Enterprise AI Deployment and Governance

This capstone unit synthesizes technical, ethical, legal, and operational considerations for deploying AI at scale in enterprise and civic contexts. Learners evaluate trade-offs, mitigate risks like bias and ambiguity, and create actionable plans for procurement, hosting, explainability, and smart-city integration.

Learning Objectives

• Analyze build-versus-buy and cloud-versus-on-premises trade-offs and recommend a deployment and procurement strategy that balances cost, scalability, maintenance, security, and compliance for an enterprise AI solution
• Evaluate ethical, legal, and societal risks of AI systems (including bias, lack of transparency, ambiguity, and unintended consequences) and propose concrete mitigation, monitoring, and governance policies
• Apply augmented-analytics, intelligent text-mining, and conversational AI design principles to produce prototype specifications or design recommendations that address problem framing, data quality, and user transparency requirements
• Demonstrate development of an enterprise AI implementation plan that includes risk assessment, explainability approaches, compliance checklists, monitoring/feedback mechanisms, and a roadmap for scalable deployments such as smart-city initiatives