American University Overhauls Curriculum as AI Breaks Entry-Level Jobs

Reimagining Higher Education with AI: Kogod’s Journey Towards an AI-Integrated Curriculum With AU — Ai4

Ai4

Because artificial intelligence is eliminating entry-level corporate tasks, business schools must rapidly embed universal AI fluency and human-centric skills across all coursework to keep graduates employable.

AI-assisted summary of Reimagining Higher Education with AI: Kogod’s Journey Towards an AI-Integrated Curriculum With AU — original source. Check the original for full context.

Source published: 2025-08-29

Detailed notes

## Background Published on YouTube by the Ai4 channel on August 29, 2025, this presentation features Gwanhoo Lee, Director of the Institute for Applied AI and Professor at American University's Kogod School of Business. The talk outlines Kogod's comprehensive roadmap for embedding artificial intelligence across higher education curricula, aligning student learning outcomes with workforce shifts, and transforming university operations.

## TL;DR Addressing the reality that entry-level career ladders are fracturing, Gwanhoo Lee shares how American University's Kogod School of Business executed an aggressive, school-wide AI transformation. The strategy combines top-down executive support with bottom-up faculty engagement, rolling out a four-year scaffolded undergraduate model, specialized AI degree tracks, and clear course designations. Beyond technical fluency, the curriculum emphasizes deeply human skills, entrepreneurial agility, and standardized usage accountability while integrating AI directly into campus operations. Ultimately, Lee distills practical lessons for academic leaders, stressing speed over perfection to ensure universities lead rather than fall behind.

## Atmosphere & style The presentation carries an energetic, pragmatic, and candid tone, marked by honest admissions about institutional improvisation and trial-and-error rather than pretending to possess an effortless blueprint. Lee balances sobering workforce statistics and corporate insights with lighthearted anecdotes, creating an engaging and relatable dynamic with the audience. The talk feels like an inspiring yet grounded dispatch from the front lines of academic reform, building toward an urgent, stirring call for institutional leadership.

## Key takeaways - [00:04](https://www.youtube.com/watch?v=acMYFQaK_R4&t=4s) Institutional AI transformation in higher education requires continuous experimentation, adaptation, and improvisation rather than waiting for a perfect blueprint. - [01:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=70s) With 86% of students already using AI and entry-level career rungs breaking, universities must shift from training for traditional junior tasks to developing advanced AI fluency and human adaptability. - [04:00](https://www.youtube.com/watch?v=acMYFQaK_R4&t=240s) Achieving faculty buy-in relies on a combination of top-down support, bottom-up community forums like 'Second Friday' with over 70% voluntary attendance, and immersive industry visits to AI leaders. - [06:36](https://www.youtube.com/watch?v=acMYFQaK_R4&t=396s) Academia faces severe hiring and retention competition against tech industry compensation, requiring a recruitment focus on mission-driven scholars. - [07:20](https://www.youtube.com/watch?v=acMYFQaK_R4&t=440s) Kogod implemented a four-year scaffolding curriculum spanning Year 1 literacy and ethics, Year 2 functional business AI, Year 3 domain-specific applications, and Year 4 capstone practicums. - [09:54](https://www.youtube.com/watch?v=acMYFQaK_R4&t=594s) Courses are categorized into 'Sage' (>50% AI content) and 'Artisan' (light-touch) integrations, utilizing custom tools like Perplexity Spaces across dozens of sections. - [12:43](https://www.youtube.com/watch?v=acMYFQaK_R4&t=763s) A mandatory two-step disclosure policy requires students to document specific AI tool usage and explicitly state their own human intellectual contributions. - [13:33](https://www.youtube.com/watch?v=acMYFQaK_R4&t=813s) The educational framework for the AI economy is anchored on three pillars: universal AI fluency, deeply human skills (empathy, leadership, integrity), and an entrepreneurial mindset. - [15:07](https://www.youtube.com/watch?v=acMYFQaK_R4&t=907s) Student AI competency is benchmarked against the Digital Education Council's 5-level framework, moving from foundational understanding to domain-specific real-world applications. - [17:20](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1040s) Universities should deploy AI across internal operations, such as admissions chatbots, research translation, PR drafting, and advising, to mirror curricular innovation. - [17:20](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1040s) American University established the Institute for Applied Artificial Intelligence with over 30 faculty members to coordinate campus-wide research and education initiatives. - [19:18](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1158s) Key lessons for university leaders include ensuring executive backing, prioritizing speed over perfection, fostering community engagement, and leveraging external recognition to sustain momentum.

## Detailed walkthrough ### [00:04](https://www.youtube.com/watch?v=acMYFQaK_R4&t=4s) Navigating Higher Education’s AI Disruption at Kogod

Gwanhoo Lee opens his address at the Ai4 conference by welcoming the audience and expressing his gratitude to those who stayed until the final sessions. He introduces an inside look at how the Kogod School of Business at American University in Washington, DC has been actively navigating artificial intelligence—what he frames as one of the most profound disruptions in the history of higher education. Rather than claiming to possess a magic bullet, Lee candidly admits that Kogod’s transformation has been defined by continuous experimentation, trial and error, adaptation, and on-the-fly improvisation.

Despite the unvarnished realities of building the playbook as they go, the school has made bold strategic choices. Lee emphasizes that the lessons and practical insights gathered along the way offer a valuable blueprint for other academic institutions grappling with similar challenges. He sets out to share these hard-won stories in hopes of helping peers accelerate their own institutional strategies.

- **Institution:** Kogod School of Business at American University (Washington, DC). - **Core Philosophy:** Embracing experimentation, trial and error, and improvisation over waiting for a perfect blueprint. - **Key Quote:** "I will not pretend that we have discovered perfect answer for this... In fact, much of our AI journey has involved experimentation, trial and error, adaptation and improvisation to be honest."

---

[01:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=70s) The Reality of AI in Academia and the Breaking Career Ladder

Lee points out that while saying "AI will change everything" has become a cliché, its truth is undeniable. He surveys the room, asking how many audience members begin their mornings talking to AI rather than humans or find themselves relying on AI for an increasing number of daily tasks. Turning to academia, he acknowledges a well-known vulnerability: traditional universities are notoriously slow to adapt when the world shifts rapidly around them. To avoid being left behind, Kogod made a conscious decision to be proactive and actively reimagine higher education for an AI-driven era.

The urgency is underscored by stark data and shifting workforce dynamics. A 2024 survey revealed that 86% of higher education students are already utilizing AI in their studies, proving that whether faculty welcome it or not, AI is already in the classroom. Furthermore, Lee references an op-ed in *The New York Times* written by a senior executive at LinkedIn, which warned that "the bottom rung of the career ladder is breaking." Because AI is rapidly absorbing entry-level tasks, universities can no longer train students for traditional entry-level jobs; they must instead equip them with high-level AI fluency, practical skills, deeply human capabilities, and adaptability so they can step directly into more complex roles.

- **Student AI Adoption Rate:** 86% of higher education students surveyed in 2024 actively use AI in their studies. - **Workforce Shift:** Entry-level positions are rapidly disappearing as AI capabilities expand, breaking the traditional career ladder. - **Stakeholder Perspectives Shared:** - *Venture Capital CEO:* "AI won't take your job, but someone who knows AI could take your job if you don't know AI." - *Young Alumna:* "AI is doing what I did at 22 as a first-year financial analyst." - *Advisory Board Member:* "Run, do not walk. You cannot afford to walk. We have to run."

---

[04:00](https://www.youtube.com/watch?v=acMYFQaK_R4&t=240s) Winning Over Faculty: Two-Pronged Engagement and the Silicon Valley Reality Check

Integrating AI across an academic curriculum is impossible without genuine faculty buy-in. Kogod adopted a two-pronged strategy combining top-down vision and resources from leadership with bottom-up engagement that listens closely to faculty concerns. To build momentum, the school brought in high-profile industry leaders to spark curiosity and urgency, formed a dedicated faculty committee to keep academic voices at the center of policy decisions, and conducted surveys to pinpoint specific barriers to adoption. They also appointed one of their youngest faculty members as an AI Instructional Faculty Fellow to serve as an accessible, go-to peer resource.

