Higher education must actively integrate artificial intelligence into academic and administrative operations to adapt to rising costs and shifting student expectations.
## Background
This presentation was delivered by Lucy Avetisyan, CIO at UCLA, and published by Ai4 on YouTube on August 29, 2025. According to the page description, the talk explores how artificial intelligence is accelerating a profound transformation in higher education, presenting both disruption and opportunity while illustrating how AI reshapes academic innovation, operations, and decision-making.
## TL;DR
Lucy Avetisyan presents UCLA's proactive strategy for integrating artificial intelligence to address systemic challenges in higher education, such as rising costs and shifting student expectations. She highlights institutional milestones, including the appointment of a Chief Data and AI Officer, strategic industry partnerships, and a campuswide ChatGPT Enterprise pilot that funded dozens of projects across departments. The session concludes with UCLA's 'Moonshot 2027' vision, aimed at achieving universal AI fluency, modernizing curriculum, and establishing robust ethical governance.
## Atmosphere & style
The presentation carries a visionary, strategic, and forward-looking tone that balances the stark economic and cultural realities facing higher education with an inspiring call to action. Avetisyan presents with clarity and institutional purpose, positioning AI not as a purely technical disruption or workforce threat, but as an empowering human-centered partner. The overall feeling is pragmatic and collaborative, leaving the audience with an energized sense of urgency to actively shape the future of academia.
## Key takeaways
- [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) Lucy Avetisyan frames AI's role in higher education around deepening human connections, delivering real-time student insights, and creating a personalized, equitable academic experience.
- [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) Higher education faces rising operating costs (up 3.4% in 2024), aging infrastructure, funding shortages, and changing student expectations that demand proactive institutional adaptation.
- [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) Student AI adoption is overwhelmingly high (87% for schoolwork and 90% for personal management), yet over half feel a lack of guidance despite viewing responsible AI skills as essential for their careers.
- [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) A major curriculum gap exists in higher education, as only 1 in 7 university provosts report reviewing their curriculum to prepare students for AI in the workforce.
- [00:36](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=36s) UCLA appointed Dr. Chris Mattman as Chief Data and AI Officer to lead campuswide and systemwide AI strategy and governance without creating a heavy administrative footprint.
- [00:36](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=36s) UCLA launched foundational literacy initiatives, including an AI Learning Hub where completing AI training was made a mandatory development goal for all IT staff before scaling campuswide.
- [00:36](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=36s) The university formed strategic collaborations with major tech vendors (e.g., OpenAI, Google, Microsoft) and secured domain-specific AI research grants from NASA and the Department of Transportation.
- [00:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=26s) In Fall 2024, UCLA launched a campuswide ChatGPT Enterprise pilot, selecting and funding 68 projects across 27 departments anchored around four operational pillars.
- [00:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=26s) Operational outcomes of the ChatGPT pilot include automated course and instructor feedback processing and over 15 custom GPTs integrated into ServiceNow for IT ticket automation.
- [00:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=26s) Student and academic services expanded through 'Career AI' for 24/7 student career guidance and curriculum realignment at UCLA Extension that led to a high-demand Systems Engineering program.
- [13:39](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=819s) UCLA's 'Moonshot for 2027' aims to achieve full university-wide AI fluency, treating AI as a core, essential skill across faculty, staff, and student workflows.
- [13:39](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=819s) Ethical integrity and workforce transitions will be managed through a new campuswide AI Council launching in late 2025 and structured workforce roadmaps to address job evolution.
## Detailed walkthrough
Here is a detailed, faithful walkthrough of the presentation:
[00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) Introduction and the Urgency for AI in Higher Education
Lucy Avetisyan, Chief Information Officer at UCLA, opens her presentation by clarifying that while she addresses a room of technologists, her talk is not purely focused on hardcore technology—it centers on how artificial intelligence is transforming higher education. She invites the audience to imagine a campus where real-time insights shape each student's journey, where AI deepens human connections rather than replacing them, and where the student experience becomes personal, equitable, and empowering. "This isn't the future we're waiting for," she emphasizes, "This is the one we're living and building together."
Addressing current institutional pressures, Avetisyan notes that higher education faces rising costs, aging infrastructure, severe funding challenges, and rapidly shifting student expectations. Institutions must adapt proactively rather than react passively to remain relevant. Highlighting stark statistics on workforce and student perceptions, she outlines the landscape forcing this evolution:
- **Shift in Credential Perception:** 56% of U.S. teens believe real-world, on-the-job experience is more beneficial than earning a college degree.
- **Curriculum Gap:** Only 1 in 7 university provosts report that their institution has reviewed its curriculum to ensure students are prepared for AI in the workforce.
- **Financial Strain:** Operating costs for U.S. colleges and universities increased by 3.4% in 2024 alone.
- **Student AI Adoption:** 87% of students use AI for schoolwork, 90% use it for personal life management, and students spend an average of 10 hours per week interfacing with AI.
- **Guidance Deficit:** Over half of students feel a lack of guidance regarding AI, yet 62% believe understanding responsible AI usage is critical to their future careers.
[00:36](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=36s) UCLA's Strategic AI Initiatives and Infrastructure
To lead decisively, UCLA appointed its first Chief Data and AI Officer (CDIO), Dr. Chris Mattman, who joined from NASA's Jet Propulsion Laboratory (JPL) where he served as Chief Technology and Innovation Officer. Sitting on the CIO's leadership team, Mattman leads campuswide AI strategy, advanced data analytics, and governance across both UCLA and the broader University of California system without relying on a large, heavy administrative footprint.
UCLA has deployed several foundational initiatives to foster AI innovation and digital literacy across campus:
- **Centralized AI Portal:** Launched a dedicated UCLA AI website outlining principles for responsible use, showcasing approved tools, and listing campus training events.
- **AI Learning Hub:** Created a self-guided educational hub. IT leadership made completing this training a mandatory professional development goal for all IT staff before scaling it to faculty and broader staff.
- **Strategic Vendor Collaborations:** Formed partnerships and pilot projects with AI vendors and technology platforms, including OpenAI, Google, Microsoft, Palantir, Gecko, and ServiceNow.
- **AI-Driven External Grants:** Applied AI to domain-specific research projects, securing grants from NASA and the Department of Transportation for smart city planning and wildlife management initiatives.
[00:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=26s) The ChatGPT Enterprise Campuswide Pilot and Case Studies
In Fall 2024, UCLA launched a campuswide pilot of OpenAI's ChatGPT Enterprise to serve as a testbed for generative AI in teaching, research, and administration. The initiative invited project proposals across campus, receiving 74 detailed submissions and funding 68 projects across 27 departments. To date, 46 of these projects have been completed, anchored by four operational pillars: *Innovation* (prototyping), *Collaboration* (cross-functional engagement), *Capacity Building* (AI fluency), and *Community Development* (responsible use).
Key outcomes across departmental case studies include:
- **Automated Course & Instructor Feedback:** A team transformed faculty evaluation analysis from a slow, manual process into a rapid, scalable automated feedback system, recognized at both InstructureCon and UC Technology conferences.
