Artificial Intelligence

Through professional programs developed by faculty from Cornell Bowers Computing and Information Science, Cornell Tech, Cornell SC Johnson College of Business, Cornell Law School, Cornell Brooks School of Public Policy, Weill Cornell Medicine, and Cornell Engineering, Cornell University approaches artificial intelligence (AI) as both a technical field and a force reshaping business, law, policy, healthcare, finance, communications, and society.

That breadth matters because AI decisions rarely sit in one function. A leader evaluating AI strategy needs to understand value creation and organizational change. A developer building with large language models requires practical fluency in model behavior and data management. A risk, legal, or policy professional must evaluate privacy, accountability, bias, intellectual property, and governance. Cornell’s portfolio is designed to help professionals build that judgment from multiple angles.

What also distinguishes Cornell’s AI programs is the combination of academic rigor, interdisciplinary expertise, and a learning experience designed for immediate professional application. Developed by faculty from multiple Cornell schools and colleges, these programs help professionals move beyond AI hype to understand how the technology creates value, introduces risk, and changes decision making across organizations. Participants learn alongside a global network of experienced professionals in small, facilitated cohorts, applying concepts to real-world challenges while earning a Cornell University credential that’s recognized across industries. This combination of subject-matter depth, practical relevance, and personalized learning creates a professional education experience that goes beyond standalone technical training or self-paced online courses.

Cornell offers AI professional learning opportunities through several formats, including professional certificates, courses, workshops, degrees, and enterprise programs. Each format differs in its structure, time commitment, and credential, but all programs deliver an unparalleled learning experience representing the pinnacle of premium online professional education.

• AI certificate programs provide comprehensive expertise in an AI subject area for professional transformation and workplace impact. Topics include AI strategy, machine learning, generative AI, large language models, AI law and policy, healthcare, financial services, cybersecurity, hospitality, productivity, and workplace communication. Most certificate programs include 4 to 8 individual courses completed over 2 to 6 months. Programs are delivered online in a cohort-based format with live expert facilitation, personalized feedback, workplace projects, interactive activities, and opportunities for live sessions. Small class sizes for individual professionals create meaningful opportunities to learn alongside a global cohort of peers. In support of organizational development goals, participants can enroll in private, dedicated cohorts that create a shared learning experience for a team and can be tailored to organizational priorities through customized projects and facilitated discussions. Participants earn a Professional Certificate from Cornell University upon completion.
• Individual AI courses allow learners to explore a specific topic in depth within a shorter time frame and can help build targeted fluency in a specific AI method or use case. Many courses are available as standalone learning experiences and may also serve as components of certificate programs. Courses are typically completed in 2 to 4 weeks and delivered online in a cohort-based format with live expert facilitation. Organizations can select specific individual courses to develop a custom learning program that solves their biggest organizational challenges and can be taken either with a global cohort of peers or in a private cohort. Several courses can stack to a certificate, and participants receive a Letter of Completion from Cornell University.
• AI Workshops are live, faculty-led online sessions designed to rapidly build specific, actionable AI skills and strategies for immediate workplace application. Led by Cornell faculty, Workshops typically last 3 to 5 hours and emphasize structured instruction, guided hands-on practice, peer discussion, and interactive participation. Workshops are available individually or through a 6-month All-Access Pass which provides unlimited access to upcoming sessions. Workshops can also be delivered in a dedicated session for an organization interested in aligning large teams in a consistent approach. Participants earn a Letter of Completion from Cornell University upon completion.
• Cornell professional degree programs that include AI-related study provide academic credentials through formal admissions-based programs. Depending on the degree, AI topics may be explored through disciplines such as data science, decision analytics, business analytics, engineering, information science, and related fields. These programs are distinct from professional certificates, courses, and Workshops. Degree programs typically require a multi-year commitment and award a Cornell University degree upon completion.
• AI enterprise and team programs help organizations build shared AI capabilities, accelerate adoption, and translate AI learning into organizational impact. Organizations can combine AI courses, certificate programs, Workshops, and custom executive education into a blended learning strategy that supports leaders, technical teams, and cross-functional groups at every stage of AI adoption. For executive leadership teams, Cornell offers custom executive education built around the Studio Method, a distinctive learning-by-doing approach that helps organizations develop an AI strategy, align stakeholders, and create an actionable roadmap tailored to their business. Organizations can incorporate customized projects, facilitated discussions, dedicated cohorts, and other unique learning experiences into a unified program that reflects strategic priorities while participants earn Cornell credentials associated with each learning experience.
• In addition, Cornell Keynotes provide open access to timely conversations on AI and other emerging topics featuring Cornell faculty and industry experts. AI-focused sessions explore subjects such as generative AI, AI strategy, the future of work, fintech, data science, and technology innovation through live and on-demand presentations, panels, and discussions. Keynotes are 1-hour live and recorded video and podcast episodes designed for professionals who want to stay informed on emerging AI trends and faculty perspectives without committing to a course or certificate program.

