA, and SOC 2
    Model auditability, explainability, and drift-monitoring control design
    AI vendor and governance contracting — data-use terms, accountability clauses, audit rights
    Responsible AI policy development and board-ready governance reporting
    Shadow AI discovery and sanctioned-use frameworks
    Ongoing governance operations support and regulatory change monitoring

    Key Benefits

    Audit-Ready Evidence

    Controls, documentation, and decision trails that satisfy regulators, auditors, and boards — produced as a byproduct of operations, not a scramble before review.

    Reduced AI Risk Surface

    Architecture-level controls catch data pollution, ungoverned model access, and vendor gaps before they become incidents or penalties.

    Future-Proof Compliance

    Governance contracting and adaptable control frameworks keep you ahead of evolving AI regulation instead of reacting to it.

    Layered AI governance controls verifying data, models, and compliance checkpoints
    Governance by architecture

    Controls, evidence, and accountability — built in before AI scales risk.

    Why BCP for AI Governance & Compliance

    Full-lifecycle governance: architecture and database evaluation, security and compliance audit, control implementation, and ongoing operations support
    One control set mapped across NIST AI RMF, ISO/IEC 42001, EU AI Act, HIPAA, ONC HTI-1, and SOC 2 — no parallel compliance programs
    Governance contracting expertise: AI clause libraries, vendor agreement review, audit rights, and accountability allocation built into contracts
    Healthcare-depth: PHI/PII pipeline governance, BAA boundary review, and zero-retention patterns for sensitive data
    Shadow AI discovery and sanctioned-use frameworks that replace prohibition with fast, compliant intake
    Board-ready evidence: model cards, eval packs, audit trails, and quarterly governance reporting produced as a byproduct of operations

    Who We Serve

    The audiences this service is built for, with the specifics that matter to each.

    Health Systems & Providers

    Governance for clinical AI, ambient documentation, and decision support before enterprise rollout.

    • Clinical AI model inventory and risk tiering
    • PHI handling review for training and inference pipelines
    • FDA SaMD and ONC HTI-1 decision-support transparency readiness

    Payers & Health Plans

    Auditable AI for utilization management, risk adjustment, and member-facing automation.

    • Algorithm accountability for UM and prior-auth automation
    • Model audit trails for state and CMS scrutiny
    • Vendor AI contract review and governance clauses

    Life Sciences & Discovery Science

    Governed AI for research, pharmacovigilance, and submission-adjacent workflows.

    • Data lineage and provenance for model training sets
    • GxP-aware AI validation documentation
    • AI use policies for research and clinical teams

    Digital Health & AI Vendors

    Governance as a market differentiator — evidence packs that win enterprise procurement.

    • ISO/IEC 42001 and NIST AI RMF gap analysis
    • Model cards, eval reports, and bias documentation
    • Customer-facing trust and compliance artifacts

    Typical Triggers

    If any of these sound familiar, you're in the window where this service delivers the most value.

    AI scaling past pilot

    Models moving to production without inventory, ownership, or monitoring in place.

    Regulatory or audit pressure

    Board, auditor, regulator, or enterprise customer asking for AI governance evidence you cannot produce.

    Shadow AI discovery

    Teams using unsanctioned AI tools with company or patient data and no oversight.

    Vendor AI proliferation

    Dozens of vendors embedding AI into products with no consistent contracting or review standard.

    Incident or near-miss

    A model output, data leak, or bias event exposed the absence of controls.

    New regulation in scope

    EU AI Act, state AI laws, or ONC HTI-1 transparency rules now apply to your products or operations.

    Service Deliverables

    Three engagement models, same engineering rigor — choose the operating boundary that fits your team.

    BCP Hosted

    Fully managed by BCP

    • BCP-operated AI governance dashboard: model inventory, risk tiers, drift and incident status
    • Continuous regulatory change monitoring with quarterly impact briefings
    • Managed model audit cadence with evidence collection and board-ready reporting

    Client Hosted

    Delivered into client tenant

    • Governance control framework deployed in your tenant: policies, model registry, approval workflows
    • Data governance layer: lineage, quality checks, retention and PHI/PII handling controls
    • Complete documentation set: model cards, data sheets, eval results, risk assessments

    BCP-Managed, Client Hosted

    BCP operates inside your tenant

    • BCP runs the governance operating model inside your environment: reviews, approvals, audit response
    • Vendor and contract governance: AI clause library, review workflow, renewal audits
    • On-call governance expertise for new use-case intake and risk review

    Free self-assessment · 3 minutes

    How ready is your AI governance?

    Answer 12 questions across architecture, data, security, and compliance. Get an instant readiness score and specific next steps.

    Service Timeline

    BCP's framework-driven methodology: Discover → Design → Build → Validate → Launch → Operate. Durations are typical and right-sized to scope.

