AI Governance: Strategy, Policy & Responsible Deployment

Ensure ethical, compliant, secure AI with governance, risk controls, transparency, fairness and regulatory best practice

What you'll learn
- Apply AI governance frameworks to ensure ethical, compliant, and risk-aware deployment of AI across enterprise environments.
- Identify, assess, and mitigate fairness, transparency, privacy, and security risks throughout the AI lifecycle.
- Implement governance tools and workflows, including documentation, approval gates, and continuous monitoring with watsonx.governance.
- Develop organizational playbooks and reporting structures that demonstrate accountability to executives, auditors, and regulators.
- Classify AI systems by risk tier and enforce proportional controls that meet regulatory and ethical requirements.
- Design human-in-the-loop oversight and escalation workflows to ensure safety and prevent harmful automated decisions.
- Lead enterprise-wide governance adoption through effective change management, policy integration, and stakeholder alignment.

Requirements
- No prior AI governance experience required — we start from the foundations
- A basic understanding of how AI or machine learning systems are used in real business contexts
- Familiarity with organizational roles (product, data, legal, compliance) is helpful but not mandatory
- Interest in topics like responsible AI, ethics, policy, or operational risk management
- Curiosity and a willingness to explore how AI impacts organizations and society
- Access to a laptop/desktop computer and standard internet connection
- (Optional) Exposure to enterprise AI or analytics projects will enhance learning but is not required

Description
This course involves the use of artificial intelligence(AI).

AI Governance: Strategy, Policy & Responsible Deploymentis a comprehensive certification course designed to equip professionals with the knowledge, tools, and frameworks required to drivetrustworthy,ethical, andcompliant AIadoption within modern enterprises. As organizations accelerateAI transformation, the need for cleargovernance, strongrisk management, andregulatory alignmenthas never been more essential. This course empowers learners to confidently design, deploy, and monitorresponsible AI systemsthat protect users, uphold values, and deliver sustainable business impact.

Learners will develop a practical and strategic understanding ofAI governance frameworks, includingrisk-tiering,policy enforcement,model transparency,fairness testing,explainability, andoperational controls. They will learn howdata quality,data lineage, andprivacy-preserving machine learningshape the integrity and security of AI outcomes. Through hands-on labs usingIBM watsonx.governance, participants gain real-world experience automatingcompliance,monitoring, andaccountabilityacross the entireAI lifecycle— from design and development to deployment, auditing, and decommissioning.

A key focus of the course is aligningAI governancewith global regulations and best practices, such as theEU AI Act,GDPR,NIST AI Risk Management Framework, andISO/IEC 42001standards. Learners will explore how to meet stringent requirements fortransparency,privacy,bias mitigation,incident response, andhuman oversight, ensuring thathigh-risk AIsystems operate safely and lawfully. Alongside compliance, the course emphasizes the strategic role of governance in enabling responsible innovation — demonstrating howethical AIbecomes a source ofcompetitive advantage, not a barrier to progress.

Participants will mastermodel documentationtools includingmodel cards,data sheets, andrisk logs, ensuring decisions are traceable, reviewable, and audit-ready. They will build skills incontinuous monitoring, detectingdrift,performance degradation, andsecurity threatsto maintain user trust throughout the system’s life in production. Through exposure tored-teaming,adversarial testing, andethical escalation workflows, learners develop an integrated, proactive defense against AI misuse and unintended harm.

Finally, this course prepares learners to leadenterprise-wide AI governance adoption, includingchange management,training systems, andorganizational operating models. Students will produce their ownAI governance playbookandresponsible deployment roadmapthat can be implemented immediately within their workplace. They will also learn how to effectively report AI risk posture and governance outcomes toexecutives,boards, andregulators, converting compliance evidence into trust-building communication.

By the end of this program, learners will have the confidence and capability to championresponsible AI, enforce stronggovernance policies, acceleratecompliance readiness, and scaleAI innovationsafely across the enterprise. Whether you are inproduct leadership,data science,security,compliance, oroperations, this certification establishes you as a forward-thinking expert in the design and deployment ofethical, secure, and accountable AI systems.

Who this course is for:
- Product managers and business leaders guiding AI-powered initiatives
- Compliance, legal, and risk management professionals adapting to new AI regulations
- Data and AI practitioners who must align technical decisions with responsible governance
- IT, security, and operations teams ensuring safe and reliable model deployment
- Executives and program managers establishing enterprise AI strategies and policies
- Anyone looking to advance their career by mastering responsible and trustworthy AI practices
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