- **ServiceNow IT Ticket Automation:** The central IT team built over 15 custom GPTs integrated into ServiceNow. The system automates ticket triage, streamlines staff onboarding, reduces turnaround times, and provides step-by-step guides for troubleshooting network issues.
- **24/7 Career Guidance:** The UCLA Career Center launched "Career AI," enabling students to access personalized career guidance outside standard business hours.
- **Curriculum Modernization:** UCLA Extension used AI models to realign its Technical Management Program with industry demands, resulting in a new Systems Engineering program that exceeded enrollment targets.
- **Community of Practice:** Established an active interdisciplinary community of practice, allowing healthcare and medical education faculty to share best practices on AI integration.
[13:39](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=819s) UCLA's "Moonshot 2027" and Ethical AI Governance
Avetisyan outlines UCLA's "Moonshot for 2027," targeting full AI fluency across the entire university ecosystem. Under this framework, AI is treated as a core skill across every discipline rather than an optional tool:
- **AI-Enabled Faculty:** Equipping educators to teach and conduct research using integrations such as OpenAI with Canvas and deep research tools from Google and OpenAI.
- **AI-Empowered Staff:** Positioning AI as an supportive "teammate" that eliminates repetitive labor rather than a threat to job security, incorporating developer tools like OpenAI Codex for software development.
- **Ethical Integrity:** Enforcing strict standards around equity, privacy, and accountability through a new campuswide AI Council launching in late 2025.
- **Workforce Transition Mapping:** Utilizing frameworks like the Gartner AI workforce roadmap to evaluate job evolution, manage organizational anxiety, and upskill employees safely.
Concluding her talk with the quote, "The best way to predict the future is to invent it," Avetisyan calls on academic leaders to take bold, collaborative steps in actively shaping an ethical, AI-enabled future for higher education.
## Notable quotes
> [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) This isn't the future we're waiting for. This is the one we're living and building together. — Lucy Avetisyan
> [13:39](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=819s) The best way to predict the future is to invent it. — Lucy Avetisyan
## Mentioned
Lucy Avetisyan, UCLA, Dr. Chris Mattman, NASA Jet Propulsion Laboratory, University of California, OpenAI, Google, Microsoft, Palantir, Gecko, ServiceNow, Department of Transportation, ChatGPT Enterprise, InstructureCon, UC Technology, UCLA Career Center, UCLA Extension, Canvas, OpenAI Codex, Gartner
## Video description
Lucy Avetisyan, CIO, UCLA
Abstracts
The talk will explore how AI is accelerating a profound transformation across higher education, presenting both disruption and unprecedented opportunity. The session will share strategic insights, leadership lessons, and critical observations from navigating this fast-evolving landscape. The talk will illustrate how AI is reshaping academic innovation, operational priorities, and institutional decision-making in real time. Attendees will gain a forward-looking perspective on how to lead with clarity, purpose, and agility in the face of rapid change. This session is designed for leaders who are ready to move beyond experimentation and begin actively shaping the AI-enabled future of higher education.
UCLA 在 27 个校园部门部署 ChatGPT
高等教育必须积极将人工智能融入学术与行政运营，以应对不断攀升的成本和学生期望的变化。
Lucy Avetisyan 介绍了 UCLA 积极整合人工智能以应对高等教育系统性挑战（如成本上升和学生期望改变）的战略。她重点介绍了该校的里程碑举措，包括任命首席数据与 AI 官、建立战略性行业合作伙伴关系，以及开展在全校资助了数十个跨部门项目的 ChatGPT Enterprise 试点。会议最后展望了 UCLA 的“登月计划 2027”（Moonshot 2027）愿景，旨在普及全员 AI 素养、推进课程现代化并建立健全的伦理治理体系。
UCLA 首席信息官 Lucy Avetisyan 指出高等教育正面临运营成本上升（2024年上涨 3.4%）和课程脱节等严峻压力；尽管高达 87% 的学生已在课业中使用 AI，但超过半数学生感到缺乏校方指导。 (0:04)
为确立系统化战略，UCLA 任命前 NASA JPL 高管 Chris Mattman 博士为首任首席数据与 AI 官，推出将 AI 培训作为 IT 人员必修目标的 AI 学习中心，并与 OpenAI、Google 等企业展开战略合作。 (0:36)
2024 年秋季，UCLA 启动了全校级 ChatGPT Enterprise 试点，在 27 个部门资助了 68 项应用创新，覆盖自动化课程反馈、基于 ServiceNow 的 IT 工单自动化以及全天候职业咨询等场景。 (0:26)
围绕“Moonshot 2027”规划，UCLA 致力于在全校生态中普及 AI 素养，并计划于 2025 年底前成立全校性 AI 委员会，全面推进 AI 伦理、隐私与问责治理。 (13:39)
Reading summary
UCLA Chief Information Officer Lucy Avetisyan asserts that universities must proactively embed artificial intelligence across administrative, instructional, and research workflows to navigate escalating operational costs, credential skepticism, and pervasive, unguided student technology use.
Institutional Pressures Driving Academic AI Adoption (0:04)
Higher education institutions face compounding structural headwinds that challenge traditional operations. Operating costs for U.S. colleges and universities rose by 3.4% in 2024, while public confidence in traditional credentials continues to erode, with 56% of U.S. teenagers reporting that direct workplace experience is more valuable than completing a college degree. Despite these economic and cultural shifts, only 1 in 7 university provosts reported that their institution had formally reviewed its curriculum to prepare students for an AI-augmented labor market.
Simultaneously, student technology habits have outpaced institutional policy. Survey data indicates that 87% of students actively use AI for coursework, 90% rely on it for daily personal management, and users spend an average of 10 hours per week interacting with AI systems. Although more than half of students report receiving inadequate institutional guidance on the technology, 62% recognize that mastering responsible AI practices is vital to their future career prospects.
Centralized Leadership and Foundational Infrastructure (0:36)
To coordinate strategic implementation across campus and the broader University of California system, UCLA appointed its first Chief Data and AI Officer, Dr. Chris Mattman, previously the Chief Technology and Innovation Officer at NASA's Jet Propulsion Laboratory. Operating within the CIO's executive team, Mattman directs campuswide AI governance and analytics with a deliberately lean administrative footprint, avoiding heavy institutional overhead.
UCLA backed this governance model with dedicated digital infrastructure, establishing a centralized public portal detailing approved tools, training events, and responsible use principles. Institutional leadership also mandated foundational AI coursework as a professional development requirement for all IT personnel before rolling out the educational hub to faculty and administrative staff. In parallel, the university formalized vendor partnerships with platforms including OpenAI, Google, Microsoft, Palantir, Gecko, and ServiceNow, while securing federal AI research grants from NASA and the Department of Transportation for municipal planning and wildlife tracking initiatives.
Campuswide ChatGPT Enterprise Pilots and Applications (0:26)
In Fall 2024, UCLA deployed OpenAI's ChatGPT Enterprise as an institutional testbed across teaching, research, and operations. The initiative elicited 74 project proposals and funded 68 implementations across 27 departments, with 46 projects successfully completed. The rollout was structured around four operational pillars: innovation, collaboration, capacity building, and community development.