    012–3 weeks

    Discover

    • AI/ML inventory across models, vendors, and shadow usage
    • Architecture, database, and data-flow evaluation
    • Regulatory scope mapping (HIPAA, EU AI Act, state laws, HTI-1)
    023–4 weeks

    Assess

    • Gap analysis against NIST AI RMF and ISO/IEC 42001
    • Security and compliance audit of pipelines, access, and endpoints
    • Risk tiering and prioritized remediation roadmap
    033–4 weeks

    Design

    • Governance operating model: roles, committees, intake and approval workflows
    • Control framework: model auditability, drift monitoring, incident response
    • Policy and contract clause library
    044–8 weeks

    Implement

    • Deploy model registry, monitoring, and evidence collection
    • Data governance controls: lineage, quality, retention, PHI/PII handling
    • Vendor contract remediation and governance clauses
    052–3 weeks

    Validate

    • Control testing and mock audit
    • Model documentation and eval pack completion
    • Leadership and board reporting dry run
    06Ongoing

    Operate

    • Continuous monitoring, drift and incident review
    • Quarterly governance reviews and regulatory watch
    • Annual framework re-assessment and refresh

    Service Stack

    The BCP-preferred technology stack for this service, plus the common client stacks we support and operate.

    BCP Technology Stack

    Frameworks

    NIST AI RMFISO/IEC 42001EU AI ActONC HTI-1

    Governance platforms

    Azure PurviewCollibraMicrosoft Responsible AI dashboardUnity Catalog

    Model audit & monitoring

    MLflowEvidentlyAzure ML monitoringFairlearn

    Security & evidence

    Microsoft Purview ComplianceAzure PolicyDefender for CloudSOC 2 evidence automation

    Common Client Stacks We Support

    Azure-native

    Azure MLAzure OpenAIPurviewAzure Policy

    Databricks-first

    Unity CatalogMLflowLakehouse Monitoring

    AWS

    SageMaker Model GovernanceBedrock GuardrailsAudit Manager

    Hybrid / multi-vendor

    CollibraServiceNow GRCCustom model registries

    Representative Use Cases

    • AI readiness assessments for health systems before enterprise AI deployment
    • ISO/IEC 42001 and NIST AI RMF gap analysis and remediation roadmaps
    • Governance contracting for AI vendor and model-provider agreements
    • PHI/PII data governance for model training and inference pipelines
    • Model audit and explainability programs for clinical decision support AI
    • Shadow AI discovery and sanctioned-use policy rollout for regulated enterprises

    Compliance

    The standards we engineer to — and how BCP ensures the controls are real, evidenced, and audit-ready.

    NIST AI RMF

    Full Govern/Map/Measure/Manage alignment with documented actions per function and risk tier.

    ISO/IEC 42001

    AI management system design, gap analysis, and certification-readiness evidence.

    EU AI Act

    Risk classification, transparency obligations, and technical documentation for in-scope systems.

    HIPAA

    PHI/PII controls for training and inference, BAA boundary review, minimum-necessary enforcement.

    ONC HTI-1

    Decision-support transparency and source-attribute documentation for clinical AI.

    SOC 2

    AI controls mapped into existing trust-services criteria and audit evidence.

    Service Proof Points

    Representative engagements with the technical challenge, BCP solution, measured outcomes, and the trust assets we deliver alongside the work. Client identifiers anonymized; details available under NDA.

    Regional health system, 12 hospitals

    Enterprise AI governance program build

    Challenge

    40+ AI tools in use across clinical and operational teams with no inventory, no approval process, and board-level concern after a vendor AI incident.

    BCP Solution

    • Full AI inventory and shadow-AI discovery across clinical and IT estates
    • Governance operating model with intake, risk tiering, and approval workflows
    • Vendor contract remediation with AI accountability and audit-rights clauses

    Measured Outcomes

    47
    AI tools inventoried & risk-tiered
    100%
    Unsanctioned tools remediated
    6 wks → 10 days
    Time to approve new AI use case

    Stack

    NIST AI RMFAzure PurviewServiceNow GRCMicrosoft Responsible AI

    Trust Assets

    • Board governance report
    • Mock audit results
    • AI policy library
    Digital health AI company, Series C

    ISO/IEC 42001 readiness for an AI vendor

    Challenge

    Enterprise customers demanding AI governance evidence in procurement; no formal management system or model documentation.

    BCP Solution

    • ISO/IEC 42001 gap analysis and AI management system design
    • Model cards, eval packs, and bias documentation for the full product line
    • Customer-facing trust center content and audit-response playbook

    Measured Outcomes

    9/9
    Procurement security reviews passed
    -31%
    Sales cycle for enterprise deals
    Audit scheduled
    Certification readiness

    Stack

    ISO/IEC 42001MLflowEvidentlyFairlearn

    Trust Assets

    • Gap analysis report
    • Model card library
    • Trust center artifacts
    Read the full case study: Building an Audit-Ready AI Governance Program

    Frequently Asked Questions

    01

    What does an AI governance engagement with BCP include?

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    02

    Which AI governance frameworks and regulations does BCP work with?

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    03

    How does BCP help with AI vendor and governance contracting?

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    04

    We already have AI models in production. Is it too late to add governance?

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    05

    How do you handle PHI and sensitive data in AI pipelines?

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    06

    What is shadow AI and how do you address it?

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    07

    How long does it take to become audit-ready?

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    Request a AI Governance & Compliance Proposal

    Share the specifics so we can scope, price, and stand up the right team. Most proposals back within 3–5 business days.

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