To maintain continuous dialogue, Kogod launched "Second Friday," a monthly online knowledge-sharing forum held every second Friday at 9:00 a.m. In this voluntary space, faculty present best practices, exchange pedagogical ideas, and voice real frustrations. To leadership's surprise, over 70% of full-time faculty have regularly attended these sessions—even throughout the summer break. Additionally, in January, deans and select faculty embarked on an immersive trip to Silicon Valley and the Bay Area, visiting OpenAI, Google, Perplexity, and other tech leaders. Seeing cutting-edge developments firsthand inside AI companies proved to be the ultimate catalyst, converting even the most skeptical academics into enthusiastic champions of AI integration.

```mermaid accTitle: Faculty Engagement Strategy Architecture flowchart TD subgraph TopDown ["Leadership Support (Top-Down)"] A["Vision & Direction"] B["Resource Allocation"] C["Industry Leaders & Advisory"] end

subgraph BottomUp ["Faculty Engagement (Bottom-Up)"] D["AI Instructional Faculty Fellow"] E["Second Friday Monthly Forum (70%+ Attendance)"] F["Faculty AI Committee & Surveys"] end

subgraph Immersive ["Silicon Valley Field Study"] G["Visits to OpenAI, Google & Perplexity"] end

TopDown --> H["Curriculum Transformation"] BottomUp --> H Immersive --> H ```

- **Second Friday Forum:** Monthly 9:00 a.m. virtual session achieving over 70% voluntary full-time faculty attendance, even during summer months. - **Faculty Leadership:** Appointment of a junior faculty member as the AI Instructional Faculty Fellow to provide peer-to-peer technical and pedagogical support. - **Industry Excursions:** January site visits to OpenAI, Google, and Perplexity in the Bay Area to expose faculty to state-of-the-art developments. - **Key Quote:** "Nothing convinces a skeptical academic faster than seeing firsthand what's happening inside AI companies."

---

[06:36](https://www.youtube.com/watch?v=acMYFQaK_R4&t=396s) Recruiting Talent in a Hyper-Competitive Market

To support this ambitious transformation, Kogod actively invested in faculty talent specializing in AI and machine learning. However, Lee shares the harsh reality of competing against tech giants for top-tier expertise. Academia simply cannot match the compensation packages offered by major technology firms. Illustrating this challenge with a touch of humor, Lee reveals that one of their newly hired AI faculty members left the university after just a single semester to launch an AI startup.

Despite these recruitment hurdles, Kogod remains committed to scouting individuals who value the broader societal mission and educational impact of academia. Through persistent efforts, the school has successfully onboarded key talent dedicated to shaping the next generation of business leaders.

- **Recruitment Reality:** Higher education faces extreme competition from tech giants with vast financial resources. - **Retention Challenge:** A recent faculty hire departed after just one semester to found an AI startup. - **Strategic Focus:** Targeting scholars and practitioners who prioritize the mission, teaching, and societal impact of higher education.

---

[07:20](https://www.youtube.com/watch?v=acMYFQaK_R4&t=440s) A Scaffolding Model for AI Integration Across the Curriculum

By the fall semester, Kogod stands as one of the first business schools in the United States to offer a comprehensive suite of specialized AI credentials: an undergraduate AI major, an undergraduate AI minor, a Master’s in Business Analytics and AI, and a dedicated AI STEM track. Beyond rolling out specialized degree paths, the overarching strategy focuses on embedding AI systematically into every level of the standard curriculum.

For undergraduate students, the learning journey is carefully scaffolded across four years. First-year students build foundational AI literacy while learning responsible and ethical usage. Second-year students apply AI tools across core business functions including accounting, finance, marketing, operations, and HR. Third-year students take a deep dive into domain-specific applications—such as environmental monitoring in sustainability, predictive modeling in finance, automated auditing in accounting, or big data analytics. In their senior year, everything culminates in an AI-infused practicum project where students solve real-world industry problems using the full spectrum of AI tools learned throughout their degree. A similar model applies to graduate students, beginning at orientation with core AI concepts and ethics before advancing into discipline-specific master's coursework.

```mermaid accTitle: Four-Year Undergraduate AI Learning Scaffolding flowchart LR subgraph Year1 ["Year 1: Foundation"] Y1["AI Literacy & Ethics"] end

subgraph Year2 ["Year 2: Core Functions"] Y2["Functional Business AI\n(Accounting, Finance, Marketing, HR)"] end

subgraph Year3 ["Year 3: Domain Mastery"] Y3["Specialized Applications\n(Audit Automation, Predictive Finance)"] end

subgraph Year4 ["Year 4: Synthesis"] Y4["AI-Infused Practicum\n(Real-World Problem Solving)"] end

Y1 --> Y2 --> Y3 --> Y4 ```

- **New Degree Offerings:** Undergraduate AI Major, Undergraduate AI Minor, Master's in Business Analytics & AI, and an AI STEM track. - **Undergraduate Scaffolding:** - *Year 1:* Basic literacy and ethical/responsible AI usage. - *Year 2:* Functional business integration (accounting, finance, marketing, operations, HR). - *Year 3:* Deep-dive domain applications (automated auditing, predictive financial modeling, marketing campaigns). - *Year 4:* Hands-on AI-infused practicum tackling real-world business problems.

---

[09:54](https://www.youtube.com/watch?v=acMYFQaK_R4&t=594s) Course Categorization, Classroom Adoption, and Interactive Tools

Kogod classifies its AI-integrated courses into two distinct categories: "Sage" courses, where over 50% of the content is explicitly AI-focused, and "Artisan" courses, which incorporate AI with a lighter, tailored touch. Currently, the school boasts 19 Sage and 39 Artisan courses (58 in total), all with explicitly defined AI learning outcomes. Course adoption has escalated rapidly: over 50% of classes incorporated AI in the spring semester, with adoption projected to reach 75% in the fall.

To provide customized academic support, 15 core courses spanning over 60 sections deployed Perplexity Spaces (similar to Google’s NotebookLM) during the spring semester to deliver class-specific AI assistance to students. Lee highlights innovative classroom implementations across disciplines: - **Negotiation:** Students use AI to simulate complex bargaining scenarios, build distinct negotiator personas, test tactics, and receive instant personalized feedback. - **Digital Marketing:** Group projects require students to craft complete marketing campaign portfolios using more than 10 distinct AI tools. - **Entrepreneurship:** A faculty member completely revamped his course by co-teaching alongside a custom-built AI assistant and creating curated prompt libraries for personalized student exploration.

---

[12:43](https://www.youtube.com/watch?v=acMYFQaK_R4&t=763s) Standardized Accountability: AI Usage Forms and Human Contribution

To maintain academic integrity and ensure students remain active thinkers rather than passive consumers, Kogod enforces a clear two-step disclosure policy for assignments involving AI. Whenever students utilize AI tools for coursework, they must submit a standardized school form detailing their usage alongside their final project.

First, students must specify the exact functional stage where AI was employed—whether for initial brainstorming, drafting, data visualization, quantitative analysis, presentation design, or proofreading. Second, and most crucially, students must explicitly document what *they as humans* contributed to the final deliverable. This requirement guarantees that AI acts as an accelerator for human effort rather than a complete replacement for critical thought.

- **Standardized AI Disclosure Form:** Required for any assignment where AI is utilized. - **Step 1 (Tool Mapping):** Categorizing AI use (brainstorming, drafting, data analysis, visualization, presentation, or proofreading). - **Step 2 (Human Audit):** Documenting explicit human contributions, edits, critical reasoning, and oversight. - **Core Objective:** Preventing AI-driven delegation and preserving student ownership of intellectual output.

---

[13:33](https://www.youtube.com/watch?v=acMYFQaK_R4&t=813s) The Three Pillars of Education for the AI Economy

Relying solely on technical AI skills is insufficient to prepare graduates for long-term career success. Citing private conversations with senior executives at LinkedIn, Lee reinforces that the most valuable assets in an AI-driven economy remain deeply human traits. In response, Kogod has structured its overarching student development framework around three core pillars, anchored by solid domain expertise:

1. **AI Fluency for Everyone:** Universal foundational competence in leveraging modern AI tools across disciplines. 2. **Deeply Human Skills:** Cultivating non-automated leadership traits, including empathy, communication, cross-functional coordination, and ethical integrity. 3. **Entrepreneurial Mindset:** Preparing every student—whether joining a multinational corporation or a three-person non-profit—to look beyond static job descriptions, identify novel opportunities, and drive proactive results.

Complementing these pillars, deep domain expertise remains essential; without specialized subject-matter knowledge, professionals cannot effectively evaluate, direct, or apply AI capabilities in meaningful ways.

- **Pillar 1:** Universal AI Fluency. - **Pillar 2:** Deeply Human Skills (empathy, leadership, communication, coordination, integrity). - **Pillar 3:** Entrepreneurial Mindset across all organizational scales. - **Foundation:** Core domain expertise required to harness and evaluate AI meaningfully.

---

[15:07](https://www.youtube.com/watch?v=acMYFQaK_R4&t=907s) A 5-Level Framework for AI Learning Outcomes

Kogod structured its AI learning outcomes hierarchically—starting at the course level, progressing to the program level, and culminating at the school level. For instance, in an advanced quantitative methods and machine learning course within the Finance Department, students learn key AI concepts, build predictive financial models, and perform natural language processing (NLP) on unstructured financial text.

At the broader undergraduate program level, Kogod adopted the 5-level framework established by the Digital Education Council to define student progression:

- **Level 1 (Foundational Understanding):** Grasps fundamental AI concepts, underlying algorithms, and related data processes. - **Level 2 (Critical Thinking & Judgment):** Systematically verifies AI data sources, evaluates competing model architectures, and selects the right model for specific business problems. - **Level 3 (Ethical & Responsible Use):** Identifies potential algorithmic bias, data inaccuracies, and discriminatory risks to ensure responsible deployment. - **Level 4 (Human Centricity & Collaboration):** Demonstrates effective collaboration between human teams and automated systems (such as AI agents), integrating human judgment with machine-generated insights. - **Level 5 (Domain-Specific Application):** Applies specialized, discipline-specific AI tools to solve complex, real-world business challenges.

---

[17:20](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1040s) Industry Partnerships, Operational AI, and The Institute for Applied AI

To support its ambitious academic roadmap, Kogod established strategic industry partnerships with major technology leaders. These collaborations provide students with enterprise access to tools like Perplexity Enterprise, co-develop novel methodologies with Google for assessing AI learning outcomes, and create joint educational programs.

To "practice what they preach," the business school aggressively embeds AI into its own administrative operations. Operational use cases include: - Deploying an AI admissions chatbot to answer prospective student and parent inquiries. - Automating the translation of complex faculty academic research into consumer-friendly blogs, social media posts, and video scripts. - Draft press releases and marketing articles for public relations. - Streamlining alumni fundraising, academic advising, internal policy navigation, and student event planning.