Unlike many AI learning options offered by technology vendors, consulting firms, or self-paced online platforms, Cornell provides an independent, research-informed perspective on how AI is transforming business, technology, law, healthcare, public policy, and society. Rather than focusing on a single platform or tool, our programs help professionals develop the judgment to evaluate AI technologies, understand their opportunities and limitations, and make informed decisions across a rapidly changing landscape.

Learning takes place through an interactive online model that includes expert-facilitated cohorts, graded assignments, project feedback, peer discussion, and real-world application. Cornell faculty-developed content is paired with practical professional practice, helping participants understand not only what AI tools can do but also when, where, and why to use them. This approach helps professionals build lasting judgment, not just familiarity with AI vocabulary.

The portfolio reflects Cornell’s interdisciplinary strength, with courses authored by leading faculty. For example, the AI strategy curriculum was created by Karan Girotra from Cornell Tech and Cornell SC Johnson College of Business. Machine learning content was developed in collaboration with Cornell Bowers Computing and Information Science faculty including Kilian Weinberger. The large language model curriculum was designed with guidance from David Mimno of Cornell Bowers. AI law and policy content was authored by faculty including Frank Pasquale from Cornell Law School and Cornell Tech and Sarah Kreps from Cornell’s College of Arts and Sciences.

Cornell’s AI portfolio draws from multiple Cornell schools and units, reflecting the way AI touches computing, business, policy, law, medicine, engineering, finance, nutrition, and workplace practice.

• Cornell Bowers Computing and Information Science contributes technical depth in areas such as machine learning, large language models, text analysis, data science, and AI engineering. Authoring faculty include Kilian Weinberger, David Mimno, Sumanta Basu, Sreyoshi Das, Ayham Boucher, and Martin Wells.
• Cornell Tech contributes perspectives on AI business transformation and approaches to improve AI productivity. Programs from Cornell Tech are primarily authored by Karan Girotra, who also leads several live online AI Workshops.
• Cornell SC Johnson College of Business contributes programs in the areas of business, finance, marketing, and communications. Contributing faculty include Andrew Karolyi, Vera Chau, and Chris Meredith in finance; Clarence Lee in marketing; and Lutz Finger, who developed a program on building AI solutions. Several of these faculty also participate in delivering AI Workshops.
• Cornell Law School contributes legal, ethical, and regulatory perspectives, including faculty expertise from Frank Pasquale, a leader in the area of AI law and ethics.
• Cornell Brooks School of Public Policy contributes governance, public policy, cybersecurity, and technology policy perspectives from faculty including Ning Su, Sarah Kreps, and Judith Germano.
• Weill Cornell Medicine contributes healthcare AI expertise from faculty including Fei Wang, Yiye Zhang, Yifan Peng, and Jose Florez-Arango, part of the Department for Population Health.
• Cornell Engineering contributes engineering, data science, and AI in finance perspectives from faculty including Linda Nozick, Victoria Averbukh, David Goldberg, Jamol Pender, and Jeffrey Varner.
• Cornell College of Human Ecology contributes nutrition- and health-related perspectives from faculty including Saurabh Mehta in precision nutrition and AI.

Cornell’s AI portfolio is designed for individual professionals, organizational teams, and executive leaders seeking to build AI capabilities at different levels of their organization. Programs range from individual courses and certificate programs to AI Workshops, custom executive education, and enterprise learning solutions, allowing learners and organizations to select the format that best fits their goals.

Executive leaders and leadership teams often work with Cornell to develop customized executive education experiences that address their organization’s strategic priorities. Through Cornell’s Studio Method, leadership teams can build a shared understanding of AI, evaluate opportunities and risks, align around an AI strategy, and develop an actionable roadmap for implementation and organizational change.

Organizations building AI capabilities across multiple functions can combine certificate programs, courses, Workshops, and dedicated cohorts to create scalable learning pathways for leaders, technical teams, and cross-functional groups, helping establish a shared foundation for responsible AI adoption.

