Operationalizing Data and AI Initiatives

This unit focuses on converting strategy into executable data and AI initiatives by assessing build vs. buy decisions, identifying and prioritizing use cases, and defining scope, KPIs, schedules, and stakeholders. Learners will plan resourcing, training, governance, and compliance, perform data resource audits, and produce project charters and monetization/financial use case recommendations to prepare initiatives for implementation.

Learning Objectives

• Analyze build-versus-buy options and foundation-model infrastructure trade-offs using cost models and performance criteria to recommend the most cost-effective technical approach for a selected use case.
• Evaluate and prioritize potential data and AI use cases against business value, speed-to-market, compliance risk, and data readiness, and produce a scoped project charter that defines scope, schedule, stakeholders, and measurable KPIs.
• Develop a comprehensive resourcing and governance plan that specifies required skill sets, training and hiring recommendations, fine-tuning and operational responsibilities, and strategies for adherence and compliance.
• Apply auditing and documentation techniques to conduct a data resources audit, extract relevant information from documentation and interviews, and produce proposals for financial improvements and data monetization opportunities.