To unify these disparate initiatives, Kogod launched **The Institute for Applied Artificial Intelligence**, directed by Professor Gwanhoo Lee. Bringing together over 30 affiliated faculty members from across the entire American University campus, the Institute serves as a centralized hub to connect, coordinate, and amplify AI research and teaching across disciplines.

- **Key Corporate Partners:** Perplexity (enterprise tools) and Google (learning outcome assessment frameworks). - **Operational AI Implementations:** Admissions chatbots, research translation to media content, PR generation, fundraising support, and academic advising tools. - **The Institute for Applied AI:** Cross-disciplinary research and implementation hub directed by Gwanhoo Lee, uniting 30+ faculty members campus-wide.

---

[19:18](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1158s) External Validation and Strategic Takeaways for Higher Education

Kogod’s comprehensive approach has earned widespread external recognition. Leaders from Microsoft, OpenAI, and *Times Higher Education* have praised the initiative, while publication *Poets&Quants* remarked that Kogod has executed "the most consequential AI transformation in business education." Lee notes that while these accolades are humbling, their true value lies in boosting community confidence, attracting new industry partners, and sustaining momentum.

In closing, Lee distills Kogod’s journey into four critical lessons for university leaders, administrators, and industry policy makers:

1. **Executive Support is Essential:** Institutional transformation fails to take root without direct backing and resource commitments from senior leadership. 2. **Speed Over Perfection:** Waiting for a flawless, polished plan leads to paralysis. Institutions must move quickly, iterate, and refine as they go. 3. **Build an Engaged Community:** Connect faculty, students, and staff into collaborative learning networks to make the transition smoother and more engaging. 4. **Leverage External Validation:** External recognition validates internal efforts, builds momentum, and opens new partnership doors.

Lee leaves the audience with a final, stirring challenge: *"Are you AI ready? Not just your faculty or some students... but as an institution as a whole? If you don't lead this change, someone else will."*

- **Major Recognition:** Praised by OpenAI, Microsoft, *Times Higher Education*, and *Poets&Quants*. - **Key Takeaway 1:** Executive support is non-negotiable. - **Key Takeaway 2:** Bias for action—move fast rather than waiting for a perfect plan. - **Key Takeaway 3:** Foster community through inclusive forums and shared learning. - **Key Takeaway 4:** External validation fuels internal momentum and industry partnerships.

## Notable quotes > [00:04](https://www.youtube.com/watch?v=acMYFQaK_R4&t=4s) I will not pretend that we have discovered perfect answer for this... In fact, much of our AI journey has involved experimentation, trial and error, adaptation and improvisation to be honest. — Gwanhoo Lee

> [01:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=70s) the bottom rung of the career ladder is breaking. — Senior Executive at LinkedIn (via The New York Times)

> [01:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=70s) AI won't take your job, but someone who knows AI could take your job if you don't know AI. — Venture Capital CEO

> [01:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=70s) AI is doing what I did at 22 as a first-year financial analyst. — Young Alumna

> [01:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=70s) Run, do not walk. You cannot afford to walk. We have to run. — Advisory Board Member

> [04:00](https://www.youtube.com/watch?v=acMYFQaK_R4&t=240s) Nothing convinces a skeptical academic faster than seeing firsthand what's happening inside AI companies. — Gwanhoo Lee

> [19:18](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1158s) the most consequential AI transformation in business education. — Poets&Quants

> [19:18](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1158s) Are you AI ready? Not just your faculty or some students... but as an institution as a whole? If you don't lead this change, someone else will. — Gwanhoo Lee

## Mentioned Gwanhoo Lee, Kogod School of Business, American University, Institute for Applied Artificial Intelligence, Ai4, OpenAI, Google, Perplexity, Microsoft, LinkedIn, Digital Education Council, The New York Times, The Wall Street Journal, Axios, Poets&Quants, Times Higher Education, Perplexity Spaces, NotebookLM

## Video description Gwanhoo Lee, Director of the Institute of Applied AI and Professor of IT and Analytics, American University

Abstracts

Artificial intelligence is transforming the foundation of higher education. I will present a bold, practical vision for how universities can lead in this era by rethinking both teaching and learning. Drawing on my work as Director of the Institute for Applied Artificial Intelligence at American University’s Kogod School of Business, I will share our strategies for embedding AI across the curriculum, aligning learning outcomes with emerging technologies, and preparing students for careers shaped by AI. Our efforts have earned recognition from The Wall Street Journal, The New York Times, Axios, and Poets&Quants, and have been praised by industry leaders. I will provide actionable insights for academics, university administrators, industry leaders, and policymakers to drive AI-driven transformation in higher education.

[Source](https://www.youtube.com/watch?v=acMYFQaK_R4)

中文简报

AI冲击初级就业岗位，美利坚大学全面改革课程体系由于人工智能正在消除企业的初级工作任务，商学院必须迅速在所有课程中融入通用的AI素养与以人为本的技能，以保持毕业生的就业竞争力。面对初级职业阶梯正在断裂的现实，Gwanhoo Lee分享了美利坚大学Kogod商学院（Kogod School of Business）如何推行全院范围的果断AI转型。该战略结合了自上而下的管理层支持与自下而上的教职员工参与，推出了四年阶梯式本科培养模式、专门的AI学位方向以及明确的课程分类标识。除技术应用能力外，该课程体系在将AI直接融入校园运营的同时，还着重培养深层次的人文技能、创业敏捷性以及规范化的使用问责机制。最后，Lee为高校管理者提炼了实用经验，强调速度胜于完美，以确保大学走在时代前列而非落后于人。调查显示 86% 的高等教育学生已在学业中使用 AI，面对传统职业初级台阶被技术打破的现状，大学必须从训练传统初级任务转向培养深度 AI 素养与人类适应力。 (1:10) 美利坚大学 Kogod 商学院推行自上而下与自下而上相结合的教师赋能机制，其“第二个星期五”月度交流会吸引超 70% 的全职教师自愿参与，并组织硅谷实地考察走访 OpenAI 与 Google 等企业以凝聚共识。 (4:00) 学院建立了四年阶梯式本科 AI 培养体系，涵盖大一基础素养与伦理、大二商业核心功能应用、大三垂直领域深耕，以及大四的 AI 综合实战项目，并设立了多项本硕 AI 专业认证与学位。 (7:20) 针对学术诚信与自主思考，学院推行标准化的双步披露政策，要求学生在提交作业时列明具体的 AI 工具使用环节，并明确阐述自身的人类智力贡献。 (12:43) 面向 AI 时代的教育框架以三大支柱为核心：普及性 AI 素养、深度人文技能（同理心、领导力、沟通与道德操守）以及跨组织情境下的创业家思维。 (13:33)

Reading summary

Facing rapid workplace disruption and high student adoption, the Kogod School of Business at American University restructured its programs around an operational, multi-tiered artificial intelligence curriculum. Professor Gwanhoo Lee argues that universities must favor rapid experimentation over flawless planning to adapt before traditional entry-level career pathways disappear. Workforce Disruption and Academic Urgency (1:10) A 2024 survey cited by Lee indicated that 86% of higher education students already use AI in their coursework, establishing that technological adoption has outpaced traditional university curricula. Citing an op-ed by a LinkedIn executive, Lee warned that the bottom rung of the career ladder is breaking because AI rapidly absorbs entry-level work. Advisory voices echoed this shift, noting that entry-level analytical tasks are already handled by software. In response, business education must shift from preparing students for obsolete introductory tasks to training them for higher-order decision-making, ethical fluency, and adaptability. Faculty Alignment and Market Recruitment Hurdles (4:00) Curricular transformation required bridging top-down administrative support with bottom-up faculty engagement. Kogod established 'Second Friday,' a monthly online forum where over 70% of full-time faculty voluntarily met—even during summer breaks—to discuss pedagogical experiments and operational hurdles. To sway skeptics, leadership sent faculty and deans to Silicon Valley to visit OpenAI, Google, and Perplexity. Simultaneously, recruitment highlighted academia's structural limits: universities cannot match Big Tech salaries, a dynamic illustrated when a newly hired AI professor departed after a single semester to launch a startup. The school therefore targeted scholars focused specifically on educational and societal impact. Scaffolded Curricula and Measurable Course Standards (7:20) Kogod launched an undergraduate AI major and minor, an AI STEM track, and a Master's in Business Analytics and AI. For undergraduates, the learning pathway is scaffolded across four stages: first-year AI literacy and ethics, second-year functional integration across accounting and marketing, third-year specialized domain use like automated auditing and predictive modeling, and a fourth-year applied practicum solving real-world business problems. Graduate training follows an aligned trajectory beginning with orientation. Accountability, Classroom Tools, and Pedagogical Pillars (9:54) The school classifies offerings into 19 'Sage' courses (over 50% AI-focused content) and 39 lighter-touch 'Artisan' courses, with total course integration targeted to reach 75% in the fall semester. Classrooms deploy Perplexity Spaces across 15 core courses, alongside role-playing negotiation bots and prompt libraries. To enforce academic integrity without banning technology, students who use AI must submit a standardized disclosure identifying both the functional task delegated and the explicit human contribution made. This framework underpins three broader educational pillars: universal AI fluency, deeply human skills like empathy and ethical reasoning, and an entrepreneurial mindset grounded in domain expertise. Institutional Practice and Cross-Disciplinary Integration (17:20) Kogod embedded AI into its own administrative operations, employing tools for admissions chatbots, student event planning, fundraising, and summarizing faculty research into public communications. Strategic partnerships with Perplexity and Google provided enterprise access and assisted in designing learning outcome metrics. To centralize ongoing research and teaching across American University, the school formed the Institute for Applied Artificial Intelligence under Lee's direction, connecting more than 30 faculty members across diverse disciplines. While Kogod's strategy drew validation from industry leaders at Microsoft, OpenAI, and academic outlets, Lee emphasized that institutional change cannot wait for polished consensus. Higher education leaders must proceed through trial and error, as failure to proactively redesign programs risks leaving institutions and their graduates unprepared for an AI-altered economy.