Demonstrated departmental outcomes span operational triage and academic programming. UCLA's central IT department deployed over 15 custom GPTs integrated into ServiceNow to automate help-desk ticket routing, assist staff onboarding, and generate network troubleshooting guides. Academic operations automated faculty evaluation feedback, replacing manual review processes. Furthermore, the UCLA Career Center deployed a 24/7 advisory agent named Career AI, UCLA Extension restructured its Technical Management curriculum into a high-demand Systems Engineering program that surpassed target enrollments, and medical faculty established an interdisciplinary community of practice to coordinate healthcare AI training.
Long-Term Fluency and Ethical Governance (13:39)
Looking ahead, UCLA defined its "Moonshot for 2027," an initiative intended to establish baseline AI fluency across every discipline rather than treating computational tools as niche electives. The operational plan integrates OpenAI within the Canvas learning management system, equips researchers with deep research tools from Google and OpenAI, and incorporates developer platforms such as OpenAI Codex to support internal software engineering.
To address institutional friction and worker displacement concerns, the administration adopted Gartner's AI workforce roadmap to evaluate job evolution and guide employee upskilling. Avetisyan framed staff-facing tools as administrative teammates designed to eliminate routine tasks rather than head count. UCLA plans to enforce formal accountability, equity, and data privacy standards by inaugurating a permanent campuswide AI Council in late 2025.
Avetisyan concludes that university leaders must collaboratively design AI implementations rather than reacting passively to market shifts. However, realizing this institutional transformation will depend on mitigating staff anxieties over job displacement and establishing functional accountability once the permanent AI Council convenes in late 2025.
## Background
本视频由 Ai4 频道于 2025 年 8 月 29 日发布在 YouTube 平台。内容为加州大学洛杉矶分校（UCLA）首席信息官（CIO）露西·阿维蒂西安（Lucy Avetisyan）的主题演讲，主要探讨 AI 对高等教育带来的深刻变革与机遇，分享 UCLA 在推动学术创新、重塑运营流程及制定 AI 治理路线图等方面的战略思考与领导力实践。
## TL;DR
面对学生高频应用 AI 与传统教育体系脱节的现实，UCLA 率先设立首席数据与人工智能官（CDIO），积极推进全校 AI 门户、学习中心及跨界产业生态合作。学校通过引入 OpenAI ChatGPT Enterprise 落地了数十个覆盖教学、科研与 IT 运维的标杆项目，并确立了面向 2027 年让全校师生实现“AI 精通（AI Fluent）”的宏大登月计划。在此过程中，UCLA 坚守“无诚信即无创新”的伦理准则，成立全校 AI 委员会并普及全员素养培训，致力于将 AI 打造成赋能人类的得力队友，主动塑造高等教育的全新未来。
## Atmosphere & style
演讲整体基调温和坚定、务实且极富前瞻性。露西·阿维蒂西安以亲切自如的台风开场，迅速将复杂的技术转型锚定在以人为本的教育核心价值观之上，既冷静客观地剖析了高校面临的系统性挑战与职场焦虑，又用生动的实战成果展现了主动破局的信心。整场分享逻辑紧凑、情感充沛且极具号召力，让观众在严谨的战略框架与温暖的人文关怀中深切感受到教育变革的澎湃生机。
## Key takeaways
- [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) 高等教育 AI 转型的核心使命是在坚守大学核心价值观与人文底色的前提下，利用 AI 释放人的潜能，打造个性化且公平的学习体验。
- [01:40](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=100s) 传统教育供给与青年需求严重脱节：87% 的学生已使用 AI 辅助学业，但超过半数缺乏指导，且仅有七分之一的大学教务长审查了课程体系。
- [01:40](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=100s) 高等教育面临结构性信任与成本危机：56% 的美国青少年认为在职经验比大学学位更有价值，且大学单年运营成本上涨了 3.4%。
- [03:41](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=221s) UCLA 率先设立首席数据与人工智能官（CDIO），跨越行政与学术壁垒主导全校战略路线图，而非设立孤立的官僚部门。
- [03:41](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=221s) 推进全员创新机制与基础设施：推出 AI 门户、创新倡议及学习中心，将 AI 专业技能学习列为 IT 员工的强制性发展目标并推向全员。
- [06:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=386s) 开展 OpenAI ChatGPT Enterprise 深度试点：覆盖 27 个院系的 68 个项目，并成功孵化出获得 NASA 和美国交通部资助的研究课题。
- [06:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=386s) 确立 AI 推进四大核心支柱：围绕创新试验文化、跨学科协作、AI 数字素养能力建设以及合乎伦理的社区发展展开。
- [09:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=566s) 业务场景多点开花：重构教学反馈收集流程、在 ServiceNow 上定制 15+ 运维 GPT、打造 24/7 Career AI 平台并重塑继续教育课程。
- [12:53](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=773s) IT 运维搭建交互式排障中心：基于历史工单自动生成标准化操作指南，切实缩短网络故障响应时间并降低停机风险。
- [13:39](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=819s) 启动 2027 登月计划（Moonshot）：以全员精通 AI（AI Fluent）为目标，积极探索大模型深度科研能力，并将 AI 视作协同队友而非生存威胁。
- [15:06](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=906s) 恪守“无诚信即无创新”底线：正式成立全校 AI 委员会，建立严格的第三方工具审查机制，确保数据隐私与算法公平不可逾越。
- [16:07](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=967s) 以文化投资化解职场焦虑：借助 Gartner 框架评估岗位形态重塑，通过全员素养培训赋能员工，主动构建理想的高等教育未来。
