Recommended Topics (for 15–20 senior leaders)
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Executive AI Primer: What leaders need to know now—GenAI/LLMs, RAG, limits, risks, and where value actually shows up
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Value & Use-Case Portfolio: Identify, score, and prioritize use cases (ROI, feasibility, data readiness, model risk) to build a short-list for pilots
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Data, Architecture & MLOps: Platform choices, integration, evaluation/monitoring, cost controls, and LLMOps considerations
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Operating Model & Roles: Decision rights, product vs. platform responsibilities, staffing plan (product, data, ML, security), partner/vendor strategy
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Governance, Risk & Compliance: Responsible AI guardrails—privacy/IP, bias/testing, safety (hallucination mitigation), policy and regulatory mapping
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Roadmap & Metrics: 30-60-90 day plan, KPI set (value, accuracy, latency, cost/req), review cadence, and change-management approach
Optional add-ons (choose 1–2 if time permits)
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Sector case studies & mini-demos
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Communications kit for boards/executives
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Budgeting & unit economics for AI
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Procurement & vendor due diligence
Designed for leadership teams of 15–20, this lab is ideal for CEOs, COOs, CIOs/CTOs/CDOs, CFO sponsors, and VPs/Directors across Product, Engineering, Data/AI, Operations, and Strategy who must set AI direction and own outcomes. It’s equally valuable for cross-functional leaders in Security, Risk/Compliance, Legal, and HR/Change who will govern, staff, and scale AI. Perfect for executive retreats, board sessions, and enterprise or business-unit strategy off-sites—on campus at Caltech or at your location.
Is this the right program if we want concrete, technology-specific AI decisions—not just theory?
Yes. This lab is built for senior leaders who need to choose high-value AI use cases, set guardrails, and approve an investment roadmap. You’ll work with current technologies (LLMs, RAG, fine-tuning, evaluation/monitoring, MLOps/LLMOps) translated into executive choices.
Do participants need a technical background?
No coding is required. We provide an executive primer and shared vocabulary so mixed leadership teams (product, engineering, data/AI, operations, risk, legal, HR) can evaluate options, trade-offs, and risks together.
How is the workshop customized for our organization?
Before the session, we gather your priorities and sample use cases; during the lab, we score and prioritize them by ROI, feasibility, data readiness, and model risk. We align recommendations to your industry, risk posture, and platform/infrastructure direction.
What tangible outputs will we leave with?
A ranked use-case portfolio, an initial AI operating model and governance guardrails, and a 30-60-90 day action plan with owners, milestones, KPIs, and checkpoints—ready to brief boards and operating leaders.
What format, size, and location work best?
Designed for 15–20 senior leaders, this is a one-day, facilitated working session held on campus at Caltech or at your location. Options include pre-work webinars, an extra half-day for roadmap deep-dives, and CEUs/PDUs upon request.
Will Caltech faculty facilitate or participate in the workshop?
Yes—if you choose. As part of customization, we can include Caltech professors and researchers for briefings on current research, or talks on AI in science and engineering. We can also arrange lab visits and bring in guest speakers (e.g., JPL leaders, industry leaders, external experts) to deepen relevance.
How does this differ from “Reinventing Work for the Age of AI”?
This lab focuses on AI technology strategy—use cases, platforms, governance, and investment roadmaps. Reinventing Work centers on workforce and operating-model strategy—skills, roles, org design, and change leadership. Some clients run them as a paired sequence.
Can we bring sensitive use cases or data? What about confidentiality?
We don’t require proprietary data for the lab; sanitized examples are sufficient. If preferred, we can execute an NDA and structure breakouts to protect confidentiality while still producing decision-ready outputs.