精炼阅读摘要

美利坚大学科戈德商学院（Kogod School of Business）通过全方位试验与快速迭代，在全院范围内推行人工智能课程与运营整合，旨在应对传统初级职业阶梯断裂的挑战，并为高等教育转型提供一套可复制的实践范本。应对就业断层与普及现状 (1:10) Gwanhoo Lee 指出，2024 年的一项调查显示已有 86% 的高等教育学生在学业中使用 AI，表明该技术已不可逆转地进入课堂教学。与此同时，《纽约时报》刊载的 LinkedIn 高管评论警示“职业阶梯的最底层正在断裂”，因为自动化工具正迅速吸收传统初级岗位的基础工作任务。Lee 引述风投机构及年轻校友的观点强调，刚毕业的分析师传统工作正被技术取代，大学若继续按部就班培养基础技能将使学生面临被淘汰的风险。为此，高校必须转变定位，放弃等待完美方案的拖延模式，以行动和试验为导向，培养学生直接胜任更复杂职能所需的高阶 AI 素养、核心专业知识及不可替代的人性化能力。教师动员机制与人才吸纳壁垒 (4:00) 推进全院级教学变革的关键在于赢得教学人员的深度支持。科戈德商学院采取了自上而下的资源倾斜与自下而上的需求倾听相结合的“双轨策略”。学院设立了由青年教师担任的 AI 教学研究员（AI Instructional Faculty Fellow），并在每月设立名为“第二个周五”（Second Friday）的线上常态化研讨会。该研讨会即便在暑假期间也维持了全职教师超过 70% 的自愿出席率。此外，学院领导层与骨干教师于 1 月前往硅谷，实地参访了 OpenAI、Google 和 Perplexity 等前沿企业，通过直观接触行业最新进展，有效消解了学术人员的疑虑并激发了教学创新动力。在师资建设方面，学院面临着与科技巨头竞争 AI 专业人才的现实难题。由于高校薪酬结构无法与科技行业抗衡，学院曾遭遇新聘教师仅任职一学期便离职创立 AI 初创公司的尴尬局面。面对这一留存挑战，商学院调整了招聘重心，重点吸纳认同高等教育育人使命、重视社会价值创造并致力于培养下一代商业领袖的学者与实践者。分级课程设计与学术诚信管理 (7:20) 在教学落地层面，科戈德商学院构建了四年渐进式培养体系，成为全美首批推出 AI 本科主修、辅修、商业分析与 AI 硕士以及专用 AI STEM 方向的商学院之一。该体系在大一阶段夯实 AI 基础认知与伦理规范；大二阶段融合会计、金融、市场营销、运营与人力资源等核心商业职能；大三阶段深入行业垂直应用，涵盖审计自动化、金融预测建模和大数据分析；大四阶段则以综合实践项目为主，要求学生运用 AI 工具解决真实的商业难题。在课程分类上，学院设定了 AI 内容占比超过 50% 的 19 门“智者”（Sage）课程，以及针对性融入工具的 39 门“匠人”（Artisan）课程，授课采用率在春季学期达到 50%，并计划在秋季提升至 75%。教学中还广泛引入了 Perplexity Spaces 等定制工具，覆盖 15 门核心课程与 60 多个班级，用于模拟谈判演练、生成多工具整合的营销组合方案以及教师人机共教。为维护学术诚信，学院推行了标准化的 AI 使用申报表制度，要求学生在提交作业时必须完成两项声明：一是明确列出 AI 在头脑风暴、草拟、数据分析、可视化或润色等哪个具体环节发挥了作用；二是详细阐明人类自身所贡献的批判性思考、编辑与监督工作，确保 AI 扮演的是认知加速器而非思维替代品。育人支柱、评价标准与行政整合 (13:33) 针对 AI 时代的复合型人才要求，学院依托扎实的专业知识，确立了三大核心支柱：普及全员的 AI 熟练度（AI Fluency）、深度人性化技能（涵盖同理心、沟通、跨职能协作及道德坚守等机器难以复制的领导特质）以及应对未知挑战的创业者思维（Entrepreneurial Mindset）。在能力衡量方面，学院采纳了数字教育委员会（Digital Education Council）制定的五层递进框架，从“基础认知”层层递进到“批判性思维与判断”（模型选型与数据验证）、“伦理与合规使用”（防范算法偏见）、“人机协作能力”以及最终的“领域垂直深度应用”，为各学科提供了阶梯式的成效评估依据。在教学之外，学院积极践行知行合一，将 AI 全面融入行政运作，包括部署招生咨询智能客服、将教师科研成果自动转化为通俗博文和社媒视频脚本、辅助起草公关稿件以及优化校友募捐和学术辅导流程。同时，学院与 Perplexity、Google 等行业巨头建立战略合作，并由 Gwanhoo Lee 牵头成立应用人工智能研究所（The Institute for Applied AI），联动全校 30 余位跨学科教研人员，构建起教研产一体化的协同平台。 Lee 总结认为，高校在应对颠覆性技术时，必须依赖管理层的直接支持与资源倾注，并坚持“速度重于完美”的试验思维，通过构建包容的师生社群与借助外部认可来持续维持变革势头。然而，面对企业高薪对高校师资的持续虹吸，以及各学科技术应用深度的参差不齐，传统学术体系如何在维持长期治理规范与快速响应产业迭代之间取得长久平衡，仍是各院校亟待解答的深层挑战。