## Detailed walkthrough
### [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) 开启高等教育的 AI 转型愿景与核心使命
演讲伊始，加州大学洛杉矶分校（UCLA）首席信息官（CIO）露西·阿维蒂西安（Lucy Avetisyan）微笑着询问在场听众有多少人是纯粹的技术人员。她随即澄清，这并不是一场艰深晦涩的技术硬核对话，而是聚焦于 AI 与高等教育的深度交织。当前高等教育界正在探寻一个根本问题：如何在坚持大学核心价值观的同时，利用 AI 释放高等教育中人的潜能？面对瞬息万变的技术浪潮，UCLA 的使命是在不放弃人文底色与伦理准则的前提下，开启一场深刻的制度变革。
在简短寻找演讲翻页笔的轻松插曲之后，她邀请全场听众闭上双眼构想一个未来校园：在那里，每一位学习者的成长路径都能依托实时数据洞察来个性化塑造；AI 不会削弱或取代人与人之间的联结，反而进一步加深了这种联结；学生的就学体验变得比以往任何时候都更加个性化、公平且赋予人力量。她坚定地指出，这不是一个遥不可及、只能被动等待的未来，而是 UCLA 师生正在共同生活和亲手构建的现实。
### [01:40](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=100s) 高等教育面临的现实压力与剧烈分歧的数据画像
高等教育正承受着巨大的系统性压力，UCLA 也不例外。伴随着近期新闻舆论的关注，大学面临着严峻的资金拨款挑战、日益老化的基础设施压力以及不断攀升的运营成本。更为关键的是，学生对高等教育的期望与认知正在经历极其迅猛的代际转变。面对外部剧变，大学必须采取积极适应而非被动应付的姿态，才能在未来格局中保持不可替代的现实相关性。
阿维蒂西安列举了一组触目惊心的数据对比，揭示了传统教育供给与青年群体需求之间的巨大脱节：
- 56% 的美国青少年认为，获得切实的在职工作经验比拿到大学学位更有价值。
- 仅有七分之一（约 14.3%）的大学教务长（Provost）表示其学校已对课程体系进行了全面审查，以确保学生能为 AI 驱动的未来职场做好准备。
- 仅在 2024 年，美国各大学院校的运营成本就上涨了 3.4%。
- 现实中，87% 的学生已经在使用 AI 辅助完成学业，90% 的学生利用 AI 管理个人生活，平均每周与 AI 交互或导航的时间长达约 10 个小时。
- 与高频使用形成鲜明反差的是，超过半数的学生感到缺乏清晰的使用指引，同时有 62% 的学生认为理解如何负责任地使用 AI 对他们未来的职业生涯至关重要。
这一巨大鸿沟正是高等教育展现领导力的关键契机。高校必须以明确的伦理框架、清晰的方向感和赋能机制来引领变革，确保毕业生步入社会时具备与 AI 协同共存的完备素养。
```mermaid
flowchart TD
accTitle: 学生与传统教育在AI适应上的脱节
subgraph S1["学生现实现状"]
A["87% 学生将 AI 用于学业<br/>90% 用于个人管理<br/>每周交互约 10 小时"]
B["超过 50% 感到缺乏官方指引<br/>62% 认为负责任使用 AI 至关重要"]
A --> B
end
subgraph S2["高校制度现实"]
C["仅 1/7 教务长审查了课程体系"]
D["运营成本单年激增 3.4%<br/>56% 青少年质疑大学学位价值"]
C --- D
end
subgraph S3["战略应对方向"]
E["高校以清晰指引、伦理赋能引领转型<br/>培养学生与 AI 共存的职业核心竞争力"]
end
S1 -.->|巨大代际断层| S2
S1 ==> E
S2 ==> E
```
### [03:41](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=221s) 设立 CDIO 职位与全校性 AI 推进举措
为了果断推进战略落地，UCLA 率先设立了全校首位首席数据与人工智能官（Chief Data and AI Officer, 简称 CDIO），这也是全美高等教育界最早设立该职位的举措之一。约一年前，克里斯·马特曼（Chris Mattman）正式加入领导团队担纲此任。此前，他曾长期担任 NASA 喷气推进实验室（JPL）的首席技术创新官。阿维蒂西安强调，CDIO 并不掌管庞大的官僚团队或专属预算盘子，其核心职责在于穿针引线、纵览全局机遇，跨越不同业务部门与学术学院，协同全校利益相关者共同制定数据与 AI 创新的战略路线图，并在加州大学系统及 UCLA 的多个 AI 治理委员会中发挥主导作用。
在推动全员创新方面，阿维蒂西安秉持着"创新绝不应仅局限于 IT 部门内部"的理念，全面联合校内外伙伴铺开多项基础设施与制度建设：
- 推出专属的 AI 门户网站：系统性阐明负责任使用 AI 的指导原则，集中展示可用 AI 工具，发布相关研讨活动与全校培训机遇。
- 启动 AI 创新倡议（AI Innovation Initiative）：在全校范围内激发跨界创造力，鼓励各部门申报并孵化原型解决方案。
- 建立 AI 学习中心（AI Learning Hub）：为全校教职工提供自主学习路径。该项目已在 IT 组织内部先行试点，并被列为全体技术人员的强制性专业发展目标（Mandatory Professional Development Goal），目前正全面推向全校教职工。
- 深化产业与研究生态合作：积极推进与 Google、微软（Microsoft）、OpenAI 以及 Palantir、Gecko 等前沿企业的深度协作，并在近一年内密集引进了大批顶尖 AI 学者，全面夯实科研基础设施。
### [06:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=386s) OpenAI ChatGPT Enterprise 试点落地与四大支柱
去年秋季，UCLA 正式在全校范围内启动了 OpenAI ChatGPT Enterprise（企业版）试点项目。这不仅仅是一项单纯的 IT 工具采购或技术部署，更是作为学校探索生成式 AI 赋能教学、科研与行政管理的战略试验场。UCLA 试图借此摸索出一套兼顾责任边界、制度治理、素养培育和规模化创新的全校推广模式。
该试点项目一经发布便引发了全校范围的热烈反响，各学院和部门提交了多达 74 份详尽且篇幅可观的长篇项目提案。学校从中遴选出跨越 27 个不同院系部门的 68 个项目，精准聚焦于三大核心战略领域：赋能教学创新、提升运营效能以及激活 AI 驱动的科研前沿。截至目前，已有 46 个项目顺利结项并产出了切实的落地成果与复盘经验。不仅如此，试点中孵化出的智慧城市规划以及野生动物管理等前沿课题，已成功赢得了来自美国国家航空航天局（NASA）和美国交通部（DOT）的国家级研究资助，充分印证了高校内部的 AI 探索具有远超校园围墙的社会溢出价值。
这一系列探索紧紧围绕着 UCLA 推行 AI 创新的四大核心支柱：
- 创新（Innovation）：在全校深度培育快速构建原型的试验文化。
- 协作（Collaboration）：打通学术与行政壁垒，推动跨职能、跨学科深度联动。
- 能力建设（Capacity Building）：系统性普及全校师生的 AI 数字化素养与流畅应用能力。
- 社区发展（Community Development）：支撑负责任且合乎伦理道德的技术工具应用。
### [09:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=566s) 教学反思、IT 服务自动化与职业发展中心的落地案例
随着各项试点的推进，多个业务场景迎来了实质性变革。其中一个广受赞誉的典型案例是教学反馈收集机制的革新。以往收集和提炼教师授课反馈的过程极其繁琐、人工化且滞后，而借助 AI 自动化流程后，分析工作变得极其敏捷且具备高度可扩展性，将一线教师从机械的数据整理中彻底解放出来，使其能够专注于教学模式创新。该创新成果甚至在 InstructureCon 峰会以及加州大学技术大会（UC Tech Conference）上作为标杆试点项目斩获嘉奖。有教授反馈，AI 提供的深度洞察让他们获得了前所未有的创新教学策略，进而显著提升了课堂互动率和学生的深层次学习成果。
在行政管理与 IT 运营层面，UCLA 自身的 IT 团队积极行动，基于核心运维平台 ServiceNow 构建了超过 15 个定制化 GPT 应用。这些专用工具实现了工单的智能自动分类分流、加速了新员工入职配置流程，并大幅缩短了技术支持响应时间。阿维蒂西安感叹，AI 的介入让技术支持工作变得“更加具备人情味”（more human），因为它剔除了大量令人疲惫的重复性琐务，使团队能将精力投入到真正需要共情与深度沟通的复杂问题中，全团队对于“AI 驱动效能”形成了全新的认知习惯。
另一个备受师生喜爱的成果是 UCLA 职业发展中心（Career Center）打造的“Career AI”平台。该平台为学生提供 24/7 全天候定制化求职与生涯规划指导，成功打破了传统线下办公时间的刚性限制，且底层由学校官方背书的合规 AI 提供安全保障。与此同时，在医学教育与医疗健康等关键学术领域，各专业人员展现出极高的跨界热情，逐步形成了一个充满活力的全校性 AI 实践社群（Community of Practice）。最后，UCLA 继续教育部（UCLA Extension）也借助 AI 全面重塑其技术管理课程体系，使其与工业界前沿需求无缝接轨，不仅显著提升了学员满意度与就业成果，更为多学科快速更新课程架构探索出了可复制的通用模型。
