How AI Is Reshaping Higher Ed Careers, and What M.Ed. Professionals Should Do Next

Is AI shrinking the job market or growing it? Both, depending on the track. Indeed.com research found machine-learning engineer postings up 59 percent by 2025, while general IT postings remain below their early-2020 level, according to a GovTech opinion piece by Jim A. Jorstad published October 9, 2026.

For M.Ed. students, certification candidates and those planning education major career paths, the question is not which code to learn. It is where teaching and leadership roles sit in a market that pays for AI fluency.

The same piece treats education and human development as comparatively safe, hands-on work, yet expects those jobs to use AI tools daily.

The Two-Track Job Market: What the Latest AI Labor Data Says

The AI labor market is splitting in two: specialized AI work is growing while general IT hiring stalls. The numbers behind that split are more nuanced than most headlines suggest.

What the Opinion Piece Reports

Jim A. Jorstad's October 9, 2026 opinion piece in GovTech cites Indeed research showing machine-learning engineer postings up 59 percent by 2025, while overall IT postings remain below their pre-pandemic level of early 2020. He also points to CompTIA's State of the Tech Workforce report, which projects modest IT job market growth in 2026. He adds that senior AI engineers earn a premium over non-AI peers, and that the gap appears to be widening.

What the Primary Sources Confirm

• Indeed Hiring Lab: The 59 percent figure holds, but the baseline matters. As of July 30, 2025, U.S. machine-learning engineer postings were 59 percent above early-2020 levels and still 47 percent below their early-2022 peak.¹ That is not a one-year jump.
• CompTIA 2026: Net tech employment fell 0.3 percent in 2025 (about 33,624 jobs) and is projected to grow 1.9 percent in 2026, adding 185,499 jobs.² In January 2026, more than 275,000 active U.S. postings referenced some level of AI skill, ranging from dedicated AI engineers to roles that simply require AI fluency.²
• Pay premium: CompTIA estimates a $112,805 median salary across tech occupations, more than double the all-occupation median.³ Its materials do not isolate a premium for AI skills, however. The senior AI engineer premium appears in the opinion piece, not the primary report, so treat it as an observation rather than a measured figure.
• IT postings below 2020: We could not match this broad claim to a specific primary-source figure. Read it as the author's characterization.

Why This Matters for Educators

Two tracks emerge: narrow technical specialties that recover and pay well, and routine IT and support work under pressure. Educators sit on the stronger side of the education job growth comparison. The same source places education and human development among the safer categories, and the people who teach, design instruction and certify the workforce are the ones every AI-era role depends on. For M.Ed. graduates, the task is not to retrain as engineers; it is to become fluent users of the tools their students and colleagues are already adopting. That fluency is central to high-paying AI careers in education and to the work shaped by a Master's in Higher Education.

Which Roles Are at Risk and Which Are Safer Bets

Nurse practitioners top a list of 65 occupations that U.S. Career Institute ranked as least likely to be lost to AI, with projected growth of 40 percent from 2024 to 2034 and a median wage of $129,210.¹ The online school's list matters less for its headline jobs than for what it implies about the work educators train people to do.

Jobs Named as At Risk

The source names three kinds of work as candidates for elimination by AI:

• Simple data entry
• IT and general call centers
• General accounting

All three involve repetitive, rule-bound tasks. That is the common thread, not the field itself.

What the Lowest-Risk List Is, and Is Not

The U.S. Career Institute list is a vendor-published ranking, not a government forecast. It draws on automation-risk scores from the "Will Robots Take My Job?" site, which builds on Oxford University's occupational-automation methodology. The company kept occupations scored at 0.0 percent and ordered them by projected 2024 to 2034 growth in Bureau of Labor Statistics data. So the order reflects job growth among low-risk roles. It does not prove any job is immune to AI.

Physician assistants rank second (20 percent growth, $133,260 median). Nursing instructors and post-secondary nursing teachers rank third, at 17 percent growth and a $79,940 median wage.¹

Where Education Fits

Education and human development appear among the hands-on categories the source treats as safer. Other teaching roles show up further down the ranking: post-secondary psychology teachers at 41, art, drama and music teachers at 57, social work teachers at 58, and K-12 education administrators at 63.²

The Practical Takeaway

The source expects these safer jobs to still use AI tools every day. For anyone preparing for Master's in Education Jobs, the task is not to avoid AI. It is to pair the human work of instruction, judgment and trust with routine, competent use of AI in the Classroom.