Detailed notes — zh

## Background 该视频由 Ai4 频道于 2025 年 8 月 29 日在 YouTube 平台发布，主讲人为美利坚大学（American University）应用人工智能研究所主任兼 IT 与分析学教授关厚·李（Gwanhoo Lee）。内容主要介绍了科戈德商学院（Kogod School of Business）如何大刀阔斧重构商科课程体系并将 AI 深度融入教学、科研与校园运营，为高等教育应对技术颠覆提供了极具实操性的转型蓝图。 ## TL;DR 面对 AI 快速普及以及传统初级岗位被颠覆的严峻现实，科戈德商学院拒绝被动等待，率先落地了覆盖本科四年贯通培养与多元学位的全链路 AI 课程改革。学院采用“自上而下与自下而上”双轨策略，通过设立 AI 教学专员、每月“第二个周五”研讨会以及硅谷巨头实地参访等举措深度赋能教师群体，并独创了“贤者”与“工匠”两级课程分类架构和严格的学生 AI 使用披露制度。除了强化全员 AI 驾驭力，学院着重将同理心与沟通等“深度人性技能”以及创业家精神列为核心支柱，同时成立应用人工智能研究院并将 AI 全面应用于行政与招生运营，为全球高校输出了一套“行动先于完美”的系统化转型经验。 ## Atmosphere & style 整场演讲基调务实坦诚、节奏明快且极具紧迫感，主讲人毫不避讳高校在体制惯性与顶尖人才招募中的痛点与阵痛。叙事中穿插了学生作业披露、硅谷参访及教师心态转变等鲜活案例，既有发人深省的职场危机剖析，又有极具感染力的破局探索，给观众带来一种充满锐气、兼具理性思考与实践热忱的现场沉浸感。 ## Key takeaways - [00:04](https://www.youtube.com/watch?v=acMYFQaK_R4&t=4s) 高等教育正面临历史上最深刻、最具颠覆性的 AI 剧变，美利坚大学科戈德商学院选择主动试错与实验，引领全新教育形态而非被动等待。 - [02:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=130s) 随着 AI 迅速替代传统初级岗位，职场底层阶梯正在断裂；高校必须立即行动，培养学生直接承担更复杂专业角色的能力。 - [04:00](https://www.youtube.com/watch?v=acMYFQaK_R4&t=240s) 推行全院教学变革需自上而下与自下而上双轨并行，通过设立 AI 教学专员、举办“第二个周五”论坛及组织硅谷巨头访学来深度赋能教师。 - [06:36](https://www.youtube.com/watch?v=acMYFQaK_R4&t=396s) 打造本科四年贯通式培养路径：从大一素养伦理、大二核心职能应用、大三垂直专业纵深，逐步递进至大四的真实商业综合实战项目。 - [09:24](https://www.youtube.com/watch?v=acMYFQaK_R4&t=564s) 独创将全院课程划分为“贤者课程”（深度融合）与“工匠课程”（轻量嵌入）两大类别，并在数十个教学班级统一部署 Perplexity Spaces 个性化辅导空间。 - [11:24](https://www.youtube.com/watch?v=acMYFQaK_R4&t=684s) 在将 AI 深度融入谈判模拟和营销方案等真实课堂的同时，推行严格的作业 AI 使用披露机制，确保人类学生的独立思考与价值增量不缺位。 - [13:33](https://www.youtube.com/watch?v=acMYFQaK_R4&t=813s) 确立毕业生核心素养的三大支柱（全民 AI 驾驭力、深度人性技能、创业家精神）与深厚专业知识，并建立由低到高的五级学习产出评估阶梯。 - [17:20](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1040s) 将 AI 全面融入招生客服、科研成果传播与公关行政等运营流程，并成立应用人工智能研究院以统筹跨学科协作与产业落地。 - [19:17](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1157s) 高校成功实现 AI 转型的四大核心法则：高层坚决背书、快速敏捷试错、凝聚师生与校友共同体、借势外部权威认证注入势能。 ## Detailed walkthrough ### [00:04](https://www.youtube.com/watch?v=acMYFQaK_R4&t=4s) 面对史上最深刻的变革：高管与商学院的破局开端主讲人关厚·李（Gwanhoo Lee）在会议尾声登台致谢，开门见山地向与会者剖析了华盛顿特区美利坚大学（American University）科戈德商学院（Kogod School of Business）在过去一段时间里应对人工智能冲击的真实历程。他坦言，AI 正带来高等教育历史上最深刻、最具颠覆性的剧变之一，学院绝不敢自诩已经找到了这场转型之旅的“完美标准答案”。相反，科戈德商学院的这一路探索充满了试错、调整、即兴应变与大胆实验。演讲者指出，高教界传统深厚，但往往因循守旧、反应迟缓。虽然“AI 将改变一切”如今已成老生常谈，但在现实生活中，越来越多的人早晨醒来第一件事是与 AI 对话而非与人类交流，日常工作中对智能工具的依赖与日俱增。面对世界飞速重塑的现实，科戈德商学院做出了一个极其清醒而坚决的选择——绝不被动等待，而是主动构想并引领 AI 时代高等教育的全新形态。 ### [02:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=130s) 职业天梯底层断裂：被颠覆的职场与迫在眉睫的现实根据 2024 年的一项权威调查，高达 86% 的大学生已经在日常学业中使用 AI 工具。李教授强调，无论教育者喜欢与否，AI 已经深入课堂内部，假装视而不见无异于自欺欺人。与此同时，《纽约时报》（The New York Times）刊登的一篇由领英（LinkedIn）高管撰写的专栏文章指出，职场阶梯的最底端正在断裂——由于 AI 越来越强大，传统的初级岗位（Entry-level jobs）正在以惊人的速度消失。在学院开启课程重构之初，来自不同利益相关方的声音深深触动了领导团队： - 一位风险投资机构的首席执行官在对学生演讲时直言不讳：“AI 不会抢走你的工作，但懂 AI 的人会取代不懂 AI 的你。” - 一位刚毕业不久的年轻校友感慨：“AI 现在做的事情，正是我 22 岁刚入职担任第一年财务分析师时所做的全部工作。” - 学院顾问委员会的一位资深成员更是直接警告领导层：“必须跑起来，绝不能慢慢走，你们承担不起慢走的代价。” 高等教育必须立即行动，通过培养学生的 AI 素养、实践技能、深度人文特质以及灵活应变能力，帮助他们直接跨越断裂的初级阶梯，承担起更复杂的专业角色。 ### [04:00](https://www.youtube.com/watch?v=acMYFQaK_R4&t=240s) 双轨推进策略：如何赢得教授群体的认可与支持在大学体制下，课程体系的根本性改革若没有全体教职员工的深度参与，绝不可能取得成功。科戈德商学院采取了“自上而下与自下而上”并行的双轨策略：顶层领导团队提供前瞻愿景、战略方向、充足资源与保障支持；底层则深度倾听教师心声，建立持续的坦诚对话。为了把教师从旁观者变成推动者，学院采取了一系列雷厉风行的具体举措： - **引入行业领袖并成立委员会**：邀请顶尖 AI 行业领袖走进校园做深度交流，激发教师的好奇心与紧迫感；同时组建由教师代表组成的专属委员会，确保每一项政策制定都将教工声音置于核心。 - **设立 AI 教学指导专员**：通过全院问卷摸排接纳阻碍后，学院任命了一位最年轻的教职成员担任“AI 教学研究专员”（AI Instructional Faculty Fellow），作为全职教工随时可寻求支持的专属顾问。 - **年轻校友反哺与“第二个周五”论坛**：推出系列培训项目，其中最受欢迎的高分课程直接由走在产业一线的年轻校友讲授。同时设立每月一次的线上知识分享论坛“第二个周五”（Second Friday，每月第二个周五上午 9 点举行）。教师们在此倾诉教学困惑、宣泄焦虑，更分享优秀教案。即便纯属自愿参加，甚至在暑假期间，该论坛的专职教师出席率依然突破了 70%，创下了学院历史纪录。 - **硅谷朝圣之旅**：今年 1 月，院长亲自带领核心骨干教师直奔湾区与硅谷，密集走访 OpenAI、Google、Perplexity 等前沿人工智能企业，现场展示学院的 AI 改革思路并探讨深度合作。李教授笑着总结道：“没有什么能比亲眼目睹 AI 巨头内部正在发生的变革，更能迅速说服一名持怀疑态度的学者了。” ### [06:36](https://www.youtube.com/watch?v=acMYFQaK_R4&t=396s) 师资引才攻坚战与四阶段本科贯通式培养在师资队伍建设方面，学院持续投入重金招募 AI 与机器学习领域的顶尖人才。李教授坦承，高校在招聘市场上处境极其艰难，因为薪资待遇完全无法与科技巨头匹配；学院近期招募到的一位优秀学者甚至在执教仅一个学期后，就离职去创办了自己的 AI 初创公司。即便如此，学院依然在不懈寻觅那些真正认同高等教育使命与育人价值的专家。至本年秋季学期，科戈德商学院成为全美首批全面构建 AI 专业矩阵的商学院之一，覆盖本科 AI 主修（Major）、本科 AI 辅修（Minor）、商业分析与 AI 硕士项目以及多项 AI 证书体系。比增加新专业更令人兴奋的，是全链路贯穿、逐层递进的四阶段本科课程地图： ```mermaid flowchart TD accTitle: 本科四年 AI 贯通式培养路径 accDescr: 展示学生从大一至大四逐步深入的 AI 技能培养流程 subgraph Y1["第一学年：素养与伦理基础"] A["建立基础 AI 素养<br/>负责任与合规使用道德原则"] end subgraph Y2["第二学年：核心商业职能应用"] B["会计 / 财务 / 市场营销<br/>运营管理 / 人力资源全线整合"] end subgraph Y3["第三学年：垂直领域深度钻研"] C1["可持续发展：环境监测"] C2["金融：预测模型构建"] C3["会计：自动化审计实施"] C4["营销与分析：智能活动与洞察"] end subgraph Y4["第四学年：综合实践项目"] D["真实商业世界综合 Practicum<br/>融会贯通各类 AI 工具解决复杂问题"] end Y1 --> Y2 Y2 --> Y3 Y3 --> Y4 ``` 在大一阶段，重点是让学生夯实 AI 基础素养，牢固树立负责任、符合商业道德的使用规范；大二阶段，要求学生将 AI 应用于财务、会计、营销、供应链和人力等所有核心商业功能模块；大三阶段，全面转入细分专业纵深钻研，例如可持续发展专业利用 AI 进行环境监测、金融专业建立预测模型、会计专业推行自动化审计、市场营销专业设计综合推广战役；到了大四，所有工具与知识融会贯通，学生必须在毕业实践项目（Practicum）中直接面对真实商业挑战，利用工具链输出完整解决方案。 ### [09:24](https://www.youtube.com/watch?v=acMYFQaK_R4&t=564s) 课程分级架构与 Perplexity Spaces 深度融合在研究生培养端，学生在入学破冰导向（Orientation）阶段便会接受核心 AI 工具操作规范和伦理框架训练，随后迅速深入各自的专业垂直领域。目前，科戈德商学院下辖的会计、金融、管理、营销等各个系所均已将 AI 纳入日常教学。学院根据课程融入 AI 的深度，独创性地将全院相关课程划分为两大类别： | 课程类别 | AI 内容占比 | 定位与教学目标 | 现状规模 | |:--- |:--- |:--- |:--- | | **贤者课程 (Sage Courses)** | 50% 以上 | 课程内容以 AI 为核心或主要驱动力，深度钻研技术在商业中的重塑 | 19 门 | | **工匠课程 (Artisan Courses)** | 轻量级融入 (Lighter touch) | 维持原有商业学科核心，但在特定模块巧妙嵌入 AI 工具辅助学习 | 39 门 | 目前全院共有 54 门被明确认证的 AI 课程，每门课程均制定了清晰量化的学习产出指标（Learning Outcomes）。在上一个春季学期中，全院超过 50% 的课堂已经实际使用了 AI，预计秋季这一比例将飙升至 75%。此外，学院在 15 门核心基础课程、超过 60 个教学班（Sections）中统一部署了 Perplexity Spaces（功能类似 Google NotebookLM），为学生打造针对特定课程资料库的智能问答与个性化辅导空间。 ### [11:24](https://www.youtube.com/watch?v=acMYFQaK_R4&t=684s) 真实课堂实践与学生 AI 使用申报制度演讲者详细分享了几个极具代表性的课堂案例： - **商务谈判课程**：学生利用 AI 模拟极其复杂的博弈场景，建立多种具有不同性格倾向与利益诉求的“谈判对手数字人画像”（Personas）。