University IT 2025-2027 Priority Initiatives

Modernize system access and device management as part of the broader Identity and Compliance strategic roadmap to ensure the security and integrity of Stanford's data and systems. Key efforts in FY2027 include implementing Microsoft Entra ID as a secondary identity provider alongside Shibboleth, rolling out Intune for device management, enforcing verified Duo push, and evaluating core network architecture.

Simplify research data security compliance, address evolving federal mandates, and strengthen our institutional security posture. Establish a certified CMMC Level 2 cloud environment to meet Department of War requirements for Controlled Unclassified Information. In FY27, partner with an external provider to build and validate the environment, establish operational roles, and onboard researchers.

A multi-year initiative to replace PeopleSoft HR and payroll systems for Stanford and SLAC. Launched in July 2026, Sequoia runs on Oracle Human Capital Management, a cloud platform that streamlines access to and delivery of HR and payroll services. Sequoia's launch is supported by a dedicated six-month Hypercare model.

A multi-year initiative to rollout an enterprise learning platform to replace STARS using Cornerstone OnDemand. STARS currently supports 50K+ learners and 30+ business units to assign, deliver, and track compliance training for Stanford. Phase 1 focuses on migrating all active STARS users to the new platform in PY2027, establishing a foundation before onboarding additional campus units in Phase 2.

Replace Oracle Enterprise Asset Management and Oracle Inventory with IBM Maximo to support facilities and asset management needs across multiple operational units. Following solution design and proof-of-concept testing in PY2026, implementation kicks off for the School of Medicine, SLAC, and Land, Buildings & Real Estate.

Stanford Navigator will unify class search and enrollment into a single, personalized platform, modernize the Stanford Bulletin for degree and course information, and provide robust APIs to make trusted curricular data widely accessible. Through PY2027, key work includes deploying enterprise search, launching the new digital Bulletin, and designing an integrated enrollment experience.

Replace the legacy student system and websites with Salesforce for the Stanford Continuing Studies Program, which serves more than 17,000 learners yearly. Going live in PY2027, the modern platform delivers a scalable, accessible user experience for staff and supports student registrations.

Ensuring Stanford provides technologies critical for data-driven discovery and AI/machine learning during the next decade, while addressing the ever-increasing demand for research computing capacity. Phase 2 builds on initial campus analysis by conducting cloud and co-location pilots, completing a data center feasibility study, and finalizing a long-term strategy for expanding research computing.

Streamline the management of Stanford's faculty and teaching/research staff lifecycle for 9K+ community members. Improve efficiency in processes from recruitment to appointments, promotions, and retirement to reduce administrative burden. Key efforts in PY2027 focus on replacing recruitment tools with Interfolio and developing a platform prototype for overall lifecycle management.

Launched in 2025, this effort supports our campus community with their wide-ranging needs for AI services such as developer enablement, functional agents, and intelligent automations. In PY2026, clients include Business Affairs (FMS, UHR, ORA, OCRO), Student and Academic Services, Office of Development, Graduate School of Business, School of Medicine, and the President and Provost's Office. 

Stanford is upgrading its campus phone infrastructure to a modern Unified Communications-as-a-Service solution. Throughout PY26-27, the project team is evaluating vendors, designing system architecture, and preparing the cloud platform for migration. Campus-wide migrations are set to begin in June 2027.   

Stanford is modernizing its cybersecurity defenses to keep pace with evolving threats and AI-driven exploits. By mid-2027. a unified, enterprise-wide vulnerability management platform will be deployed to provide continuous asset discovery, cloud-to-campus coverage, and risk-based prioritization. This effort ensures critical exposures are remediated quickly and efficiently.

Stanford is developing a unified enterprise wireless strategy to align Wi-Fi and cellular networks into a seamless, high-performance connectivity framework. This initiative focuses on defining baseline service standards, expanding indoor, outdoor, and high-density coverage, and optimizing long-term investments to support future needs.

This multi-year initiative aims to elevate the IT service experience for the entire Stanford community. Through mid-2027, the ITSM program will focus on translating initial pilots into full campus production, with key efforts centered on updating our ServiceNow platform, centralizing operational data, deploying standard artificial intelligence capabilities, and redesigning the service catalog and knowledge base for easier, search-driven navigation.

Marlowe, Stanford's flagship GPU-based computing instrument, is a collaboration among Stanford Data Science, the Vice Provost and Dean of Research, and Stanford Research Computing, working together with NVIDIA. Ongoing efforts focus on optimizing the use of Marlowe for the broader campus research community, including the continual review and refinement of policies, procedures, and technology configurations.

Address a growing need to archive large volumes of high-risk data and protected health information (PHI). Launched in July 2026, Elm provides secure, compliant cold storage with ongoing service support to accommodate the continuous growth of campus research data.

Helping the Stanford community effectively leverage AI technologies. This comprehensive effort includes the release of new enterprise AI tools, implementing custom and vendor-provided solutions, and supporting responsible use across the university. In parallel, delivering training resources through the new AI Practice effort to guide the practical implementation of AI across campus.

AI Catalyst (UIT only): Efforts within UIT to support developer enablement, functional agents, intelligent automations, and AI Playground/support related requests.

Create a centralized, scalable infrastructure for data de-identification, particularly for unstructured data that creates significant challenges in the Data Risk Assessment process. The absence of standardized processes and validation mechanisms creates operational bottlenecks; establishing a reliable and scalable de-identification process will help mitigate risk and improve research efficiency.