EVP Artificial Intelligence Innovation Program (AIIP)

EVP Artificial Intelligence Innovation Program (AIIP)

Programs & initiatives
Submit a proposal
2019 Harvard University IT Summit

Contents

Overview

The Executive Vice President (EVP) Artificial Intelligence Innovation Program (AIIP) is intended to encourage the exploration of generative AI to improve operational efficiency and administrative systems and processes. The AIIP is an inclusive approach to innovation—soliciting proposals directly from EVP staff—and is designed to foster creativity and collaboration among our respective Units’ teams.

Program Details

Staff are invited to submit a proposal about an identified AI-related innovation opportunity.  Selected proposals will receive: 

  • Access end-user AI tools such as AI Sandbox and ChatGPT Edu, development tools including OpenAI Codex and Claude Code, and AI providers including AWS, OpenAI, and Google.
  • Connect with HUIT and CADM experts and practitioners to shape your proposal and accelerate development of your pilot solution.
  • Up to $15,000 in funding for a 6-month experiment or pilot.
  • An opportunity to showcase key learnings and AI innovations to administrative leadership. 

More information on the EVP-AIIP Round 1 pilots can be found here.

Key dates and timing

  • February 6: Proposal submission opens to EVP areas.
  • March 20: Proposal submissions close for review by submission committee; submissions will be prioritized based on alignment to themes identified by the University Generative AI Administration and Operations Committee.
  • April: Proposal groups pitch their idea to select members of the Office of the EVP and awards announced for selected proposals.
  • May - October: Experimentation with assistance from HUIT.
  • November: Teams share project outcomes and learning with sponsors.   

For any questions or assistance in refining proposal ideas, please contact evp_aiip@harvard.edu. 

Office hours

First round pilots (2025)

AI for Administrative Learning Resources

  • Leverage AI to create draft training content for sponsored research topics at Harvard, significantly reducing SMEs' development time.
  • Increase efficiency, accelerating content delivery while reducing non-compliance risks and audit exposure. 

AI-TIES (Targeted Information Extraction and Summarization)

  • Use generative AI to automate information extraction and create task-specific summaries, improving efficiency and demonstrating AI's ability to filter pertinent content.
  • Aim for precise information extraction and summarization, lessening manual distillation effort. 

HUHS FirstAIde

  • Develop an AI chatbot for Harvard University Health Services (HUHS) customer support staff, offering digital health plan services and integrating AI for scaled customer service and improved response times.
  • Improve customer service by providing faster, precise responses and increasing operational efficiencies, serving as a learning tool for Member Services staff. 

Improving Reunion Customer Service with AI

  • Employ AI tools for email review and triage in Alumni Affairs & Development areas across campus, streamlining large volume email processing.
  • Save staff time, enhance efficiency in handling requests and feedback, and provide effective support in donor-related tasks. 

Productivity, Risk-Mitigation, and Efficiency through AI-Assisted Contract Drafting

  • Utilize AI for contract drafting and analysis at the Office of Contract Management (OCM), enabling faster and more reliable self-generated drafts and risk assessments.
  • Enhance OCM’s efficiency and effectiveness in contract review and negotiation, reducing risks and achieving savings. 

ServiceRightNow

  • Use AI, particularly ChatGPT, to automate routine service ticket tasks, focusing human expertise on complex issues.
  • Expect a significant reduction in workload, assessed through fewer tickets, quicker response times, and improved customer satisfaction. 

Use of AI in Streamlining Data Use Agreements​

  • Apply AI to streamline processing of Data Use Agreements (DUAs), focusing on identifying standard language exceptions to expedite the review process.
  • Realize a substantial decrease in initial review time, easing the burden on reviewers and negotiators handling complex negotiations. 

Using AI to Enhance the HR Policy Creation and Review Processes​

  • Implement AI to analyze data and improve HR policy creation and review at Harvard, focusing on searchability, accuracy, consistency, relevance, accessibility, or inclusivity.
  • Result in a more accessible, organized policy library, facilitating strategic focus for workforce policy leadership.