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AI Vendor Risk Management Service
AI Act Compliance With Responsible AI Book a AI Risk Audit Why FormitiThe 4 Pillars of Industrial AI Oversight
Our framework is designed to meet the rigorous demands of the West Midlands supply chain, ensuring compliance without stifling innovation.
Regulatory Alignment (UK & EU)
Global Compliance Readiness” We ensure your AI systems align with the latest legislative frameworks. Whether you are operating under the UK’s pro-innovation framework or exporting goods subject to the EU AI Act, our governance models map to high-risk categorization.
Key Standard: ISO 42001 (AI Management)
Data Privacy & GDPR
Ironclad Data Protection” Your factory data often contains personal identifiers (worker metrics) and sensitive IP. We implement strict Data Minimization and Anonymization protocols, ensuring that AI training datasets never violate UK GDPR or compromise individual worker privacy.
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Key Standard: Privacy-Enhancing Technologies (PETs)
Ethical AI & Bias Mitigation
Fairness in the Factory” Algorithmic bias can lead to unfair operational decisions or skewed quality control. We deploy ethical frameworks to test your models for bias against protected characteristics, ensuring your AI is neutral, fair, and socially responsible.
Key Standard: The Nolan Principles (adapted for AI)
Accountability & Audit Trails
The ‘Why’ Behind the Decision” Black-box AI is a liability. We mandate Explainable AI (XAI), creating immutable digital audit trails for every automated decision. If an inspector asks why a decision was made, you will always have the data to prove it was ethical and compliant.
Key Standard: Algorithmic Transparency Recording Standard
Your Path to AI Readiness
A phased approach to integrating governance without disrupting production.
Step 1: The "Digital Audit"
Identify & Assess Before we build, we map. We conduct a full audit of your current data landscape, identifying high-risk AI use cases (e.g., predictive maintenance algorithms) and assessing current GDPR compliance gaps.
Deliverable: Risk & Readiness Report.
Step 2: The Framework Build
Design & Standardize We tailor a governance framework specific to your sector (Automotive, Aerospace, Logistics). This creates the “Standard Operating Procedures” (SOPs) for how your teams interact with AI, ensuring alignment with the EU AI Act.
Deliverable: Custom AI Governance Handbook.
Step 3: Workforce Integration
Train & Upskill Governance fails without buy-in. We run workshops for your shop-floor engineers and management, demystifying AI ethics and training them on new data privacy protocols.
Deliverable: Staff Certification & Training Modules.
Step 4: Continuous Assurance
Monitor & Optimize AI models drift over time. We establish a “Continuous Monitoring” loop, conducting quarterly ethical audits and bias checks to ensure your systems remain compliant as regulations evolve.
Deliverable: Quarterly Compliance Certificates.
Scalable AI Governance: Built for Global Growth
Industry-specific frameworks designed to turn regulatory compliance into a market advantage.
AI Compliance & Risk: Your Questions Answered
Everything you need to know about navigating the evolving AI regulatory landscape.
Q1.1. How does the EU AI Act affect my business if we aren't based in Europe?
Much like GDPR, the EU AI Act has extraterritorial reach. If your AI system’s output is used within the EU—or if you provide AI services to EU-based users—you must comply. Non-compliance carries significant global fines, making readiness a prerequisite for international trade.
Q2. What is the difference between "High-Risk" and "Limited-Risk" AI?
The Act uses a risk-based approach. High-Risk systems (e.g., HR recruitment tools, critical infrastructure, or credit scoring) require strict auditing and logging. Limited-Risk systems (e.g., chatbots) primarily require transparency—users must know they are interacting with AI. We help you classify your entire inventory to avoid over-engineering your compliance.
Q3.Why is "Vendor Risk Management" so critical for AI?
Most businesses don’t build their own AI; they lease it (e.g., OpenAI, Microsoft, Midjourney). However, you are legally responsible for how that AI handles your customer data. If a vendor’s model has a “data leak” or inherent bias, the regulatory burden often falls on the deployer (you). We audit the vendor so you don’t inherit their risk.
Q4.Can we still innovate while maintaining strict AI Oversight?
Absolutely. In fact, good governance accelerates innovation. By establishing “Guardrails” early, your development teams can experiment within a safe framework, preventing costly “scrap and rework” cycles that happen when a project is found to be non-compliant late in the game.
Q5. What is an Algorithmic Impact Assessment (AIA)?
An AIA is a deep-dive evaluation of how your AI makes decisions. It looks for bias, transparency, and data quality. Formiti’s AIA process ensures your algorithms are “explainable”—meaning you can prove to a regulator exactly how and why an AI reached a specific conclusion.
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