How AI Is Changing IT and Support Roles Inside Colleges and Universities

What the Adoption Data Shows

• Sourced evidence: EDUCAUSE's 2026 study of higher education workers, fielded in fall 2025, found 94% using AI tools and 73% using them daily or weekly. Yet 56% reported using tools their institution had not approved, and only 54% knew their institution's AI policies.
• Sourced evidence: The 2025 EDUCAUSE AI Landscape Study found 52% of institutions using AI to automate administrative workflows; just 2% had new funding for AI, so most work was absorbed by existing staff.² The 2026 EDUCAUSE Horizon Report found 37% holding an institution-wide chatbot license.³
• Sourced evidence: In the UK, Jisc found 86% of higher education institutions offered students AI guidance, against 49% of further education colleges.⁴

What the Data Does Not Show

Neither EDUCAUSE nor Jisc has published sector-wide figures on help desk ticket volumes, resolution times or headcount changes tied to AI. EDUCAUSE found no evidence of staffing cuts in help desk, academic technology or support teams. Smaller institutions were more likely to upskill current staff. Jisc likewise reports a shift in the work, not a reduction.

Where Tier-1 Work Is Moving

• Informed interpretation: Chatbots and automation are the likeliest candidates to absorb password resets, how-to questions and routine routing. That is a reasonable reading of the chatbot licensing trend, but the data does not yet confirm it.
• Sourced evidence: The work that grows is licensing, privacy, integrations, curriculum redesign support and AI-enabled advising.
• Informed interpretation: Policy gaps create openings. Only 13% of institutions measured AI return on investment, and the unapproved tool use above suggests nobody is yet guiding faculty well.

The Takeaway for M.Ed. Readers

If tier-1 support shrinks, the growth is in work that technology cannot settle alone: coaching faculty through new tools, designing learning that holds up when students use AI in the classroom, and writing policies people can follow. Those are teaching and leadership skills, and they are what an M.Ed. builds.

Related Articles

New Higher Ed Roles Where Education Meets AI: Titles, Duties, Qualifications and Pay

Job titles in this space vary widely by institution, and the same work may be posted as a strategist, director, coordinator or lead depending on the campus. Treat the salary figures below as indicative, not guarantees. Several come from individual 2026 job postings rather than national surveys, and where no authoritative published figure exists, the table says so.

What Instructional Designers Earn

Instructional design is a common landing spot for M.Ed. graduates moving into AI-era higher ed roles.

What AI Faculty Strategist and AI Institute Director Postings Actually Require

Indiana Tech's AI Faculty Strategist posting asks for a master's degree in a listed or related field plus five or more years of higher education teaching experience, with a doctorate listed as preferred. That single listing captures the pattern across this small, emerging category: a master's is enough at the coordinator and strategist level, while institute leadership almost always names a doctorate.

Where a master's is enough

Several postings set a master's as the floor. College of Charleston's Chief AI Officer role requires a master's with a PhD preferred.¹ Lander University's Associate Provost for AI and Director of its Center for Applied AI lists a master's alongside a doctorate and expects higher education administrative experience.² A Director of Curriculum Design and AI Integration posting asks for a master's in instructional design, curriculum and instruction, educational technology, higher education, computer science, AI or a related field, plus at least five years of progressively responsible work. A Director of AI for Academic Success listing offers two routes: a master's with at least three years in academic technology or AI-related initiatives, or a terminal degree with at least five years leading digital transformation work in higher education.³

Where a doctorate is expected

Research institute leadership is a different tier. Augusta University's Director of its AI Institute requires an earned doctorate, eligibility for appointment as Professor and a nationally recognized research record. Ohio State's Arts and Humanities AI Institute Director requires a terminal degree sufficient for tenure at Associate Professor or Professor. Texas Woman's University requires an earned doctorate plus faculty and leadership experience for its Chief AI Strategist.⁴ Notre Dame's Associate Director for Physical AI and Robotics requires a doctoral degree in any field with typically three to four years of experience.⁵

Required versus preferred

Doctorates frequently appear as preferred rather than required at the strategist level. Teaching experience shows up often, grant and external funding experience less so, and administrative experience is common in provost-adjacent roles. Note that few of these postings exist nationally, so treat these patterns as early signals rather than settled hiring norms.

From M.ed. to AI-Era Higher Ed Role: What Does a Typical Career Path Look Like?

Most educators reach AI-focused higher ed roles by climbing from course-level work to campus-level strategy. At each step, documented evidence of applied AI use matters as much as the degree itself. Pay varies widely by institution, so this path focuses on the credentials and proof that typically unlock each move.