### [12:53](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=773s) 运维与教学试点成效：从智能排障中心到扩展项目
UCLA 的早期 AI 实践已经在教学和 IT 运营两端取得了显著成效。在继续教育方面，工程类项目的招生规模超出了预期目标，学生反馈出更高的满意度，这一经过验证的可扩展教学模型目前正在向 UCLA Extension 的其他更多课程体系中推广复制。与教学端的突破相呼应，IT 运维团队也开展了极其实用的自主探索：团队成员基于过往积累的大量历史工单数据，搭建了一个交互式故障排查中心（Interactive Troubleshooting Hub），将庞杂的工单记录自动提炼并转化为标准化的分步操作指南。
这一举措虽然看似简单实用，却切实减少了技术团队的系统停机时间。在初期落地的成果中，不仅网络故障的响应与解决速度显著加快，技术文档的规范性与一致性大幅提升，现场 IT 工程师和技术支持人员的工作体验也得到了极大改善。
- **扩展项目成效**：工程项目招生超出预期指标，高满意度模型正向 UCLA Extension 其他学科铺开。
- **智能排障中枢**：将历史服务工单提炼为标准化操作手册，实现更快的网络故障恢复与文档统一。
---
### [13:39](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=819s) UCLA 2027 登月计划：全员具备 AI 素养与前沿技术集成
面向未来，UCLA 确立了面向 2027 年的宏大“登月计划”（Moonshot），其核心愿景是让每一位“Bruin”（UCLA 师生员工）都实现“AI 精通”（AI Fluent）。在校方看来，掌握 AI 已经不再是一个可有可无的选修选项，而是一项核心生存技能。学校致力于让每一个学科的每一名学生都具备面向未来的竞争力，同时赋能全体教职工：从课堂讲授到前沿实验室，教师们都将配备利用 AI 进行教学、开展科研和推动创新的全套能力。校方正紧密关注并积极探索 OpenAI 与教学管理系统 Canvas 的原生集成，以及 OpenAI 和 Google 近期相继推出的深度研究（Deep Research）能力在学术环境中的落地场景。
```mermaid
flowchart TD
accTitle: UCLA 2027 AI Moonshot Architecture
accDescr: UCLA 2027登月计划的四大支柱及其具体赋能举措
subgraph Strategy["2027 登月愿景 (AI Fluency)"]
direction TB
S1["学生端：跨学科面向未来"]
S2["教师端：教学与科研深度赋能"]
S3["员工端：视 AI 为协同队友"]
S4["底线端：坚守伦理与治理"]
end
subgraph TechOps["前沿技术与实践落地"]
direction TB
T1["Canvas 与 OpenAI 原生整合"]
T2["Google / OpenAI 深度研究能力"]
T3["代码生成工具优化开发流程"]
end
Strategy --> TechOps
```
在教职员工层面，UCLA 极力强调要将 AI 定位为“协同工作的队友，而非生存威胁（as a teammate, not as a threat）”。鉴于外界对于 AI 替代人类工作、引发失业潮的普遍恐惧，学校正抓紧引入和打磨一系列辅助工具栈，核心宗旨是赋能和提升员工的价值，而非取而代之。例如在 IT 与软件开发团队内部，他们正深入探索代码大模型（Codecs）等生成式代码工具的应用，借此重构软件开发生命周期中的时间分配与人力投入。
- **学生培养定位**：跨所有学科构建未来就业力，将 AI 视为核心基本功。
- **教学科研整合**：密切跟进 OpenAI 与 Canvas 系统的集成进展，引入大模型深度科研搜索能力。
- **员工赋能原则**：引入效率工具栈重塑开发与行政流程，坚定推行“提升人而非替代人”的方针。
---
### [15:06](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=906s) 伦理底线与治理框架：成立全校 AI 委员会
任何 AI 技术的应用都必须深深植根于伦理道德之中。UCLA 树立了“无诚信即无创新（No innovation without integrity）”的明确准则，坚决要求校园内落地的每一个 AI 解决方案都必须在公平性（Equity）、隐私保护（Privacy）以及问责机制（Accountability）上达到极高标准。尽管在技术日新月异的背景下维持这套严苛标准充满挑战，但学校依然将其定为不可妥协的底线。
为了将伦理原则转化为可执行的日常操作，学校建立了一套系统化的评估框架，用于严格审查第三方工具的安全合规性、底层数据的使用与留存方式，并精准识别潜在风险与应对预案。与此同时，UCLA 正在构建全校性的治理体系，正式启动跨部门的“全校 AI 委员会”（Campuswide AI Council），从制度层面上确保全校所有 AI 项目在推进过程中始终将数据隐私与算法公平视为不可逾越的红线。
- **核心准则**：坚持“无诚信即无创新”，确保公平性、隐私权与问责制不可谈判。
- **风险与工具评估**：针对数据流向、工具合规性及潜在风险建立标准化审查流程。
- **顶层治理组织**：正式成立并启动全校 AI 委员会，统筹全校 AI 战略与安全治理。
---
### [16:07](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=967s) 化解职场焦虑：以文化投资、素养培训共创未来
AI 对传统岗位形态的冲击确实在组织内部引发了一定程度的焦虑。为此，UCLA 参考了 Gartner 的发展路线图，将其作为未来数月内评估 AI 对具体岗位影响、推动劳动力队伍及工作模式渐进式演变的重要参考路径。学校深知，消除恐惧的最佳方式就是大力投资组织文化建设、普及技术素养并提供安全的探索空间。学校正在面向全体教职工全面推出 AI 素养培训课程，鼓励每个人主动思考并探索如何借助这些先进工具来改进、重构并进化自身的工作内容。
演讲最后引用了经典名言：“预测未来的最好方式就是去创造它（The best way to predict the future is to invent it）。”在高等教育的历史转折点上，UCLA 不仅是在被动预测趋势，更是在主动构建心目中理想的高等教育未来。面对在场的全行业领导者，主讲人抛出最终思考：“为了释放 AI 在教育领域的未来潜力，你们将采取怎样的大胆举措？”每一位参与者的学术研究、领导力与创新创造，都将共同塑造高等教育的全新篇章。
- **化解岗位焦虑**：借助 Gartner 框架科学评估工作形态重塑，稳步推进团队技能转型。
- **全员素养建设**：面向全体教职员工提供系统化的 AI Literacy 培训，提供试错容错的探索环境。
- **行动倡议**：呼吁全行业领导者以大胆行动与负责任的治理，共同谱写 AI 赋能高等教育的未来。
## Notable quotes
> [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) 如何在坚持大学核心价值观的同时，利用 AI 释放高等教育中人的潜能？ — Lucy Avetisyan
> [00:04](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=4s) 这不是一个遥不可及、只能被动等待的未来，而是 UCLA 师生正在共同生活和亲手构建的现实。 — Lucy Avetisyan
> [01:40](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=100s) 56% 的美国青少年认为，获得切实的在职工作经验比拿到大学学位更有价值。 — Lucy Avetisyan
> [01:40](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=100s) 87% 的学生已经在使用 AI 辅助完成学业，90% 的学生利用 AI 管理个人生活，平均每周与 AI 交互或导航的时间长达约 10 个小时。 — Lucy Avetisyan
> [03:41](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=221s) 创新绝不应仅局限于 IT 部门内部 — Lucy Avetisyan
> [09:26](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=566s) AI 的介入让技术支持工作变得“更加具备人情味”（more human），因为它剔除了大量令人疲惫的重复性琐务，使团队能将精力投入到真正需要共情与深度沟通的复杂问题中 — Lucy Avetisyan
> [13:39](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=819s) 协同工作的队友，而非生存威胁（as a teammate, not as a threat） — Lucy Avetisyan
> [15:06](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=906s) 无诚信即无创新（No innovation without integrity） — Lucy Avetisyan
> [16:07](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=967s) 预测未来的最好方式就是去创造它（The best way to predict the future is to invent it） — Lucy Avetisyan
