In a very active and highly competitive environment, AI has grown at breakneck speed. As with so many technologies, business and industry have moved far faster than academe to embrace the cost savings, capability expanding and wholly innovative aspects of AI. Fraught with our own industry-specific challenges such as enrollment downturns, sharp drops in perceived value, the striking “math cliff” in higher ed and a rapidly changing regulatory policy shift in state and federal administration, our field has been cast into a sea of pressing priorities for changes.

This year is likely to be the one where we begin to implement institutionwide AI-powered solutions to help us move forward with agility and effectiveness in adapting to the changing environment. As Aviva Legatt writes in Forbes’ “7 Decisions That Will Define AI in Higher Education in 2026”,

Yet, where these changes will take place within the field, how these changes will impact our higher education workforce and the extent to which we can change in time to meet our market demand by producing knowledgeable and skilled employees for the economy at large remains in question. For those of us in early and midcareer positions, pressing questions arise: “Will I still have a job? How will my position description change? Will I be prepared? What should I do now to ensure I remain a valuable asset to my university?” It is my purpose in this brief column to identify some of the areas in which changes seem most likely to take place in this new year.

To date, we have made significant progress in developing chatbot-hosted, transactional generative AI in which the user inputs questions and answers to the bot. One of the many high-quality examples is the Khan Academy’s Khanmigo. These have been effective in hosting tutors, study apps, curricular design and much more.

The use of generative AI continues to expand in new ways. Meanwhile, the development of AI agents is driving the expansion and efficiency of AI. In the agentic AI models, we have tools that are capable of reasoned assessment of what is needed to accomplish a goal, aligning a series of stacked tasks and completing those tasks without direct supervision in an efficient way, much like a human assistant would perform a series of tasks to achieve desired outcomes. For example, this often includes data collection, analysis of the data, identifying and implementing ways in which to accomplish the goals, documenting the findings, and finding better ways to accomplish the outcomes.

This opens the possibility that portions of individual position descriptions can be offloaded from humans and integrated into agentic AI duties. This results in fewer overall employees; lower indirect costs such as insurance, vacation and sick leave; and a more cost-efficient operation. Beginning now, institutions are moving from scattered pilots to governed, agentic workflows that will define the next decade of ensuring student success and operational efficiency.

I asked my virtual digital assistant, Gemini 3 Deep Research, on Dec. 28 to suggest some of the implementations we will most likely see broadly implemented to address the student lifecycle. Gemini suggested that the work will be “personalized, proactive and persistent.” Gemini 3 Thinking mode predicted we will see a wide range of implementations in 2026, including:

1. The 24/7 Digital Concierge (Recruitment): Beyond simple FAQs, agents now manage the entire “nurturing funnel,” handling complex credit transfer evaluations and scheduling campus tours via multichannel SMS and web interfaces. Source: 2026 Higher Education Digital Marketing Trends (EducationDynamics)
2. Socratic Tutors for Every Learner: AI tutors that don’t just give answers but engage in Socratic dialogue, scaffolding difficult concepts and generating infinite practice problems based on real-time course performance. Source: AI Tutors and the Human Data Workforce 2026 Guide (HeroHunt)
3. Mental Health First Responders: AI agents serving as low-barrier triage points, offering immediate coping strategies for anxiety and seamlessly escalating high-risk cases to human counselors. Source: How AI Chatbots Are Transforming Student Services (Boundless Learning)
4. Predictive Intervention for Gatekeeper Courses: Using “behavioral trace data” from LMS platforms to identify students struggling in high-risk introductory courses (e.g., College Algebra, Gen Chem) before the first midterm. Source: Predictive Analytics in Higher Ed: Promises and Challenges (AIR)
5. Admissions Document Verification Agents: Autonomous systems that verify international credentials, flag missing forms and check for eligibility in milliseconds, reducing the time to decision from weeks to minutes. Source: AI Agents for Universities: Automating Admissions (Supervity)

Gemini 3 Thinking mode continued with examples of back-office efficiencies that AI will provide to universities that are early adopters of an agentic AI approach:

6. Automated University Accounting: AI agents that handle invoice processing, general ledger coding and “smart” expense management, ensuring policy compliance without manual entry. Source: 5 Use Cases for AI Agents in Finance (Centric Consulting)
7. Grant Management and Writing Assistants: Agents that scan federal databases (Grants.gov) to match faculty research with funding, draft initial narratives and manage postaward financial reporting. Source: AI Grant Management: Driving Efficiency (Fluxx AI)
8. Dynamic Enrollment Marketing Agents: “Search everywhere optimization” (GEO/AEO) tools that ensure the university appears in AI-generated best-of lists and voice-search results on platforms like TikTok and Reddit. Source: Transitioning to the Agentic University 2026–27 (UPCEA)
9. Procurement and Spend Analysis: Agents that continuously monitor contract compliance and supplier health, identifying hidden savings that can be reallocated to student scholarships. Source: How AI Agents Change Procurement Work in 2026 (Suplari)
10. Regulatory Reporting and Audit Agents: Systems that autogenerate audit-ready reports for state and federal compliance, reducing the administrative burden on institutional research offices. Source: FINRA 2026 Oversight Report: The Reckoning for Autonomous AI (Snell & Wilmer)
11. HR and Benefits Support: 24/7 staff-facing agents that answer complex questions about leave policies, payroll and benefits, freeing HR staff for strategic culture-building work. Source: Agentic AI: Top Tech Trend of 2025/2026 (Gartner/EAB)
12. The “AI-First” Curriculum Redesign: Moving beyond academic integrity to “AI fluency” as a graduation standard, where agents help faculty redesign assessments to focus on process rather than product. Source: 2026 Predictions for AI in Higher Education (Packback)

Of course, there will be many comparable efficiencies implemented in other areas of universities. These are examples that demonstrate the cost and time efficiencies that can be realized through thoughtful implementation of agentic AI. In the Nov. 12 issue of this column, “Transitioning to the Agentic University 2026–27,” I detail an approach to begin the administrative agentic AI transition.

Although there is less mention publicly about direct instruction by AI, this is inevitable in coming years. Most likely AI-led instruction will begin in noncredit offerings, but ultimately no teaching task will be out of reach. It will come at a significantly lower cost, greater personalization and instant updating with every new development in the field as it happens.  How can we best prepare our colleagues in higher education for the changes that are coming this year and each successive year?