AI system/product: ChatGPT (Codex Work Mode)  
Model name/version: Exact model version not available in this session  
Date: September 24, 2026  
Web research used: Yes

# THE DEAN’S LIST

**#1 — Learning and assessment in the AI era**  
**Why it matters:** Widespread AI use changes how students learn and what coursework proves. Colleges must redesign assessment, develop critical AI literacy, and ensure graduates can demonstrate independent understanding as well as effective AI use.

**#2 — Cybersecurity and identity protection**  
**Why it matters:** Cyberattacks and identity fraud threaten teaching, research, financial aid, and institutional trust. Leaders must strengthen identity controls, protect sensitive information, and prove that essential services can recover from disruption.

**#3 — Sustainable technology spending**  
**Why it matters:** Technology costs, aging systems, and limited staff compete with academic priorities. Institutions need to simplify their systems, fund essential skills, and demand measurable value from modernization and AI investments.

**#4 — Digital accessibility**  
**Why it matters:** Accessible courses, websites, documents, and applications are essential to equal participation. Approaching public-sector compliance deadlines require coordinated investment in content, procurement, faculty support, and ongoing maintenance.

**#5 — Trusted data and accountable AI**  
**Why it matters:** As AI moves from answering questions to taking actions, unreliable data and unclear authority become institutional risks. Colleges need dependable information, privacy protections, explicit decision rights, and human accountability for automated services.

**#6 — Connected student services**  
**Why it matters:** Disconnected admissions, aid, advising, and academic systems create avoidable obstacles. Connecting services and human support can improve students’ progress while helping institutions respond to shifting enrollment and learner needs.

**#7 — Career preparation for changing work**  
**Why it matters:** AI and automation are changing entry-level work. Colleges must refresh curricula, strengthen work experience, and show what graduates can do as demand grows for shorter, verifiable credentials.

# DEEPER ANALYSIS

This ranking reflects my judgment about institutional consequences, breadth of exposure, urgency, and the preparation required between September 2026 and September 2028. It is a leadership agenda, not a technology purchasing list. Current studies and policies establish the starting conditions; forward-looking statements below are assessments rather than settled outcomes. Institution-specific risks can change the order, particularly for research universities and financially vulnerable colleges.

## #1 — Learning and assessment in the AI era

This ranks first because it reaches higher education’s central promise: students learn, and credentials reliably represent that learning. Changing assessment across programs also takes longer than adopting software.

**Evidence.** Gallup’s April 2026 report found that 57% of surveyed U.S. associate- and bachelor’s-degree students used AI for coursework at least weekly. The underlying October 2025 survey used an opt-in panel; it measures reported behavior, not learning. [Gallup](https://news.gallup.com/poll/704090/routine-college-students-despite-campus-limits.aspx)

The educational effects depend on design. A randomized Harvard physics study found stronger immediate learning with a purpose-built AI tutor than with classroom active learning. A separate high-school mathematics experiment found that unrestricted AI assistance could weaken subsequent unaided performance. Neither establishes the long-term effects across college disciplines. Together, they support testing teaching designs rather than assuming either universal benefit or universal harm. [Kestin et al.](https://www.nature.com/articles/s41598-025-97652-6), [Bastani et al.](https://pubmed.ncbi.nlm.nih.gov/40560616/)

**Next 12–24 months.** More capable tools will make polished submissions less informative about students’ own competence. I expect pressure for oral explanation, supervised demonstrations, documented revision, and assessments combining independent work with disclosed AI assistance.

Institutions should fund faculty development and evaluate learning beyond assignment completion. Large introductory courses need scalable assessment designs; professional programs must preserve demonstrated clinical, technical, and ethical competence. Colleges serving students with limited resources should address unequal access to tools and support without making paid AI subscriptions a hidden prerequisite.

**Questions now:** What must graduates demonstrate unaided? Where does AI improve learning rather than merely output? Who funds redesign, and how will we measure retained understanding?

## #2 — Cybersecurity and identity protection

This ranks second because failures can immediately interrupt the institution and harm students. The priority encompasses ransomware, compromised accounts, fraudulent enrollment, vendor exposure, and recovery capacity.