> [16:07](https://www.youtube.com/watch?v=Tw-4IzASCbA&t=967s) 为了释放 AI 在教育领域的未来潜力，你们将采取怎样的大胆举措？ — Lucy Avetisyan
## Mentioned
Lucy Avetisyan, UCLA（加州大学洛杉矶分校）, Chris Mattman, NASA（美国国家航空航天局）, JPL（喷气推进实验室）, DOT（美国交通部）, Google, Microsoft（微软）, OpenAI, ChatGPT Enterprise, Palantir, Gecko, ServiceNow, Canvas, Gartner, InstructureCon, UC Tech Conference, UCLA Extension
## Video description
Lucy Avetisyan, CIO, UCLA
Abstracts
The talk will explore how AI is accelerating a profound transformation across higher education, presenting both disruption and unprecedented opportunity. The session will share strategic insights, leadership lessons, and critical observations from navigating this fast-evolving landscape. The talk will illustrate how AI is reshaping academic innovation, operational priorities, and institutional decision-making in real time. Attendees will gain a forward-looking perspective on how to lead with clarity, purpose, and agility in the face of rapid change. This session is designed for leaders who are ready to move beyond experimentation and begin actively shaping the AI-enabled future of higher education.
[Source](https://www.youtube.com/watch?v=Tw-4IzASCbA)
Source quotes
[0:04] Lucy Avetisyan: 如何在坚持大学核心价值观的同时，利用 AI 释放高等教育中人的潜能？
[0:04] Lucy Avetisyan: 这不是一个遥不可及、只能被动等待的未来，而是 UCLA 师生正在共同生活和亲手构建的现实。
[1:40] Lucy Avetisyan: 56% 的美国青少年认为，获得切实的在职工作经验比拿到大学学位更有价值。
[1:40] Lucy Avetisyan: 87% 的学生已经在使用 AI 辅助完成学业，90% 的学生利用 AI 管理个人生活，平均每周与 AI 交互或导航的时间长达约 10 个小时。
[3:41] Lucy Avetisyan: 创新绝不应仅局限于 IT 部门内部
[9:26] Lucy Avetisyan: AI 的介入让技术支持工作变得“更加具备人情味”（more human），因为它剔除了大量令人疲惫的重复性琐务，使团队能将精力投入到真正需要共情与深度沟通的复杂问题中
[13:39] Lucy Avetisyan: 协同工作的队友，而非生存威胁（as a teammate, not as a threat）
[15:06] Lucy Avetisyan: 无诚信即无创新（No innovation without integrity）
[16:07] Lucy Avetisyan: 预测未来的最好方式就是去创造它（The best way to predict the future is to invent it）
[16:07] Lucy Avetisyan: 为了释放 AI 在教育领域的未来潜力，你们将采取怎样的大胆举措？
Source quotes
[0:04] Lucy Avetisyan: This isn't the future we're waiting for. This is the one we're living and building together.
[13:39] Lucy Avetisyan: The best way to predict the future is to invent it.
Original transcript
[0:04] Okay. Um, how many of you are
[0:07] technologists? Because this is not a
[0:10] hardcore tech conversation. It's really
[0:12] about AI and higher education. There are
[0:15] elements of that, but we'll we'll get to
[0:16] that. Well, um,
[0:20] good morning. It's a pleasure to be here
[0:22] surrounded by innovators and change
[0:25] makers. Um, at UCLA we've been asking
[0:28] how can AI unlock human potential in
[0:32] higher education while staying true to
[0:35] our values, right? That's very important
[0:37] to us, especially now.
[0:40] Over the next 20 minutes, um, I'll share
[0:43] our journey, our lessons learned, and
[0:45] what's next for our institution.
[0:50] Oh, I don't know where the clicker is.
[0:55] There it goes.
[0:57] Thank you.
[1:00] Okay.
[1:02] So, close your eyes for a moment and
[1:04] imagine a campus where every learner's
[1:08] path is shaped by real time insights.
[1:12] Where AI doesn't replace connection, it
[1:16] deepens it. where the student experience
[1:20] is more personal, it's equitable and
[1:23] empowering than ever before.
[1:27] This isn't the future we're waiting for
[1:29] as you know it. This is the one we're,
[1:31] you know, living and building together.
[1:37] Um,
[1:40] we have to be honest um with ourselves.
[1:44] Higher education is under tremendous
[1:46] pressure. my institution especially, I'm
[1:48] sure you've seen the news.
[1:51] There are funding challenges, there are
[1:53] aging infrastructure concerns, there are
[1:55] rising costs, and perhaps the most
[1:58] important, our students expectations and
[2:02] their perceptions of higher education
[2:04] are shifting very quickly.
[2:06] We have to adapt and not react. We want
[2:10] to remain relevant.
[2:13] This survey sites that 56% of US teens
[2:18] say um they believe that realw world on
[2:22] the job experience is more beneficial
[2:24] than obtaining a college degree.
[2:28] Only one in seven provosts say their
[2:32] institution has reviewed curriculum to
[2:34] ensure it will be preparing students for
[2:37] the rise of AI in the workforce.
