explainx / curriculum sample

Executive GenAI curriculum — boards, portfolios & proof

Built for CXO forums and regional GMs who need a defensible narrative, not another market-stat deck. Heavy on decision quality and sequencing—not tool training in isolation.

instructional design: bloom’s taxonomy + measurable outcomes

Every module maps to explicit learning outcomes—not open-ended discussion without deliverables. We sequence along Bloom’s taxonomy (remember → understand → apply → analyze → evaluate → create): definitions and guardrails first, then applied exercises, then measurement and approvals. Facilitators run short checks for understanding after each block (2026 materials).

For organic and generative-engine visibility (GEO), we mirror patterns associated with stronger AI-search citation: answer-first sections, statistics where available, authoritative tone, clear H1–H3 structure, comparison tables when they reduce ambiguity, and FAQ blocks intended to pair with FAQPage JSON-LD. Teams produce briefs, scorecards, and checklists—not a generic “AI creativity” workshop.

program objectives

  • Frame a portfolio view: where generative AI changes P&L vs. marginal productivity.
  • Align GC, risk, and BU heads on documentation and review standards before pilots touch customers.
  • Sequence capital & vendor decisions with stage gates and evaluation harnesses.
  • Connect strategy to course-based upskilling so line managers have a path after the offsite.

how we deliver

  1. 1

    Discovery call & problem framing

    We align on sponsors, success metrics, and constraints (2026 tool landscape, data rules, procurement gates) before anything is scheduled company-wide.

  2. 2

    Stakeholder interviews & day-in-the-life context

    Short conversations with practitioners (not only leadership) so scenarios reflect real workflows—not generic slide demos.

  3. 3

    Curriculum design & artifacts

    Modular agenda, exercise scripts, evaluation rubrics, and governance checkpoints matched to your vocabulary (banking, FMCG, engineering, etc.).

  4. 4

    Engaged, hands-on delivery

    Facilitation-led sessions with live exercises, breakout prompts, and documented failure modes—minimum passive lecture time.

  5. 5

    Post-session support: documentation & next steps

    Written recap, pilot backlog, links to explainx.ai courses for scaled upskilling, and optional office hours so momentum doesn’t stop at the workshop.

modules

Portfolio lens: where GenAI actually moves the needle

Avoid scattershot pilots; tie to business model and operating leverage.

session outline

  • Segment initiatives by data advantage, workflow embeddability, and compliance surface area.
  • Margin math patterns (cost-of-serve, conversion, cycle time) matched to public case study structures—updated for your region.
  • Board narrative: what ‘good’ looks like at 90 / 180 days.

labs

  • Score 8–12 anonymous initiative ideas and force-rank into a top-3.

beyond-catalog topics (custom)

  • Scenario planning when foundation-model pricing or SLAs shift mid-pilot.
  • Cross-border data strategy for multinational leadership teams (high-level, legal partners join as needed).

Governance without innovation paralysis

Concrete artifacts executives can sign.

session outline

  • Decision rights: who can approve external model use vs. internal retrieval-only stacks.
  • Incident taxonomy and post-mortem template tied to brand/regulatory exposure.

labs

  • Red-team a near-miss incident brief as a tabletop exercise.

beyond-catalog topics (custom)

  • KPI bridges between model eval metrics and business KPIs finance already tracks.

quick contact

Scope or pilot this curriculum

Share sponsor, headcount, and cities — we reply with timing and options. Rough budget helps us match the right depth.

related on-demand courses

faq

Will this duplicate our strategy consulting?

No—it’s facilitation to **create internal alignment**; we surface tradeoffs and documentation patterns executives can reuse.

← All curriculum samples·training hub