**Evidence.** Sophos’s 2026 international survey included 95 higher-education organizations already affected by ransomware; 53% cited insufficient expertise to detect and stop their attack. That is evidence about victims’ experience, not the prevalence of attacks across U.S. campuses. [Sophos](https://www.sophos.com/en-us/blog/state-of-ransomware-in-education-2026)

Identity protection now connects cybersecurity directly to enrollment and financial operations. Federal Student Aid introduced real-time FAFSA identity-fraud screening on April 26, 2026. Its May guidance emphasizes institutions’ continuing responsibilities and coordination among admissions, financial aid, academic affairs, and disbursement processes. Federal screening does not remove local exposure. [Federal Student Aid](https://fsapartners.ed.gov/knowledge-center/library/electronic-announcements/2026-05-29/best-practices-institutions-prevent-fafsa-fraud-and-protect-title-iv-funds)

**Next 12–24 months.** I expect more convincing impersonation and greater pressure on account recovery, help desks, and payment workflows. Institutions should prioritize phishing-resistant authentication, timely removal of access, restricted administrative privileges, tested backups, and rehearsed restoration of critical services. Vendor failures belong in continuity exercises too.

Open-access and online institutions need fraud controls that preserve legitimate students’ ability to enroll and receive aid. Research universities must also protect sensitive research and complex collaborations. Small colleges should evaluate shared security operations and incident-response arrangements where they cannot sustain specialist coverage themselves.

**Questions now:** Can we restore registration, payroll, and teaching within acceptable time limits? Who can redirect payments or reset privileged accounts? How quickly can a legitimate student challenge an erroneous fraud flag?

## #3 — Sustainable technology spending

This ranks third because every other priority competes for the same money, staff, and implementation capacity. Maintaining an expanding collection of systems while launching new initiatives can undermine both reliability and innovation.

**Evidence.** EDUCAUSE’s July 2026 workforce report describes sustained staffing shortages, increasing work complexity, budget pressure, and reactive institutional responses. These conditions make execution capacity a strategic constraint. [EDUCAUSE workforce report](https://library.educause.edu/resources/2026/7/2026-educause-workforce-report-can-higher-education-break-the-cycle-of-reactivity)

Evidence of disciplined value measurement is weaker than adoption enthusiasm: only 13% of respondents to EDUCAUSE’s January 2026 study said their institution measured returns on work-related AI tools. This respondent survey should not be read as a census of institutions. [EDUCAUSE AI-at-work study](https://www.educause.edu/research/2026/the-impact-of-ai-on-work-in-higher-education)

**Next 12–24 months.** Renewal decisions, AI subscriptions, system replacements, and integration work will force choices about which services institutions can sustain. The most useful modernization may involve retiring duplicate applications, simplifying processes, and improving existing systems. Large replacements need a credible case for benefits, migration capacity, and operating costs after launch.

Leaders should compare full costs, including staff time, security, accessibility, integration, training, and eventual exit. Time saved becomes financial savings only when work and budgets actually change; it may instead improve service quality or release capacity. Both are valuable, but they require different evidence.

Tuition-dependent colleges face tighter tolerance for failed projects. Multi-campus systems may gain from shared platforms and procurement, while research institutions must distinguish essential specialization from unnecessary duplication.

**Questions now:** Which systems will we retire? What measurable outcome justifies each investment? Can our people deliver the approved portfolio, and what would switching suppliers cost?

## #4 — Digital accessibility

This ranks fourth because equal access is fundamental and the preparation window is concrete. Remediation spans thousands of materials and recurring publishing practices, making late action expensive and ineffective.

**Evidence.** An April 2026 Justice Department rule extended the ADA Title II web-accessibility compliance dates to **April 26, 2027**, for covered public entities with populations of 50,000 or more, and **April 26, 2028**, for smaller entities and special district governments. [DOJ extension](https://www.ada.gov/assets/pdfs/2026-ifr.pdf)

The technical standard remains WCAG 2.1 Level AA. For a state university, the relevant population generally follows the governmental entity; it is not student enrollment. DOJ’s guidance also addresses content inventories, vendor contracts, training, and remediation. [DOJ implementation guidance](https://www.ada.gov/resources/web-rule-first-steps/)

**Next 12–24 months.** Institutions will need to move from isolated accommodations and website scans to sustained management of accessible digital services. Priorities include course materials, application forms, documents, video, learning platforms, and mobile applications. Procurement and content creation must prevent new barriers while existing ones are removed.

