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AI Audits and Assessments

We conduct comprehensive AI and privacy assessments to identify compliance gaps across your data practices, systems, workflows, and processes. We evaluate how personal data and AI models are collected, used, stored, and shared, ensuring alignment with regulatory requirements and industry best practices. Our assessments also highlight areas for improvement and provide recommendations to strengthen your stance.

What are AI Assessments and Audits?

 

AI assessments typically occur early or continuously. They evaluate how an AI system is designed, what data it uses, its intended purpose, associated risks, potential impacts on individuals, and alignment with internal policies and regulatory requirements. These assessments help identify issues such as bias, data quality concerns, privacy implications, and operational risks before the system is fully deployed.

 

AI audits provide a more evidence-based review. They verify that the AI system behaves as expected, complies with applicable laws and standards, maintains accurate documentation, protects personal data, and includes proper human oversight and governance controls. Audits also examine system performance, fairness, security, and audits through logs and monitoring tools.

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Employing AI within businesses has an ever-growing list of benefits. Businesses now use AI for customer service and chatbots, for AdTech processes, to streamline and automate business processes, and more. Utilizing AI in a competitive market is the way forward.

But there are regulations to comply with and guidelines to follow while using AI as they also come with a number of inherent risks.

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So, as businesses, how do we get the most value from our AI models while being compliant and mitigating risks?

 

Meru Data can help you answer these important questions.

Regulatory Landscape for AI

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Agentic AI is rapidly evolving and increasingly focused on transparency, accountability, and risk management. The EU AI Act is currently the most comprehensive framework, classifying AI systems by risk and imposing strict requirements such as documentation, human oversight, and conformity assessments on high-risk or general-purpose AI models.

 

In the U.S., the biggest shift comes from California’s new CCPA regulations on Automated Decision-Making Technology (ADMT). These rules require businesses to give consumers advance notice when AI is used to make impactful decisions, provide an opt-out option, and offer detailed explanations of how those decisions are generated. They also mandate periodic risk assessments and annual cybersecurity audits for companies using AI at scale. With these new obligations, California has effectively made AI assessments and audits a core part of compliance, raising the bar for accountability and responsible AI practices across the industry.

Why is it necessary?

​AI audits and assessments are essential because they ensure that AI systems are safe, fair, transparent, and compliant with AI regulations. As AI becomes more autonomous and embedded in business processes, organizations must verify that these systems behave as intended and do not introduce hidden risks, biases, or privacy violations. Audits help uncover issues in data quality, model performance, and decision logic, while assessments identify regulatory obligations, governance gaps, and risks to individuals’ rights.

How Can Meru Help?

Our AI Audit services provide a comprehensive evaluation of how artificial intelligence is designed, deployed, and governed within your organization. We assess AI systems for compliance with emerging regulations, alignment with ethical standards, and adherence to principles such as fairness, transparency, accountability, and privacy. We help organizations reduce regulatory and operational risk and build trust in your technology.

 

 

1. AI Bias and Large Language Models (LLM) Audits.

2. Evaluate compliance with AI regulations and industry standard.

3. Reduce operational risk from AI technology.

Benefits

  • Regulatory Compliance: Ensure alignment with laws and standards such as the EU AI Act, GDPR, CCPA, and other emerging AI regulations.

  • Risk Mitigation: Identify and address bias, fairness issues, security vulnerabilities, and operational risks before they impact users or the business.

  • Transparency & Accountability: Provide clear documentation and traceability of AI decisions, building trust with regulators, customers, and stakeholders.

  • Improved Model Performance: Detect errors, data quality issues, or model drift, leading to more reliable and accurate AI outputs.

  • Operational Efficiency: Streamline governance processes, reduce manual oversight, and allow teams to focus on strategic priorities.

  • Reputation Protection: Demonstrate responsible AI use, reinforcing customer confidence, and protecting the organization from legal or ethical challenges.

Our Core Beliefs

  • Data is an asset for organizations.

  • Companies should be both data-wise and privacy-conscious: It is indeed possible to both use data to personalize experiences for customers and ensure privacy at the same time.

  • Privacy compliance is complex. But it can be simplified and managed with the right processes and technology.

  • Sustainable privacy programs require robust Information Governance. Data needs to be governed and managed from creation to deletion.

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