AI Governance Framework Implementation
Data & AI
Motivation
AI governance is a comprehensive framework that encompasses policies, regulations, and practices designed to ensure the ethical and responsible use of artificial intelligence within an organization. It establishes a set of ethical guidelines and standards that govern the development and deployment of AI systems, ensuring that AI technologies are used in a manner that aligns with societal values and ethical principles, preventing misuse and promoting fairness. AI governance helps organizations stay compliant with regulations, avoiding legal repercussions and ensuring that their AI practices meet the necessary legal standards. It also promotes transparency in AI decision-making processes by establishing clear accountability measures. This means that organizations can provide explanations for AI-driven decisions, fostering trust among customers and stakeholders. Adopting AI governance demonstrates a commitment to ethical practices and responsible AI use, which can enhance an organization's reputation. Customers are more likely to trust and engage with companies that prioritize ethical AI practices, leading to stronger customer relationships and loyalty.
What we bring
With over 20 years of experience in software and data architectures for many of the world’s largest enterprises, PRODYNA is well-equipped to help you design and establish a comprehensive AI governance framework. Our expertise in the area of AI Governance includes:
- AI Governance Standards: Introduction of processes and tooling that helps you accomplish the goal quickly.
- Risk Management: Strategies to ensure safe and reliable AI applications.
- Model Management: Methods to identify the best model according to your non-functional requirements.
- Cross functional know-how: Years of experience working with the Azure cloud to implement policies and monitoring for applications and the data plane.
What you need
To successfully implement an AI governance framework, your organization will need to provide:
- Regulatory Requirements: Details of relevant compliance and regulatory standards.
- Platform Team: Access to your platform team.
- Stakeholder Engagement: Involvement of key stakeholders across the organization.
- Management Attention: Management needs to be aware that AI Governance is a vital part of AI applications.
What you get
Our AI governance framework implementation has three main phases. We will tailor the implementation to your organization's specific needs to minimize time and cost. PRODYNA will guide you and your employees through the following phases:
Discovery & Planning
(generally 2-10 days)
Assessment of Current State: Evaluate existing AI and Azure platform governance and compliance practices.
Define Goals and Objectives: Establish clear goals for the AI governance framework aligned with business objectives.
Gap Analysis: Identify the gap between ideal target and current situation.
Develop Roadmap: Prioritize steps towards the target and create a detailed implementation plan.
Stakeholder Analysis: Identify key stakeholders and define their roles and responsibilities.
Framework Development
(generally 2-4 weeks)
Policy and Standards Development: Create AI governance policies, standards, and procedures.
Model Management: Implement methods to evaluate models according to compliance, scalability and cost requirements.
Audit Process: Establish a governance board to plan and track changes to the governance process.
Accountability Structures: Define governance roles and escalation pathways.
Responsible AI: Implement measures to evaluate applications according to the six principles:
- Fairness
- Reliability & Safety
- Privacy & Security
- Inclusiveness
- Transparency
- Accountability
Implementation & Monitoring
(generally 2-4 weeks)
Framework Implementation: Use Azure policies to enforce compliance.
Monitoring and Reporting: Establish tools and methods to detect harmful AI application behavior.
Training and Communication: Conduct training sessions and communicate the methods and importance of AI governance.
Continuous Improvement: Regularly review and update the AI governance framework to address evolving needs and challenges.
Quick facts
- Duration: 8-18 weeks depending on the scope
- Produces a tailored AI Governance Framework with implemented Azure Policies and monitoring
Benefits
- Compliance: Align with regulations like the EUAI Act for secure, responsible AI use.
- Cost Control: Standardize and monitor AI-related costs.
- Efficiency: Automate tasks using Azure policies.
- Model Monitoring: Track model performance, data quality, and user behavior.
- Scalability: Design AI applications with the right capacity from the start.
- Transparency: Promote responsible AI practices and clear accountability.
- Risk Mitigation: Identify and address potential risks early.
Contact us
for more information.
David Wainwright