The specified deadlines concern public entities. Private institutions still have applicable disability-access obligations, including Section 504 for recipients of federal financial assistance; they should not treat the public-sector extension as permission to defer access. [DOJ disability-rights guide](https://www.ada.gov/resources/disability-rights-guide/)

Large decentralized universities face coordination problems; smaller colleges may lack remediation expertise. Both need named content owners, faculty support, usable templates, and testing with assistive technologies and disabled users.

**Questions now:** Which date and requirements apply to us? Can students independently complete essential tasks? Who owns inaccessible course content and vendor remediation, and is the work funded?

## #5 — Trusted data and accountable AI

This ranks fifth because reliable institutional information is becoming the foundation for both better decisions and more consequential automation. Its importance is high, but deployment maturity and exposure vary substantially among institutions.

**Evidence.** In EDUCAUSE’s 2026 AI-at-work study, 56% of respondents reported using tools their institution did not provide, while only 54% knew of policies or guidelines governing work-related AI use. These findings expose a gap between individual practice and institutional oversight. [EDUCAUSE](https://www.educause.edu/research/2026/the-impact-of-ai-on-work-in-higher-education)

The emerging development is software that can act across systems. NIST’s 2026 AI Agent Standards Initiative and draft identity-and-authorization concept paper address interoperability, permissions, delegation, and auditability. These are developing efforts, not a completed guarantee of agent safety. [NIST initiative](https://www.nist.gov/artificial-intelligence/ai-agent-standards-initiative), [NIST draft concept paper](https://www.nccoe.nist.gov/sites/default/files/2026-02/accelerating-the-adoption-of-software-and-ai-agent-identity-and-authorization-concept-paper.pdf)

**Next 12–24 months.** I expect more campus systems to offer assistants that retrieve records, draft decisions, or execute workflows. Institutions should require clear data ownership, current authoritative information, access restrictions, retention rules, and logs showing what happened. Contracts should address institutional data use, model training, portability, and responsibility when systems fail.

Start with bounded, measurable tasks. Admissions, aid, grading, employment, and disciplinary decisions require explicit human accountability and a meaningful correction process. A chatbot giving incorrect information and an agent changing a student’s record present different risks.

Decentralized research universities need coordination across laboratories and administrative units. Smaller colleges need practical shared standards that staff can actually apply.

**Questions now:** Which information is authoritative? What may an AI system read or change? Who approves consequential actions, checks outcomes, and can halt or reverse automation?

## #6 — Connected student services

This ranks sixth because technology can help institutions retain students and serve changing populations, but results depend heavily on service design and human capacity.

**Evidence.** WICHE projects declining numbers of high-school graduates after the 2025 peak, with substantial geographic differences. Yet National Student Clearinghouse estimates show spring 2026 enrollment increased 1.0% overall and 3.1% at community colleges. Leaders should plan for their own market rather than assume uniform contraction. [WICHE](https://www.wiche.edu/resources/knocking-at-the-college-door-11th-edition/), [Clearinghouse](https://nscresearchcenter.org/final-spring-enrollment-trends/)

Technology alone does not establish impact. A randomized MDRC/CCRC evaluation found that enhancements to existing technology-supported advising at three colleges did not improve academic outcomes. Although published in 2020, this remains a useful warning about equating more messages and alerts with better support. [MDRC/CCRC](https://www.mdrc.org/sites/default/files/iPASS_Final_Report_December_2020.pdf)

**Next 12–24 months.** Enrollment competition and service expectations will increase the value of timely, coordinated help with applications, financial aid, transfer credit, registration, and course planning. Institutions should connect these workflows so students receive consistent information and staff can resolve problems across offices.

Community colleges and regional universities should emphasize transfer, returning adults, part-time study, and pathways between short programs and degrees. Online institutions need accessible support outside conventional hours. Selective universities may prioritize different barriers, including graduate and international-student processes.

Investment should follow observed points where students abandon or delay essential tasks. Predictive systems need evaluation for accuracy and unfair treatment, plus staff able to act on findings. Retain straightforward access to a person.

**Questions now:** Where do students get stuck? Does an alert lead to a useful intervention? Are completion and persistence improving for the students we intended to help?

## #7 — Career preparation for changing work

This ranks seventh because curriculum and career pathways need action now, while the scale and timing of labor-market disruption remain less certain than the preceding operational requirements.