学生在不同语境下演练谈判策略与对抗技巧，并在演练结束后立即获取 AI 给出的多维度复盘与个性化反馈。 - **数字营销课程**：在一个小组团队项目中，学生协同调用了超过 10 种不同的专业 AI 工具，独立生成并交付了一整套涵盖文案、视觉与投放方案的多渠道营销战役资产包。 - **创业与创新课程**：一位资深教授重构了其创业学大纲，与自己亲手搭建的 AI 助教协同授课，并为全班打造了一套经过精细调试的高质量提示词库（Curated Prompts），使每位学生都能针对个性化创业赛道进行探索。与此同时，针对学生学术规范，学院推行了严格的标准化过程监管机制。学生在提交任何作业或报告时，必须同步附上一份**科戈德 AI 使用披露表**，严格落实两项规定： 1. **详尽说明使用场景**：明确勾选并阐述 AI 在本次作业中扮演的具体角色（头脑风暴、草拟文稿、数据可视化、深度统计分析、排版呈现或校对润色）。 2. **界定人类自身贡献**：白纸黑字详细陈述人类学生在最终成果中做出了哪些独立思考、事实核验与价值增量。“我们绝不接受一份完全由 AI 驱动、人类缺位的成果。” ### [13:33](https://www.youtube.com/watch?v=acMYFQaK_R4&t=813s) 确立三大支柱能力与五级学习产出标准李教授强调，光有 AI 技能是远远不够的。一位领英高管在私下交流中曾向学院团队指出：即便是进入由智能驱动的经济格局，职场上最昂贵、最具护城河价值的资产，依然是“极具深度的人性特质”（Deeply human traits）。科戈德商学院据此确立了毕业生必须兼备的三大核心素养支柱： - **全民 AI 驾驭力（AI Fluency for everyone）**：无论何种专业背景，均能熟练调用智能生产力。 - **深度人性技能（Deeply Human Skills）**：包含同理心、领导力、高情商沟通、人际协作以及商业道德与诚信原则。 - **创业家精神（Entrepreneurial Mindset）**：这绝非创业者的专属，无论是在跨国集团任职还是在只有三人的小型非营利机构打拼，员工都必须具备跳出岗位说明书（Job Description）局限、主动发现问题、打破僵局并交付超预期成果的主人翁思维。 - 此外，作为基石的**深厚专业领域知识（Domain Expertise）**依然不可或缺，因为只有真正懂业务逻辑，才能精准驾驭 AI 算力，避免沦为肤浅的代码或文案拼凑者。在评估层面，学院依据数字教育委员会（Digital Education Council）的标准，制定了由低到高的五级本科 AI 学习产出阶梯： 1. **基础概念层**：透彻理解 AI 核心原理及其底层的具体数据处理逻辑。 2. **批判评估层**：具备系统核实 AI 所用数据源真实性的能力，能理性评估多款算法模型并为当下特定商业痛点筛选最佳解法。 3. **道德合规层**：主动识别算法偏差（Bias）、幻觉错误、歧视与潜在合规风险，时刻防范系统性危害。 4. **以人为本协同层（Human Centricity）**：具备在真实人类团队与自动化系统（如自主 AI Agent）之间穿梭协作的架构能力，动态调整沟通策略，实现“人类洞察研判与机器智能推理”的深度咬合。 5. **领域实战层**：在金融量化、财会审查或供应链等具体业务场景中，完整落地产业级 AI 解决方案。 ### [17:20](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1040s) 校园运营全面 AI 化与应用 AI 研究院的成立科戈德商学院坚持“言行一致”（Practice what we preach），积极与业界巨头（如获得 Perplexity Enterprise 授权支持、与 Google 联合研发教学评估标准）建立深度生态合作，并将 AI 全面应用于学院日常行政运营： - 部署全天候 AI 智能招生客服，接管准新生与家长各类高频复杂的招录咨询。 - 训练专属 AI 工作流，将教授发表的高深学术期刊论文，全自动提炼改写为通俗易懂的行业博客、社交媒体推文、播客及短视频脚本，成倍放大科研学术影响力。 - 利用 AI 工具自动化起草全院公关通稿（Press releases）与新闻报道，赋能公关传播与校友筹款捐赠。 - 搭建教务及政策导航助手，协助师生快速理清繁复的校规审批流程，甚至学生会活动策划也已全面采用 AI 规划执行。随着全院孵化出的 AI 创新项目呈爆发式增长，学院意识到必须设立一个中枢机构来进行跨学科统筹协同与成果放大。为此，学院正式揭牌成立了**应用人工智能研究院（Institute for Applied Artificial Intelligence）**。该研究院由李教授亲自兼任院长，汇聚了全校超过 30 位跨专业领域的资深教授，打破院系壁垒，全力推动产业落地与跨学科前沿协作。 ### [19:17](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1157s) 外部赞誉与四项不可替代的转型启示科戈德商学院的大胆变革赢得了全球学界与业界的瞩目，不仅获得了微软（Microsoft）、OpenAI 以及《泰晤士高等教育》（Times Higher Education）的公开赞赏，全球顶尖商学院权威媒体《Poets&Quants》更给予极高评价，称“科戈德商学院展示了全球商业教育界迄今为止最具深远影响力的 AI 转型”。在演讲结尾，李教授将这段波澜壮阔的改革历程凝练为四条至关重要的实操心法： 1. **决策层背书至关重要（Executive support is essential）**：自上而下的坚决支持是改革生存的土壤，没有学院最高领导团队的坚定愿景与资源倾斜，任何教学变革都注定难成气候。 2. **唯快不破，拒绝等待完美（Run, do not walk）**：如果一所大学非要等到市场上出现万无一失的“标准方案”才敢启动，那么它在起跑线上就已被时代永久淘汰。必须立即行动、敏捷试错。 3. **凝聚多方信任共同体（Build a community）**：构建一个将教师、学生、产业校友与行政人员紧密连接的社群，大家坐在一起公开探讨困惑、共享试错经验，转型就会从被动的恐惧变成充满趣味的探索。 4. **借势外部认证注入势能（Leverage external validation）**：善于利用外部业界的高度评价来巩固全院改革信心，这不仅能化解院内的阻力，更能为学校链接更丰厚的企业合作资源，形成不断自驱的正向循环。 “在座的各位，你们的学校准备好迎接 AI 了吗？”李教授在全场热烈的掌声中向所有高校管理者发出了最后的叩问与倡议，“这不仅仅关乎个别教授愿不愿意改大纲，更关乎整所机构能否作为命运共同体直面风浪。如果你不去主动引领变革，颠覆就会由其他人降临到你的头上。” ## Notable quotes > [02:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=130s) AI 不会抢走你的工作，但懂 AI 的人会取代不懂 AI 的你。 — 风险投资机构首席执行官 > [02:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=130s) AI 现在做的事情，正是我 22 岁刚入职担任第一年财务分析师时所做的全部工作。 — 年轻校友 > [02:10](https://www.youtube.com/watch?v=acMYFQaK_R4&t=130s) 必须跑起来，绝不能慢慢走，你们承担不起慢走的代价。 — 学院顾问委员会成员 > [04:00](https://www.youtube.com/watch?v=acMYFQaK_R4&t=240s) 没有什么能比亲眼目睹 AI 巨头内部正在发生的变革，更能迅速说服一名持怀疑态度的学者了。 — 关厚·李 (Gwanhoo Lee) > [11:24](https://www.youtube.com/watch?v=acMYFQaK_R4&t=684s) 我们绝不接受一份完全由 AI 驱动、人类缺位的成果。 — 关厚·李 (Gwanhoo Lee) > [19:17](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1157s) 科戈德商学院展示了全球商业教育界迄今为止最具深远影响力的 AI 转型。 — Poets&Quants > [19:17](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1157s) 决策层背书至关重要（Executive support is essential）。 — 关厚·李 (Gwanhoo Lee) > [19:17](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1157s) 唯快不破，拒绝等待完美（Run, do not walk）。 — 关厚·李 (Gwanhoo Lee) > [19:17](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1157s) 在座的各位，你们的学校准备好迎接 AI 了吗？ — 关厚·李 (Gwanhoo Lee) > [19:17](https://www.youtube.com/watch?v=acMYFQaK_R4&t=1157s) 这不仅仅关乎个别教授愿不愿意改大纲，更关乎整所机构能否作为命运共同体直面风浪。如果你不去主动引领变革，颠覆就会由其他人降临到你的头上。 — 关厚·李 (Gwanhoo Lee) ## Mentioned 关厚·李 (Gwanhoo Lee), 美利坚大学 (American University), 科戈德商学院 (Kogod School of Business), 应用人工智能研究院 (Institute for Applied Artificial Intelligence), Ai4, OpenAI, Google, Google NotebookLM, Perplexity, Perplexity Spaces, 微软 (Microsoft), 领英 (LinkedIn), 数字教育委员会 (Digital Education Council), Poets&Quants, 《纽约时报》 (The New York Times), 《华尔街日报》 (The Wall Street Journal), Axios, 《泰晤士高等教育》 (Times Higher Education) ## Video description Gwanhoo Lee, Director of the Institute of Applied AI and Professor of IT and Analytics, American University Abstracts Artificial intelligence is transforming the foundation of higher education. I will present a bold, practical vision for how universities can lead in this era by rethinking both teaching and learning. Drawing on my work as Director of the Institute for Applied Artificial Intelligence at American University’s Kogod School of Business, I will share our strategies for embedding AI across the curriculum, aligning learning outcomes with emerging technologies, and preparing students for careers shaped by AI. Our efforts have earned recognition from The Wall Street Journal, The New York Times, Axios, and Poets&Quants, and have been praised by industry leaders. I will provide actionable insights for academics, university administrators, industry leaders, and policymakers to drive AI-driven transformation in higher education. [Source](https://www.youtube.com/watch?v=acMYFQaK_R4)

