By the end of this program, participants will be able to:
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Identify high-value agentic AI opportunities aligned to enterprise priorities
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Build ROI cases using payback/NPV and value-capture assumptions
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Map agent flows and basic orchestration for core processes
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Define human-in-the-loop oversight and accountability models
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Plan integration paths with existing platforms and data sources
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Anticipate role evolution and workforce enablement needs
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Draft a leadership-ready pitch that links governance to outcomes
Module 1: Agentic AI Foundations (8 hours)
Build foundational understanding of agentic AI architectures, memory systems, orchestration, and governance.
- What agents are (vs. copilots/chatbots); enterprise case studies
- Agent capabilities in practice: task chaining, memory, autonomy levels
- Measuring ROI for agentic AI: tangible/intangible value; payback/NPV
- Orchestration fundamentals and interoperability concepts
- Governance & ownership: compliance, risk, accountability models
Module 2: Agentic AI Adoption & Execution (8 hours)
Transition from experimentation to enterprise-scale adoption, with frameworks for integration, change management, and workforce transformation.
- Human-in-the-loop and change-management approaches
- Enterprise integration patterns (e.g., CRM/ERP, communications platforms)
- Bridging pilot-to-production: scaling beyond POCs
- Workforce transformation: augmentation vs. automation
- Market scan and vendor evaluation; cost–benefit analysis
- Capstone: Leadership pitch covering ROI, governance, and agent flow design
- Advanced options: Model Context Protocol (MCP), semantic routing, tool/graph orchestration, memory stores, evaluator agents
For senior decision-makers and the leaders who operationalize them: CIOs, CTOs, VPs, business unit heads, strategy and transformation directors, innovation leads, enterprise architects, and program managers responsible for evaluating agentic AI, governing risk, and integrating capabilities into existing platforms and processes.
Designed to your constraints: typically two days (~16 hours) delivered in person at Caltech CTME or on-site. Options include hybrid delivery, half-day blocks, or spaced sessions to support project-based team learning with practice time between meetings.
How is this different from general AI trainings?
It’s built for business leaders. You’ll focus on ROI, governance, and adoption strategy—not model tuning—so decisions translate to measurable outcomes and managed risk.
Can this be customized to our industry and stack?
Yes. We tailor modules, cases, and exercises to your sector, systems, and workforce readiness, aligning with your data, tools, and governance practices.
What will participants produce?
Teams create a leadership-ready pitch deck that connects agent flows to ROI, governance, and integration paths. Artifacts are for educational purposes and internal planning.
Do we need technical prerequisites?
No. Technical concepts are framed in business terms. Mixed cohorts (business, product, architecture) work well.
How are security, compliance, and risk handled?
We introduce governance models, HITL oversight, and ownership/accountability structures, and we discuss aligning with your compliance requirements.
Who should join from IT and the business?
A blended group—business leaders, transformation/innovation leads, and enterprise/solution architects—supports realistic planning and change management.
Is there an assessment or certificate?
This is a non-credit professional program with pass/fail completion based on participation and in-class activities; a Caltech CTME certificate is issued upon successful completion.