**Evidence.** An August 2026 Stanford working paper identifies weaker employment growth among young workers in AI-exposed occupations, driven principally by reduced hiring. The authors characterize the findings as descriptive rather than causal and find no economy-wide displacement. Meanwhile, NACE’s spring employer survey projected increased graduate hiring. Neither supports a simple prediction that entry-level work is disappearing everywhere. [Stanford](https://digitaleconomy.stanford.edu/app/uploads/2026/08/Canaries_August2026.pdf), [NACE](https://www.naceweb.org/talent-acquisition/trends-and-predictions/employers-expect-to-hire-5-point-6-percent-more-new-college-graduates-this-year)

Undergraduate certificate enrollment grew 10.2% in spring 2026. The 2026 Workforce Pell final rule creates support for qualifying short programs, subject to approvals and outcome requirements. Together, these developments raise the importance of trustworthy credential records, program reporting, and pathways into further education. [Clearinghouse](https://nscresearchcenter.org/final-spring-enrollment-trends/), [Department of Education final rule](https://www.govinfo.gov/content/pkg/FR-2026-05-19/pdf/2026-10013.pdf)

**Next 12–24 months.** I expect employers’ task requirements to shift faster than formal degree structures. Departments should review actual work practices with employers, update discipline-specific technology skills, and preserve foundational knowledge, judgment, communication, and verification skills.

Community and technical colleges will face immediate opportunities and reporting demands around short programs. Four-year institutions should strengthen internships, applied projects, and evidence of graduate capabilities. Research universities must also prepare graduate students for changing research and professional workflows.

The goal is demonstrable competence. A new badge or AI course title does little unless employers understand what it certifies and students can use it toward further learning.

**Questions now:** Which entry-level tasks are changing in our graduates’ fields? Where will students gain supervised experience? Which credentials have demonstrated employment value and meaningful credit pathways?

## Cross-Cutting Observations

- **People and process determine value.** Faculty development, specialist staffing, service redesign, and clear ownership are recurring prerequisites. Adding software without changing how work happens can increase costs and complexity.
- **Trust requires evidence.** Learning gains, successful recovery, accessible tasks, reliable decisions, and student completion matter more than adoption counts. Each major investment needs an outcome measure and a review date.
- **Shared foundations connect the priorities.** Identity, dependable data, accessibility, integration, and vendor oversight should be designed together. An institutional assistant inherits weaknesses in every system it touches.
- **Institutional differences matter.** Mission, finances, research intensity, student populations, and geography should determine sequencing. Shared services and consortia deserve consideration where individual institutions cannot sustain necessary expertise.

## What Might Be Underestimated

- **Research computing access.** NSF’s September 2026 establishment of a national AI research-resource operations center signals a more durable shared infrastructure. Computing access, research software expertise, and data stewardship could reshape research competitiveness. This belongs higher at research-intensive institutions; its uneven reach keeps it outside the sector-wide seven. [NSF](https://www.nsf.gov/cise/updates/nsf-establishes-operations-center-national-artificial)
- **Post-quantum migration.** NIST’s standards are available, and the agency urges migration planning. Universities should inventory cryptographic dependencies and ask suppliers for transition plans, especially for information needing long-term confidentiality. The uncertain timing of powerful quantum computers lowers its immediate ranking, but preparation can take years. [NIST](https://www.nist.gov/pqc)
- **Power and cooling constraints.** Berkeley Lab’s 2024 national study projects substantial growth in data-center electricity demand through 2028. These are scenarios, not observed 2028 consumption. Local power availability, cooling, and utility costs could constrain campus computing plans; exposure is more geographically concentrated than the seven main priorities. [Berkeley Lab](https://eta-publications.lbl.gov/sites/default/files/2024-12/us_data_center_energy_usage_report_lbnl-2001637_0.pdf)

## Sources

Principal sources used below; dates distinguish publication from the period measured. All were consulted on September 24, 2026.