Functional teams and individual professionals can develop expertise tailored to their roles. For example:

• Business leaders, managers, and product leaders can focus on AI strategy, organizational transformation, productivity, and implementation
• Developers, engineers, data scientists, analysts, and technical product managers can build skills in machine learning, large language models, agentic AI, natural language processing, model evaluation, and AI system development
• Lawyers, policymakers, compliance officers, and risk professionals can deepen their understanding of AI law, governance, privacy, intellectual property, accountability, and regulation
• Professionals in healthcare, finance, hospitality, nutrition, cybersecurity, communications, and other industries can apply AI to domain-specific challenges within their fields
• Individual contributors across nearly every profession can build practical AI fluency to improve productivity, collaboration, communication, workflow redesign, and everyday decision making

Cornell’s AI portfolio covers both foundational AI capabilities and emerging professional applications. The category is broad enough to support leaders, technical specialists, risk professionals, and domain experts.

• Generative AI and productivity, including prompt strategies, AI-assisted workflows, workplace communication, presentations, automation, and business process transformation
• Machine learning and data science, including supervised learning, classification, model selection, neural networks, probability, regression, clustering, and model improvement
• Large language models and natural language processing, including text preprocessing, sentiment analysis, tokenization, model comparison, fine-tuning approaches, attention, embeddings, and computational text analysis guided by Cornell Bowers faculty such as David Mimno
• Agentic AI and AI architecture, including retrieval-augmented generation, AI agents, context engineering, tools, memory, and workflow automation
• AI strategy and transformation, including business model innovation, organizational readiness, AI initiative prioritization, governance, and responsible adoption, with strategy perspectives connected to Karan Girotra from Cornell Tech and Cornell SC Johnson College of Business
• AI law, policy, and risk, including privacy, equity, intellectual property, liability, global governance, deepfakes, cybersecurity, and critical infrastructure, with supported faculty expertise from Frank Pasquale, Sarah Kreps, and Judith Germano
• Industry-specific AI, including healthcare AI through Weill Cornell Medicine faculty such as Fei Wang, AI in finance through Cornell Engineering and business faculty, AI in hospitality, precision nutrition and AI, and NLP for financial text data

As AI continues to transform industries and reshape professional practices, Cornell’s approach is grounded in faculty involvement, active research communities, and learning formats that can address emerging issues in the field. eCornell programs are developed by Cornell faculty, and the AI portfolio draws from schools and units connected to current work in computing, business, law, policy, medicine, and engineering. We maintain a consistent and methodical approach to reviewing student feedback and regularly update programs to ensure they reflect Cornell’s latest AI research and thought leadership.

Cornell’s broader AI ecosystem includes the AI4AI Initiative; Cornell Bowers Computing and Information Science; Cornell Tech’s AI research group; Machine Learning at Cornell; the Artificial Intelligence, Policy, and Practice initiative; and the Cornell Brooks School Tech Policy Institute. These communities directly inform our professional education programs, anchoring them in the critical questions shaping AI today including responsible use, human-AI collaboration, enterprise adoption, model behavior, privacy, security, fairness, and governance.

Our purposeful program design emphasizes human interaction through live sessions with expert facilitators, short-format AI Workshops, and symposium-style experiences. These offerings enrich our full certificate programs, giving professionals personalized ways to engage with AI applications and implementation challenges.

Cornell’s AI portfolio addresses all three, which is a major advantage for professionals whose AI decisions cross functional boundaries.

Strategy-oriented options help leaders evaluate AI opportunities, prioritize initiatives, redesign workflows, assess organizational readiness, and connect AI capabilities to business value. This perspective is authored by Cornell faculty such as Karan Girotra from Cornell Tech and Cornell SC Johnson College of Business.

Technical options help developers, data scientists, engineers, analysts, and AI practitioners build fluency in machine learning, large language models, natural language processing, agentic AI, retrieval-augmented generation, model behavior, and data workflows. Cornell Bowers Computing and Information Science faculty such as Kilian Weinberger and David Mimno support this technical depth.

Governance-oriented options help legal, policy, risk, compliance, cybersecurity, and executive professionals address privacy, bias, equity, intellectual property, liability, deepfakes, cybercrime, and global AI governance. Cornell Law School, Cornell Tech, and Cornell Brooks School of Public Policy are especially relevant here, supported by faculty including Frank Pasquale, Sarah Kreps, and Judith Germano.

