Formats⟩Live Virtual: 4 hrs./1 Day |In-Person: 6 hrs./1 Day
Artificial intelligence is no longer experimental. It is becoming a core capability for mission delivery, operational efficiency, and public service innovation. However, successful AI adoption in business requires more than tools. It demands clear strategy, governance, and alignment with mission, policy, and public trust. This course equips business leaders and program managers with the frameworks, decision models, and practical steps needed to design, govern, and implement an AI strategy responsibly and effectively.
Learning Objectives »
Define what an AI strategy means.
Align AI initiatives to mission, priorities, and mandates.
Establish AI governance, risk management, and ethical safeguards.
Build a phased, realistic AI roadmap.
Lead cross-functional adoption and change management.
Course Agenda
Identifying Strategic AI Opportunities (Where AI Should be Applied)
Linking AI to Organizational Mission
Use Cases in Business
Efficiency vs. Decision-Making Risk
“Safe” Starting Points
Avoiding High-Risk Early Deployments
Prioritization Framework
Common AI Use Cases
Human-AI Collaboration in Workflows (How AI Fits into Work)
Redefining Work: Humans + AI
Human-in-the-loop Systems
Designing AI-Supported Workflows
Building Trust and Adoption
Case Studies: Business AI
Governance, Risk and Responsible AI
Why Responsible AI is Non-Negotiable
Core AI Risks
AI Governance Framework
Vendor and Tool Evaluation
Monitoring and Lifecycle Management
Building and Executing an AI Roadmap
Defining AI Vision Aligned to Mission
AI Roadmap Development Framework
Resource and Capability Planning
Change Management and Adoption
Measuring Success, ROE and ROI
GenAI and the Future
Generative AI in Business Context
Practical GenAI
GenAI Prompting as a Workforce Skill
Emerging Trends
Developing an AI Strategy for Business Leaders
Formats⟩Live Virtual: 4 hrs./1 Day |In-Person: 6 hrs./1 Day
Artificial intelligence is no longer experimental. It is becoming a core capability for mission delivery, operational efficiency, and public service innovation. However, successful AI adoption in business requires more than tools. It demands clear strategy, governance, and alignment with mission, policy, and public trust. This course equips business leaders and program managers with the frameworks, decision models, and practical steps needed to design, govern, and implement an AI strategy responsibly and effectively.
Learning Objectives »
Define what an AI strategy means.
Align AI initiatives to mission, priorities, and mandates.
Establish AI governance, risk management, and ethical safeguards.
Build a phased, realistic AI roadmap.
Lead cross-functional adoption and change management.
Course Agenda
Identifying Strategic AI Opportunities (Where AI Should be Applied)
Linking AI to Organizational Mission
Use Cases in Business
Efficiency vs. Decision-Making Risk
“Safe” Starting Points
Avoiding High-Risk Early Deployments
Prioritization Framework
Common AI Use Cases
Human-AI Collaboration in Workflows (How AI Fits into Work)
Redefining Work: Humans + AI
Human-in-the-loop Systems
Designing AI-Supported Workflows
Building Trust and Adoption
Case Studies: Business AI
Governance, Risk and Responsible AI
Why Responsible AI is Non-Negotiable
Core AI Risks
AI Governance Framework
Vendor and Tool Evaluation
Monitoring and Lifecycle Management
Building and Executing an AI Roadmap
Defining AI Vision Aligned to Mission
AI Roadmap Development Framework
Resource and Capability Planning
Change Management and Adoption
Measuring Success, ROE and ROI
GenAI and the Future
Generative AI in Business Context
Practical GenAI
GenAI Prompting as a Workforce Skill
Emerging Trends
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