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[2:10] 风险投资机构首席执行官: AI 不会抢走你的工作，但懂 AI 的人会取代不懂 AI 的你。 [2:10] 年轻校友: AI 现在做的事情，正是我 22 岁刚入职担任第一年财务分析师时所做的全部工作。 [2:10] 学院顾问委员会成员: 必须跑起来，绝不能慢慢走，你们承担不起慢走的代价。 [4:00] 关厚·李 (Gwanhoo Lee): 没有什么能比亲眼目睹 AI 巨头内部正在发生的变革，更能迅速说服一名持怀疑态度的学者了。 [11:24] 关厚·李 (Gwanhoo Lee): 我们绝不接受一份完全由 AI 驱动、人类缺位的成果。 [19:17] Poets&Quants: 科戈德商学院展示了全球商业教育界迄今为止最具深远影响力的 AI 转型。 [19:17] 关厚·李 (Gwanhoo Lee): 决策层背书至关重要（Executive support is essential）。 [19:17] 关厚·李 (Gwanhoo Lee): 唯快不破，拒绝等待完美（Run, do not walk）。 [19:17] 关厚·李 (Gwanhoo Lee): 在座的各位，你们的学校准备好迎接 AI 了吗？ [19:17] 关厚·李 (Gwanhoo Lee): 这不仅仅关乎个别教授愿不愿意改大纲，更关乎整所机构能否作为命运共同体直面风浪。如果你不去主动引领变革，颠覆就会由其他人降临到你的头上。