[2:41] The operating costs for US colleges and
[2:44] universities have increased by 3.4% just
[2:48] in 2024.
[2:52] The reality is that 87% of our students
[2:56] use AI for their schoolwork,
[2:59] 90% for their personal life management,
[3:03] and on average they spend about 10 hours
[3:05] a week navigating or interfacing with
[3:08] AI.
[3:10] Yet more than half feel lack guidance.
[3:14] 62% believe that understanding
[3:17] responsible AI use is critical to their
[3:20] future careers.
[3:22] This is our opportunity to lead with
[3:24] clarity, ethics, and empowerment to
[3:28] ensure that our graduates are ready to
[3:30] enter the workforce that will require
[3:33] them to coexist with AI.
[3:36] That's a lot of change for our
[3:37] institutions.
[3:41] We chose
[3:43] uh to move forward decisively and
[3:46] appointed it appointed UCLA's first
[3:48] chief data and AI officer. This was I
[3:52] believe one of the first in higher
[3:53] education. And this individual uh
[3:55] actually our CDIO Chris Mattman joined
[3:59] us uh about a year ago. Um he's part of
[4:02] my leadership team. He joined us from
[4:04] NASA JPL
[4:07] where he was um the chief technology
[4:10] innovation officer.
[4:12] In the chief data and AI techn AI um
[4:16] officer role, Chris is collaborating
[4:18] with key stakeholders both internal to
[4:21] my organization as and campuswide to
[4:24] co-create the strategy and roadmap for
[4:27] data and AI innovations campuswide. He's
[4:31] playing a crucial role in identifying
[4:33] and leveraging opportunities for
[4:35] advanced data analytics and AI across
[4:38] the campus community. And he leads and
[4:41] serves on several AI governance groups
[4:43] for the UN University of California
[4:45] system and UCLA.
[4:47] Um we believed that AI is going to be
[4:51] everywhere. This individual doesn't have
[4:53] a big team, doesn't have a big
[4:55] portfolio. His role is to uh understand
[4:59] our opportunities and bring the campus
[5:01] together as we co-create our roadmap.
[5:04] We introduced a dedicated AI site
[5:07] outlining our guiding principles for
[5:09] responsible use, showcasing available AI
[5:11] tools and promoting events and training
[5:13] opportunities for our campus
[5:15] stakeholders and then led an AI
[5:17] innovation initiative to spark
[5:19] creativity campuswide and pilot new
[5:21] solutions. Um, as the CIO for the
[5:24] campus, I believe that innovation
[5:26] shouldn't just come from my IT team. We
[5:29] brought in all our partners to be part
[5:30] of this or those who were interested.
[5:34] The next item, we have launched an AI
[5:36] learning hub offering self-guided
[5:38] education for our staff and faculty. We
[5:41] have piloted this opportunity within my
[5:44] organization. Um, in fact, we have made
[5:46] this offering a mandatory professional
[5:49] development goal for all of my
[5:51] technologists and are now preparing to
[5:54] scale it for our uh faculty and staff.
[5:57] And we're pursuing collaborations with
[5:59] campus partners and AI vendors such as
[6:02] Google, Microsoft, OpenAI, exciting
[6:04] projects with Palunteer as well as
[6:06] Gecko. Uh, some of you I believe are in
[6:09] the same um in the same boat. Um we are
[6:14] also uh focused on strengthening
[6:16] infrastructure to accelerate AIdriven
[6:18] innovation as we have onboarded numerous
[6:20] AI researchers to UCLA just in the
[6:23] recent year.
[6:26] So in fall of last year we launched a
[6:29] campuswide pilot of open AI Chad GPT
[6:32] enterprise. This initiative was designed
[6:35] to um explore the potential of
[6:38] generative AI in enhancing teaching,
[6:41] research, and administrative operations.
[6:44] It was more than just a technology
[6:46] rollout. The campuswide pilot serves as
[6:48] a strategic test bed helping UCLA shape
[6:52] the universitywide approach for AI uh
[6:55] that emphasizes responsibil
[6:57] responsibility, governance, literacy,
[7:00] and scalable innovation.
[7:03] This reflects our commitment to
[7:05] collaboration and forward thinking as we
[7:07] integrate AI into the fabric of our
[7:09] institution.
[7:11] We're still in the process of closing
[7:13] some of the projects and documenting the
[7:15] outcomes and the learnings. Uh but I'm
[7:18] very excited to share some of those
[7:20] examples with you today and also to
[7:23] mention that um our projects um uh smart
[7:27] city planning and wildlife management
[7:30] just earned UCLA's um earned UCLA NASA
[7:34] and department of transportation grants.
[7:35] So these are already coming into an
[7:38] exciting um version. It's a reminder for
[7:42] us um that higher reds innovation can
[7:45] drive impact well beyond our walls and
[7:48] uh we're excited to share that. So
[7:51] here's what happened. Uh when we
[7:53] announced um the uh kind of pilot
[7:56] project campuswide, we received 74
[7:59] actual quite lengthy proposals um of
[8:02] different individuals telling us how
[8:04] they wanted to leverage these enterprise
[8:06] licenses and and um try something out.
[8:10] We received 74 proposals selected 68
[8:13] across 27 different departments. These
[8:16] projects were targeted three strategic
[8:18] areas for us. So enhancing learning,
[8:21] boosting effectiveness and activating
[8:24] AIdriven research. 46 of these projects
[8:28] are now complete with tangible outcomes
[8:31] and shared lessons.
[8:33] Here are some of the key uh themes
[8:37] related to the proposals we received. Um
[8:41] beyond the technology, I just want to
[8:43] stress that our initiative is grounded
[8:45] in four pillars. innovation by fostering
[8:48] a c a culture of prototyping campuswide
[8:51] collaboration through crossf functional
[8:55] engagement capacity be building to
[8:58] promote AI fluency um on our campus and
[9:01] community development uh which supported
[9:04] uh responsible and ethical use of these
[9:06] AI tools.
[9:08] Um, ultimately this reflects our
[9:10] commitment to using AI not just as a
[9:12] tool but possibly a strategic enabler
[9:15] for impact in education research and
[9:17] beyond, especially in the times we're
[9:20] all challenged in higher education and
[9:22] navigating significant um um issues. One
[9:26] of uh my favorite stories
[9:29] um one of the teams used AI to transform
[9:32] how we gather and analyze instructor
[9:35] feedback. that was once a very um
[9:38] cumbersome, manual and uh slow process
[9:41] and which is now very rapid scalable
[9:44] freeing our faculty to focus on
[9:46] innovation in their teaching. This was
[9:50] recognized at instruure con uh la this
[9:53] year at and and also at UC University of
[9:56] California technology conferences um as
[9:59] an exciting pilot project.
[10:02] Um I also want to share with you that um
[10:06] we heard many of our customers share
[10:08] their thoughts and their
[10:09] recommendations. This one I wanted to
[10:11] share um faculty members have gained
[10:14] insights into innovative teaching
[10:16] strategies that leverage technology
[10:18] enhanced learning resulting in improved
[10:20] student engagement and deeper learning
[10:22] outcomes. This was so exciting for me to
[10:25] see. So I just wanted to share that with
[10:27] you. Um the next one I wanted to
[10:30] highlight was um what our IT team did.