Cornell’s AI programs treat responsible use as a multifaceted challenge involving leadership, legal, technical, and organizational considerations. Learners can explore how AI systems create risks related to privacy, bias, accountability, intellectual property, liability, misinformation, global governance, cybersecurity, deepfakes, and human oversight.

This perspective is supported by Cornell faculty and units with specific AI governance expertise. Frank Pasquale, a Cornell Law School and Cornell Tech professor, developed the AI law and policy curriculum. Sarah Kreps, from Cornell University’s College of Arts and Sciences and the Cornell Brooks School Tech Policy Institute, brings a public policy and national security perspective. Judith Germano, from Cornell Brooks School of Public Policy, authored the cybersecurity and AI strategy program.

Cornell’s broader research ecosystem also includes the Artificial Intelligence, Policy, and Practice initiative housed in Cornell Bowers Computing and Information Science, which focuses on the social, policy, and practice dimensions of AI. That makes responsible AI a cross-disciplinary theme rather than a standalone compliance topic.

Cornell’s AI learning options can support organizations that need shared AI fluency across teams, not just individual upskilling. Through Cornell’s AI enterprise programs, organizations can create private cohorts, align discussions with internal priorities, and connect learning projects to business goals.

This variety can be useful when different groups require different levels of AI capability. Executives may need to evaluate strategy, governance, investment, and risk. Managers may need to redesign workflows and guide adoption. Technical teams may need deeper skills in data, models, automation, and implementation. Legal, compliance, HR, finance, healthcare, marketing, and operations teams may need role-specific applications and guardrails.

Cornell’s AI portfolio is broad enough to support that layered approach. Organizations can combine certificate programs, individual courses, live AI Workshops, and custom learning experiences to build a common language for AI while still addressing specialized needs.

Learn more about Cornell’s AI Enterprise Programs for teams here.

Cornell offers AI programs specific to several industries:

• Healthcare: Cornell’s AI in Healthcare Certificate is designed for healthcare, data, and technology professionals who want to learn how to apply AI, machine learning, natural language processing, and data management techniques to improve healthcare outcomes, support decision making, and drive responsible innovation in healthcare organizations.
• Hospitality: Cornell’s AI in Hospitality Certificate is designed for hospitality professionals, managers, and industry leaders who want to learn how to leverage AI, machine learning, and predictive analytics to enhance guest experiences, improve operational efficiency, and make more data-driven business decisions.
• Finance: Cornell’s AI in Finance Certificate is designed for finance professionals, banking leaders, fintech innovators, and business decision makers who want to learn how to apply AI technologies to improve financial analysis, manage risk, drive innovation, and lead AI adoption across financial organizations.
• Marketing: Cornell’s Marketing AI Certificate is designed for marketing professionals, strategists, and business leaders who want to learn how to use AI to enhance customer insights, personalize experiences, improve marketing performance, and drive innovation across marketing functions. In addition, we frequently offer AI Workshops designed for marketing professionals. For example, the “Search and Discoverability in the Era of AI” Workshop equips you with strategies to thrive in this new landscape as well as frameworks you can implement immediately to capture visibility in AI-powered search results and conversational interfaces.
• Human Resources: Cornell’s AI in Human Resources Certificate is designed for HR professionals, talent leaders, and people managers who want to learn how to apply AI across talent acquisition, performance management, and workforce analytics while balancing efficiency, fairness, and responsible decision making. In addition, we frequently offer AI Workshops designed for human resources professionals. For example, the “AI and the Future of HR” Workshop provides HR professionals with a high-level roadmap to navigate the future of the profession.
• Law: Cornell’s AI Law and Policy Certificate is designed for legal, compliance, policy, and business professionals who want to learn how to navigate the legal, ethical, and regulatory implications of AI; manage organizational risk; and develop responsible AI governance strategies. In addition, we frequently offer AI Workshops designed for legal professionals. For example, the “Use AI Agents for Legal and Related Workflows” Workshop gives professionals in legal and compliance-related fields hands-on experience with AI agents and practical tools to understand their capabilities and limitations.
• Cybersecurity: Cornell’s Cybersecurity and AI Strategy Certificate is designed for cybersecurity, technology, risk, compliance, and business leaders who want to learn how AI is transforming cyber defense and cybercrime as well as how to manage emerging risks through effective governance, strategy, and policy.