1. **Gallup**, April 1, 2026. [AI Is Routine for College Students, Despite Campus Limits](https://news.gallup.com/poll/704090/routine-college-students-despite-campus-limits.aspx). Survey fielded October 2025.
2. **Kestin et al., Scientific Reports**, June 3, 2025. [AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational setting](https://www.nature.com/articles/s41598-025-97652-6).
3. **Bastani et al., PNAS**, June 25, 2025, online publication. [Generative AI without guardrails can harm learning: Evidence from high school mathematics](https://pubmed.ncbi.nlm.nih.gov/40560616/).
4. **Sophos**, 2026. [The State of Ransomware in Education 2026](https://www.sophos.com/en-us/blog/state-of-ransomware-in-education-2026). Survey fielded January–March 2026.
5. **Federal Student Aid**, May 29, 2026. [Best Practices for Institutions to Prevent FAFSA Fraud and Protect Title IV Funds](https://fsapartners.ed.gov/knowledge-center/library/electronic-announcements/2026-05-29/best-practices-institutions-prevent-fafsa-fraud-and-protect-title-iv-funds).
6. **EDUCAUSE**, July 20, 2026. [2026 EDUCAUSE Workforce Report: Can Higher Education Break the Cycle of Reactivity?](https://library.educause.edu/resources/2026/7/2026-educause-workforce-report-can-higher-education-break-the-cycle-of-reactivity). Public report overview.
7. **EDUCAUSE, with AIR, NACUBO, and CUPA-HR**, January 12, 2026. [The Impact of AI on Work in Higher Education](https://www.educause.edu/research/2026/the-impact-of-ai-on-work-in-higher-education). Survey fielded September–October 2025.
8. **U.S. Department of Justice**, effective April 20, 2026. [Extension of Compliance Dates for Nondiscrimination on the Basis of Disability; Accessibility of Web Information and Services of State and Local Government Entities](https://www.ada.gov/assets/pdfs/2026-ifr.pdf).
9. **U.S. Department of Justice**, January 8, 2025; updated to reflect the April 2026 extension. [State and Local Governments: First Steps Toward Complying with the Americans with Disabilities Act Title II Web and Mobile Application Accessibility Rule](https://www.ada.gov/resources/web-rule-first-steps/).
10. **U.S. Department of Justice**, February 28, 2020. [Guide to Disability Rights Laws](https://www.ada.gov/resources/disability-rights-guide/).
11. **NIST**, February 17, 2026; updated August 14, 2026. [AI Agent Standards Initiative](https://www.nist.gov/artificial-intelligence/ai-agent-standards-initiative).
12. **NIST/NCCoE**, February 2026. [Accelerating the Adoption of Software and AI Agent Identity and Authorization](https://www.nccoe.nist.gov/sites/default/files/2026-02/accelerating-the-adoption-of-software-and-ai-agent-identity-and-authorization-concept-paper.pdf). Draft concept paper.
13. **WICHE**, December 2024. [Knocking at the College Door: Projections of High School Graduates, 11th Edition](https://www.wiche.edu/resources/knocking-at-the-college-door-11th-edition/).
14. **National Student Clearinghouse Research Center**, June 4, 2026. [Final Spring Enrollment Trends](https://nscresearchcenter.org/final-spring-enrollment-trends/).
15. **MDRC/Community College Research Center**, December 2020. [Using Technology to Redesign College Advising and Student Support: Findings and Lessons from Three Colleges’ Efforts to Build on the iPASS Initiative](https://www.mdrc.org/sites/default/files/iPASS_Final_Report_December_2020.pdf).
16. **Brynjolfsson, Chandar, and Chen, Stanford University**, August 2026. [Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence](https://digitaleconomy.stanford.edu/app/uploads/2026/08/Canaries_August2026.pdf). Working paper; payroll data through June 2026.
17. **National Association of Colleges and Employers**, April 15, 2026. [Employers Expect to Hire 5.6% More New College Graduates This Year](https://www.naceweb.org/talent-acquisition/trends-and-predictions/employers-expect-to-hire-5-point-6-percent-more-new-college-graduates-this-year).
18. **U.S. Department of Education/Federal Register**, May 19, 2026. [Accountability in Higher Education and Access Through Demand-Driven Workforce Pell: Pell Grant Exclusion Relating to Other Grant Aid; and Workforce Pell Grants](https://www.govinfo.gov/content/pkg/FR-2026-05-19/pdf/2026-10013.pdf). Final rule.
19. **National Science Foundation**, September 1, 2026. [NSF establishes operations center for the National Artificial Intelligence Research Resource](https://www.nsf.gov/cise/updates/nsf-establishes-operations-center-national-artificial).
20. **NIST**, current resource page, accessed September 24, 2026. [Post-quantum cryptography](https://www.nist.gov/pqc).
21. **Lawrence Berkeley National Laboratory**, December 2024. [2024 United States Data Center Energy Usage Report](https://eta-publications.lbl.gov/sites/default/files/2024-12/us_data_center_energy_usage_report_lbnl-2001637_0.pdf).