[10:33] So our IT teams also embraced this
[10:36] opportunity and they built 15 plus
[10:38] custom GPTs for service now which is our
[10:41] IT service management platform. Um and
[10:44] um they were able to automate uh ticket
[10:47] triage uh streamlining onboarding and
[10:50] also uh cutting turnaround times.
[10:54] Um so to to us it's a proof AI can make
[10:59] work more h uh kind of make work our the
[11:02] work that my team does more human by
[11:05] removing those repetitive tasks that are
[11:08] very very timeconuming.
[11:10] The key outcomes here included faster
[11:12] more consistent ticket routing reducing
[11:14] manual workloads and turnaround times.
[11:17] uh the onboarding and collaboration was
[11:19] certainly improved and new mindset
[11:21] around AI powered efficiency.
[11:25] The other example was UCLA's career
[11:28] center um actually created career AI
[11:31] which offers 247 personalized career
[11:33] guidance. Uh the key outcomes they were
[11:36] able to expand access to career uh
[11:39] guidance beyond business hours which was
[11:42] key for us using um UCLA backed AI tool.
[11:46] Um obviously positive reception from
[11:48] students, staff and faculty. Um early
[11:51] usage insights are shaping the future
[11:53] enhancements that this team is committed
[11:55] to explore.
[11:57] Here's another quote. So we also heard
[11:59] that um the community is interested in
[12:02] ongoing discussions and learning from
[12:04] each other as we navigate the rapid
[12:06] changing landscape of AI tools and
[12:09] applications in medical education and
[12:11] healthcare. So what's very um exciting
[12:16] rewarding is now we have a vibrant
[12:18] community of practice of AI
[12:20] practitioners who are actively
[12:23] collaborating campuswide in different
[12:25] disciplines and different academic units
[12:27] to help one another as we explore these
[12:30] opportunities.
[12:33] Um I believe this is my last but UCLA
[12:35] extension um used AI to realign its
[12:39] technical management program with
[12:40] industry needs. uh the result. So
[12:43] there's higher satisfaction, stronger
[12:46] career outcomes and scalable models that
[12:49] can serve any field. So um new systems
[12:53] uh engineering program exceeded
[12:54] enrollment targets. Students reported
[12:56] higher satisfaction and scalable model
[12:59] now expanding to other um UCLA extension
[13:03] programs.
[13:05] Um, we had also um a a group of my team
[13:09] members who explored piloting an
[13:11] interactive troubleshooting hub, turning
[13:13] past support tickets into steps
[13:15] step-by-step guide guides, excuse me.
[13:18] It's very simple, practical, and it's
[13:21] reduced downtime for our teams. Um some
[13:25] outcomes in the early stage uh faster
[13:28] network issue resolution uh more
[13:30] consistent documentation
[13:33] and uh improved support for IT engineers
[13:36] and techs.
[13:39] So I want to talk about our moonshot for
[13:43] 2027.
[13:45] Um we hope that every brein is AI fluent
[13:48] by then. What do I mean? AI isn't
[13:51] optional. It's a core skill. Every
[13:54] student, every discipline is featur
[13:56] future ready. Every faculty member is AI
[14:00] enabled from lectures to labs. Um
[14:04] faculty are equipped to teach, conduct,
[14:07] research, and innovate with AI. We're
[14:09] very closely exploring opportunities
[14:11] that will be present with the OpenAI and
[14:14] Canvas integration uh that was announced
[14:16] a couple weeks ago as well as the deep
[14:18] research capabilities that both Google
[14:21] and OpenAI have highlighted.
[14:24] Um every staff member is AI empowered um
[14:28] as a teammate, not as a as a threat. I
[14:31] think that's really important because as
[14:33] you know there's so much fear about
[14:34] people losing their jobs or being
[14:36] replaced by AI. Um we are hoping that we
[14:40] will introduce a stack of I mean we
[14:42] already are close to it to introduce um
[14:45] tool sets to elevate people and not
[14:48] replace them. So uh spending a lot of
[14:50] time on that. Uh for my team uh we're
[14:54] looking into capabilities with codecs um
[14:57] and how can really you know rethink the
[15:00] time and the effort that's uh been spent
[15:02] on on our development.
[15:06] every use case rooted in ethics and I'll
[15:08] say a little more about this um this
[15:11] been this has been um a very important
[15:15] uh a very focused effort for us no
[15:18] innovation without integrity every AI
[15:20] solution meets the bar for equity
[15:22] privacy and accountability and we're
[15:24] trying to stay very close to that
[15:26] although it's challenging uh this is the
[15:28] standard we're setting for ourselves
[15:33] um as it relates to
[15:36] ethical considerations. We can't talk
[15:39] about AI without talking about ethics.
[15:41] So, we have established a framework for
[15:43] evaluating tools, how our data is being
[15:46] used, and uh what are the risks that we
[15:48] need to be um mindful of and know how to
[15:51] mitigate. We've built a governance
[15:53] framework, launching a campuswide AI
[15:55] council, which is kicking off later this
[15:58] month, and made equity, privacy, and
[16:00] accountability a non-negotiable for our
[16:02] initiatives.
[16:05] Um,
[16:07] okay. We also recognize that AI will
[16:10] change jobs and that create anxiety. Uh,
[16:14] I'm sharing this gardener road map as it
[16:16] is a helpful approach uh we may want to
[16:19] take in the coming months to explore how
[16:22] AI can impact the jobs and how does that
[16:25] evolve our workforce and the work that
[16:27] they do.
[16:29] Um,
[16:30] it's very important to us to invest in
[16:33] our culture, in literacy, and in safe
[16:36] exploration. But we also want to be
[16:38] thinking about these kinds of things. We
[16:40] want our people to see AI as a teammate
[16:43] and not a threat. And this is why we are
[16:46] offering AI literacy courses to all our
[16:49] faculty, to all our staff, and
[16:51] encouraging them to think about how
[16:52] their jobs could evolve using these tool
[16:55] sets. um improve and evolve. Um let's
[17:00] see. Okay. Uh the best way to predict
[17:04] the future is to invent it. And at UCLA,
[17:07] we're not just predicting, we're hoping
[17:09] um to build it. Um that the the future
[17:13] that we want to see in our institution.
[17:16] So, I leave you with this. um what bold
[17:22] step will you take to unlock AI's future
[17:24] potential in education? Um I think your
[17:27] research, your leadership, your uh
[17:30] creativity, it all matters in shaping AI
[17:33] and higher education. So I hope we can
[17:36] continue this conversation because uh
[17:38] the AI future is ours to shape together.
[17:41] Thank you. And um
[17:45] um
[17:48] there's a lot more information about the
[17:50] work that we're doing and the
[17:51] information we're sharing and the
[17:52] governance model and all that in via
[17:55] that link. So hopefully we'll stay
[17:57] connected. Thank you again.