Source quotes

[0:04] Gwanhoo Lee: I will not pretend that we have discovered perfect answer for this... In fact, much of our AI journey has involved experimentation, trial and error, adaptation and improvisation to be honest. [1:10] Senior Executive at LinkedIn (via The New York Times): the bottom rung of the career ladder is breaking. [1:10] Venture Capital CEO: AI won't take your job, but someone who knows AI could take your job if you don't know AI. [1:10] Young Alumna: AI is doing what I did at 22 as a first-year financial analyst. [1:10] Advisory Board Member: Run, do not walk. You cannot afford to walk. We have to run. [4:00] Gwanhoo Lee: Nothing convinces a skeptical academic faster than seeing firsthand what's happening inside AI companies. [19:18] Poets&Quants: the most consequential AI transformation in business education. [19:18] Gwanhoo Lee: Are you AI ready? Not just your faculty or some students... but as an institution as a whole? If you don't lead this change, someone else will.

Original transcript

[0:04] Okay, good afternoon everyone. [0:07] So it's a it's thank you. It's good to [0:09] be here and then thank you so much for [0:11] staying until almost end of the [0:13] conference. [0:15] Um, today I'd like to give you an inside [0:18] look at how my institution Kogat School [0:21] of Business at America University in [0:22] Washington DC has been navigating AI [0:26] which is one of the most profound [0:28] disruptions in higher education history. [0:32] I will not pretend that we have [0:34] discovered perfect answer for this you [0:37] know uh AI transformation journey. In [0:40] fact, much of our [0:43] AI journey has involved experimentation, [0:47] trial and error, adaptation and [0:49] improvisation to be honest. [0:52] But we have made some bold moves and we [0:55] learned variable lessons and uh insights [0:58] along the way that I think could benefit [1:01] other universities and colleges facing [1:03] similar challenges. So I'm excited to [1:06] share those stories with you today. [1:10] So, it's almost a cliche to say AI will [1:13] change everything. Um, [1:16] how many of you start your morning by [1:18] talking to AI rather than humans? Yeah, [1:22] I'm not surprised. And then how many of [1:25] you find yourself relying on AI for more [1:28] and more tasks every day? Right. So, one [1:32] thing is so clear, a AI will change [1:34] everything and it's changing so fast. [1:37] What about higher education? US, it's no [1:41] exception. But unfortunately, [1:43] universities are not famous for moving [1:46] quickly when the world is changing. So [1:48] our long tradition sometimes make us a [1:51] little bit slow to adapt. [1:54] But at Kat School of Business, we made a [1:56] conscious decision to be proactive. And [1:59] we are trying to actively reimagine what [2:02] higher education could look like in an [2:04] AIdriven world. [2:10] So reality is 86 according to 2024 [2:14] surveyed 86% of hard students are [2:17] already using AI in their studies. So [2:20] whether you like it or not AI is in your [2:22] classroom. [2:24] Ignoring this reality is not a great [2:26] strategy. [2:31] According to this New York Times uh uh [2:35] up ad article uh by a senior executive [2:38] at LinkedIn, the bottom rung of the [2:40] career ladder is breaking which means [2:44] entry-level jobs are quickly [2:46] disappearing because of you know because [2:48] AI is increasingly powerful and [2:51] powerful. [2:53] So we need to prepare our students to [2:55] step into more complex roles by [2:58] equipping them with um AI fluency and [3:02] also practical skills and deeply human [3:05] skills as well as adaptability. [3:10] So as we began our journey to integrate [3:13] AI into our curriculum, we listened to [3:16] uh voices uh from a wide range of [3:19] stakeholders [3:20] and some of these quotes really stuck [3:22] with us. But the CEO of one capital uh [3:26] venture capital company told our [3:27] students in his uh uh speech uh this uh [3:31] AI won't take your job but someone who [3:34] knows AI could take your job if you [3:36] don't know AI. [3:38] One of the our young alumni here, she [3:41] put it this way. AI is doing what I did [3:43] at 22 as a first year financial analyst. [3:47] And one of our scores advised board [3:49] members gave us this advice. Run, do not [3:53] walk. You cannot afford to walk. We have [3:56] to run. [4:00] So integrating AI into curriculum cannot [4:03] succeed without engaging the faculty, [4:06] right? So we have taken a two-pronged [4:09] approach top down and bottom up to [4:11] engage our faculty. From the top our [4:14] leaders and leadership teams provide [4:17] vision, direction and resources and [4:20] support. From the bottom we listen to [4:22] our faculty and engage them in [4:24] meaningful dialogues. [4:29] So how do we engage our faculty more [4:32] specifically? First um we brought in [4:35] highprofile industry leaders to talk [4:38] about AI to spark curiosity and also a [4:43] sense of urgency among the faculty [4:46] and we formed a faculty committee to [4:49] help shape policies and keep faculty [4:52] voices central in every decision making. [4:56] We did a faculty survey to understand [4:59] adoption barriers and then we appointed [5:02] one of our youngest faculty members to [5:05] be AI instructional faculty fellow to be [5:08] a go-to resource for support [5:12] and then we rolled out a series of [5:14] training programs for faculty to learn [5:16] about AI and some interesting some of [5:18] the most engaging sessions were led by [5:21] our young alumni [5:23] and we launched the monthly online uh [5:26] knowledge sharing forum. Uh we call it [5:28] second Friday. Every second Friday 9:00 [5:31] a.m. We have online forum where you know [5:33] our colleagues share their experience [5:35] with AI. Sometimes they express [5:37] frustration concerns but also present [5:40] some of the best practices and to our [5:43] surprise even if this is an a voluntary [5:45] participation over 70% of full-time [5:48] faculty have attended this online [5:50] knowledge forum even during the summer. [5:55] never happened before. [5:58] And then back in January, uh our deans [6:00] and the select faculty members visited [6:03] OpenAI, Google, Perplexity and few other [6:06] AI companies in Bay Area and also uh [6:09] Silicon Valley and we presented our uh [6:12] approach to AI and then wanted to get [6:14] feedback from them and also wanted to [6:16] explore partnerships. [6:18] Let me tell you this, you know, nothing [6:21] convinces a skeptical academic faster [6:23] than seeing firsthand what's happening [6:26] inside AI companies. [6:28] So, I'm happy to say most of our faculty [6:30] members are on board with our AI [6:32] transformation. [6:36] So we invested in talent uh by hiring uh [6:40] several faculty members in AI machine [6:42] learning uh space and I have to tell you [6:45] this hiring market is so tough for [6:47] higher education because it's impossible [6:50] to match what tech giants can offer top [6:54] talent right and then in fact one of uh [6:57] our recent hires left us uh after just [7:01] one semester to launch an AI [7:06] Uh but we have no choice but to continue [7:10] to search for talent who appreciates and [7:12] values the the impact and then mission [7:15] of higher education and we found some. [7:20] So what does an AI integrated curriculum [7:23] look like? [7:26] So by this fourth semester we'll be one [7:28] of the first uh business schools in the [7:30] United States that offers all these [7:33] programs AI programs uh undergrad AI [7:37] major undergrad AI minor business [7:39] analytics and AI masters program and AI [7:43] bes so adding new programs exciting but [7:47] what's more exciting is AI is integrated [7:50] everywhere at all levels [7:54] so in Our undergraduate program, our [7:56] students do not just take a a few AI [7:59] courses here and there. Uh they go [8:01] through a journey step by step [8:03] systematically uh with a growing [8:06] confidence and depth. [8:08] So in their first year uh they build [8:11] basic AI literacy and learn how to use [8:14] AI responsibly ethically. That's our [8:16] focus for the first year. In their [8:18] second year they started using AI uh you [8:22] know across core business functions uh [8:24] accounting, finance, marketing, [8:25] operations, HR and so on. In their third [8:28] year, they take a deep dive into domain [8:31] specific AI applications. whether they [8:34] are building using AI for uh monetary [8:37] environment in their sustainability [8:39] major or um uh building predictive [8:43] predictive models for uh uh in finance [8:46] or implementing automated audit in [8:49] accounting or creating uh you know [8:53] campaign uh in marketing or turning big [8:55] data into business insights in in [8:57] analytics. In the final years, [9:00] everything comes together in an AI [9:02] infused practicum project where our [9:05] students solve real world problem using [9:09] a wide range of AI tools they learn [9:11] along the way. So our goal is to prepare [9:15] our students to not only to be familiar [9:18] with AI but also to be able to lead with [9:21] AI. [9:24] In our graduate program, we start at [9:27] orientation to uh uh by introducing our [9:30] students uh to the basic and essential [9:33] AI tools and concepts and also uh uh the [9:38] ethical disciplines principles in terms [9:41] of how they use AI uh responsibly and [9:44] ethically and from there they deep dive [9:48] into their domain specific discipline [9:50] specific AI concept and applications. [9:54] So where are we now in terms of AI [9:56] adoption infusion? [9:58] All our business schools departments [10:00] accounting to finance to uh management [10:03] to marketing uh we all teach AI in [10:07] certain form and then we classify our AI [10:10] classes courses into two categories. [10:14] In uh Sage courses uh we have over 50% [10:18] of course content that are AI related or [10:21] AI focused and then artisan courses uh [10:24] integrate AI incorporate AI with a [10:27] lighter touch. So right now we have 19 [10:30] sage and 39 artisan courses and these [10:33] numbers are uh are growing and all these [10:36] 54 AI courses have identified and [10:40] defined a learning outcomes [10:43] and last spring semester last semester [10:46] over 50% of they used AI in their [10:49] classroom and we expect this number to [10:51] go up to 75% in this coming fall [10:55] and last semester uh 15 core courses [10:58] with over 60 uh sections implemented uh [11:02] perplexity spaces similar to Google uh [11:05] you know uh notebook LM to provide the [11:10] students class specific support and [11:13] experience and then again this number [11:16] will go up dramatically in this coming [11:18] fall with faculty training and and then [11:21] and adoption. [11:24] Okay, let me give you a couple of [11:26] examples of how we incorporate AI into [11:28] specific courses. So, in our negotiation [11:30] course, [11:32] students use AI to simulate various [11:36] different kinds of negotiation [11:37] bargaining scenarios and they also build [11:40] different personas of different types of [11:43] negotiators and they practice their [11:45] negotiating tactics and strategies. They [11:47] learn from class against different types [11:50] of negotiators in very different types [11:52] of context and they get rece they [11:55] receive personalized feedback on their [11:57] performance. [12:00] In our uh digital marketing course, [12:02] students in their group project build a [12:06] full portfolio portfolio of uh marketing [12:10] campaign uh using more than 10 [12:12] differenti tools. And there is another [12:15] example that I love to share. Uh one of [12:17] my colleagues uh recently [12:19] um completely revised his [12:21] entrepreneurship course by collaborating [12:24] with an AI uh AI assistant that he built [12:28] himself and also he created a collection [12:31] of carefully curated prompts that [12:34] students can use to create uh students [12:37] own personalized learning experience on [12:39] certain topics. [12:43] So we ask students a couple of things. [12:46] The first thing is whenever they use AI [12:50] they need to fill out this standard form [12:53] that we use at Koka school business and [12:55] they submit it along with their uh [12:57] assignment or project. So they need to [13:00] specify how they use AI in their work [13:04] whether it's a brainstorming whether [13:05] it's a drafting whether it's data [13:07] visualization data analysis presentation [13:09] or proof reading they have to specify [13:12] second thing we ask them to do is to [13:14] document exactly what they the humans [13:18] contributed to the final work because we [13:20] don't want the final work to be [13:22] completely driven by AI right so [13:25] students need to do two things in order [13:27] to really uh uh leverage AI uh for their [13:31] work. [13:33] Okay, AI is great and powerful but uh AI [13:36] is not alone is not enough to prepare [13:38] our students in in AI economy. [13:44] So a LinkedIn senior executive told us [13:47] in a private conversation that most [13:50] valuable assets even in the AIdriven [13:53] economy are still deeply human such as [13:57] empathy such as leadership communication [14:01] uh you know integrity things like that [14:04] and we couldn't agree with more. [14:09] So we want to uh equip our students with [14:13] three these essential things. First AI [14:15] fluency for everyone. Second deeply [14:18] human skills such as as I said earlier [14:20] leadership, empathy, communication, um [14:24] uh coordination, integrity and things [14:26] like that. Third piece is actually [14:29] entrepreneurial mindset. This is not [14:31] just for future startup founders. It's [14:35] for everyone. Whether they are working [14:37] for a large global company or just a [14:40] threeperson nonprofit, they'll be [14:43] expected to go beyond their job [14:45] description and create new opportunities [14:47] and deliver results no one else. are [14:50] coming. [14:52] If I add one more thing here, uh domain [14:55] expertise will be still very important [14:57] because it enables them to fully [14:59] leverage and harness AI power and also [15:02] apply AI in meaningful ways. [15:07] So we identifi uh we defined AI learning [15:10] outcomes uh by starting with course [15:13] level learning outcome and then program [15:15] level and then school level and then uh [15:19] I'll share one example. Also in our [15:21] finance departments [15:24] um advanced quant uh advanced uh course [15:27] on quantitative method and machine [15:29] learning finance students will develop [15:31] sound uh understanding of key concept of [15:34] AI and they implement and build [15:37] predictive model for financial [15:39] applications and also use NLP method to [15:43] analyze unstructured uh text data in [15:46] financial context and so on. [15:49] We already talked about negotiation so I [15:51] skipped this. Uh and then in our program [15:54] level in our undergraduate level we [15:56] define the learning outcomes based upon [15:59] the framework from the digital uh [16:01] education council uh uh in terms of five [16:04] different levels. I'm not going to go [16:06] into all the details feel free to take a [16:07] picture but at the very high level one [16:10] is students will understand the key AI [16:14] concepts and related data processes. The [16:17] second level we focus on critical [16:19] thinking and judgment so the students [16:20] can uh systematically verify data [16:23] sources used by AI and also assess the [16:27] right model evaluate the different [16:29] models and pick the right model to solve [16:32] business problems at hand. The next [16:35] level uh learning outcome is ethical and [16:38] responsible use of AI. Students should [16:40] be able to identify potential bias, [16:42] potential inaccuracies, discrimination [16:44] and so forth so that they are mindful [16:46] about the potential risks. [16:49] The next level [16:51] human centricity. So students should be [16:53] able to demonstrate how they can collect [16:56] uh actively and proactively work uh [16:59] between human teams and the automative [17:01] system such as AI agent and adapt their [17:04] strategy communication work strategy to [17:07] to integrate human judgment with [17:09] automated insights. The final level uh [17:13] we expect students to use domain [17:15] specific discipline specific AI to solve [17:17] business problems. [17:20] So we nurtured uh strong industry [17:23] partnerships with these companies to uh [17:27] uh provide our students access to uh for [17:30] example perplexity enterprise uh uh tool [17:34] and also co-develop [17:36] method for assessing AI learning [17:38] outcomes with Google and then also uh [17:41] develop uh learning programs uh training [17:44] programs. [17:47] So we want to practice what we preach uh [17:50] by applying AI in our various. [17:54] So one example is we have AI chatbot uh [17:58] that answer all the admission questions [18:00] from prospective students and parents [18:02] and then we trained AI to translate our [18:04] faculty's uh academic research into [18:07] blogs and social media posts and then [18:09] videos for wider dissemination and then [18:13] we have AI tool to write press releases [18:16] and news articles for PR and marketing [18:18] of our school and then we are using AI [18:21] for uh to support uh fundraising and [18:24] academic advising [18:27] and then also help student uh faculty [18:29] navigate complex university processes [18:31] and policies and even our student by [18:34] using AI for organizing their events and [18:37] activities [18:39] and then we also realized that because [18:42] we launched so many you know AI projects [18:45] uh we needed a centralized unit uh the [18:49] organization to connect and collaborate [18:52] and coordinate and also amplify ify the [18:54] impact of all these efforts and then [18:56] that's why we launched the institute for [18:58] applied artificial intelligence. I have [19:00] a privilege of directing this institute [19:02] and we have more than 30 faculty members [19:04] across from the campus of free with this [19:06] institute. So the cross disciplinary [19:09] collaboration is what makes this [19:12] institute uh very valuable. [19:15] So, [19:19] so we received some positive external [19:21] validations about our progress with AI [19:24] uh from Microsoft and open AI and also [19:28] times higher education. Uh the points [19:30] and quans remarked that Kogat has [19:33] demonstrated the most consequential AI [19:35] transformation in business education [19:37] which is very flattering. Uh but [19:39] receiving these awards from industry [19:40] leaders u is not only humbling but also [19:43] very rewarding for us. [19:45] So what have you learned in terms of [19:48] lessons learned? Well, first executive [19:50] support is so essential. Without leaders [19:53] uh backing transformation struggles to [19:56] take root and then second we have to [19:59] move fast otherwise if you're waiting [20:01] for the perfect solution and answer [20:03] you'll never started and you'll be [20:05] always left. Right? And then build a [20:08] comm community. Community is so [20:09] important. When faculty, students and [20:11] staff they all connected and they learn [20:14] together and they share ideas then [20:17] transformation journey can be much [20:19] easier and then much more fun. [20:22] Lastly, receiving uh you know positive [20:24] external validation boost your [20:26] confidence and also creates new [20:28] opportunity and also fears new momentum [20:31] going forward. So I'd like to leave you [20:34] with this. Are you AI ready? I'm not [20:36] just talking about your faculty or some [20:38] students or some efforts but as a [20:41] institution as a whole uh are you ready? [20:44] So if you don't lead this change someone [20:46] else will do that. So I hope that you [20:48] will be ready to uh lead your AI uh [20:52] transformation journey. So with that [20:53] thank you so much for your attention. [20:55] Appreciate it.