Job Summary:
The Digital, Data, and Design (DĀ³) Institute at Harvard is accepting applications for an AI Learning Program Manager. DĀ³ helps industry leaders re-imagine the potential of AI in business and society through cutting-edge research and experiential learning. We are seeking an experienced Program Managerto help scale the DĀ³ executive education portfolio by embedding AI-enabled workflows into curriculum development, delivery readiness, and program evaluation. This role will work closely with Faculty and the Harvard Business School Executive Education team, to scale a new AI-focused executive workshop program.
The AI Learning Program Manager will operate as a hands-on partner who (1) rapidly translates emerging DĀ³ and HBS faculty research into executive-ready curriculum assets, and (2) designs and operationalizes AI tools, automations, and agentic workflows that streamline recurring program tasks (e.g., content iteration cycles, session readiness packs, evaluation synthesis, and reporting). The role combines strong program management discipline with practical AI fluency.
Job-Specific Responsibilities:
AI-Enabled Program Optimization
- Identify high-impact opportunities to streamline and scale executive education program workflows using AI tools, automation platforms, and agentic systemsāprioritizing improvements that preserve or enhance participant and faculty experience.
- In partnership with the Agentic AI Product Manager, develop and maintain reusable āprogram operating assetsā enabled by AI (templates, prompt libraries, rubric-based QA, agent instructions, workflow documentation, and governance checklists).
- Serve as a trusted advisor to program teams regarding when AI can help optimally scale program effectiveness.
ā¢ Curriculum Development
- Translate DĀ³/HBS research into executive-ready curriculum assets (session plans, frameworks, pre-work, exercises, discussion prompts, teaching notes, reinforcement content), using AI to accelerate synthesis and drafting while ensuring rigorous human review.
- Serve as a primary partner to faculty for refining session plans and program structure, balancing client needs with available expertise and crafting both templated and customized program plans.
- Coordinate faculty touchpoints for overall curricular review and refinement sessions and prepare all relevant documentation as needed.
- Run rapid iteration cycles on curriculum components in partnership with faculty and the Executive Education team, incorporating feedback signals and delivery insights into continuous improvements.
- Build and manage a content ārefresh cadenceā to keep AI and digital content current as research and industry practices evolve.
- Maintain a curriculum library for modular reuse across programs.
ā¢ Evaluation Automation and Insight Generation
- Redesign and automate key components of program evaluation using AI (e.g., survey synthesis, theme extraction, sentiment and qualitative coding support, debrief summaries, action logs, and leadership reporting).
- Implement a structured evaluation approach that produces actionable insights quickly, while maintaining methodological integrity.
- Define and track KPIs tied to program outcomes and operational efficiency (e.g., time-to-insight, time-to-refresh, participant relevance and applicability ratings, content reuse rate, and delivery readiness cycle time).
- Partner with stakeholders to convert evaluation insights into prioritized improvements and measurable follow-through.
ā¢ Delivery Partnership and Operational Excellence
- Partner with HBS Executive Education teams to ensure seamless delivery readiness, using AI-enabled workflows to reduce administrative burden and increase consistency (e.g., faculty prep packs, run-of-show drafts, checklists, participant communications templates).
- Anticipate operational risks and bottlenecks; design mitigations and scalable processes..
- Maintain clear documentation and āsingle source of truthā artifacts (session matrices, responsibility maps, content inventories, evaluation summaries, decision logs).
ā¢ Governance, Quality Assurance, and Responsible AI
- Establish and adhere to governance protocols for AI usage in program workflows and content development, including confidentiality, data privacy, academic integrity, bias awareness, and accuracy verification.
- Implement QA processes for AI-assisted outputs (fact-checking protocols, citation/source traceability, rubric-based review, and sign-off workflows).
- Maintain clear boundaries and documentation for AI/agent behaviors (guardrails, monitoring expectations, escalation paths, and review requirements).
Other:
- Build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents.
- This role is responsible for other duties as assigned.