Community College and Teaching-Focused Pathways

Community colleges are building AI capacity faster through training and grants than through new permanent hires, and that distinction matters for anyone planning a career there.

Where the Activity Is

The National Applied AI Consortium (NAAIC) launched in 2024 with a $2.8 million NSF Advanced Technological Education award, led by Miami Dade College, Houston City College and Maricopa Community Colleges.¹ Reports put its faculty and staff training at roughly 3,200 people,² and its own account cites more than 3,000 across 550 colleges and universities.¹ The sources do not say whether those participants are distinct individuals.

California's community college system lists AI fellows, ambassadors and a Nectir pilot reaching 84 colleges, more than 280 instructors and 8,000 students.³ It also requested $200 million for AI in 2026, including $40 million for staff and faculty development. That money was requested, not confirmed.

Elsewhere, Forsyth Technical Community College created 24 AI courses with a $916,000 award, according to Forsyth Community College AI Program reporting, and Central Georgia Community College received $4 million.⁴ Folsom Lake College offers AI and machine learning associate degrees and certificates.

How Colleges Differ

Community colleges lean toward applied teaching and workforce programs: course design, certificates, faculty training. Research universities more often house institute leadership and research roles. CUNY sits between the two. Its $3 million award backs more than 100 initiatives, including a Master of Science in Generative AI at the School of Professional Studies and a data science and AI bachelor's at Lehman College.⁵

Are AI Careers Growing There?

Partly. The 2026 evidence shows grants, pilots, fellowships and professional development. It does not show a national surge in permanent AI faculty or staff hiring, and no source here counts new full-time or part-time AI positions. Treat any claim of a hiring boom with caution.

Qualifications

Community college faculty roles usually require a master's degree, typically in the teaching field or a closely related one, as the community college teacher certification pathway explains. An M.Ed. paired with demonstrated AI course design or training experience is a credible route into the fellowship and instructional roles that are appearing.

Skills M.ed. Graduates Need to Stay Relevant

Machine-learning engineer postings rose 59 percent by 2025, according to Indeed.com research, but hiring spikes tied to specific technologies are not the signal M.Ed. graduates should chase. The safer investment is in skills that outlast any single product.

Durable Skills vs. Tool-Specific Skills

Tool-specific skills include knowing one chatbot's prompt syntax, one vendor's grading dashboard, or one learning platform's AI add-on. They are useful, and they expire when the vendor updates or the campus switches contracts. Durable skills describe judgment about teaching, learning, and risk. They carry across employers because every institution still has to decide how people learn, how work is assessed, and how student information is protected, whatever software is in use that year.

Six Durable Skills, With an Example Each

• AI literacy: Explaining to a faculty member why a chatbot can produce a confident but fabricated citation, and how to verify sources before they reach students.
• Assessment design: Replacing a single take-home essay with a staged project: proposal, draft conference, and short oral defense.
• Academic integrity: Writing a tiered guide that separates permitted AI use from misconduct, rooted in AI ethics in education, rather than relying on detection software alone.
• Data privacy: Knowing why student records should never be pasted into a public AI tool, and how FERPA shapes what a campus can approve.
• Accessibility: Checking that AI-generated materials include captions, alt text, and screen-reader-friendly structure before they go live.
• Faculty coaching: Sitting with an instructor to revise a syllabus AI policy so it matches the course's learning goals and to help ensure AI tools reduce teacher burnout rather than add to it.

Portfolio Evidence Employers Value

A list of skills on a resume is easy to write. Artifacts are harder to fake. Four items work well together:

• An AI-aware course redesign: a before-and-after outline showing which activities changed and why.
• An assessment that resists misuse: the prompt, rubric, and a short rationale explaining how it surfaces student thinking.
• A policy draft: a department-level AI use statement written for a real or realistic audience.
• A faculty workshop: slides, facilitation notes, and participant feedback from a session you actually ran.

Each artifact demonstrates several of the six skills at once, and none depends on a particular tool staying popular.

What This Means for M.ed. Programs and Teacher Certification

The biggest tradeoff in 2026 is whether a graduate program treats AI as a threaded instructional practice or a single bolt-on course. A program may look current on a website while still leaving graduates to figure out governance, bias, accessibility, and classroom use on their own.

What the programs actually require

Delaware's M.Ed. in Educational Technology asks for 33 credits and a 50-hour field practicum with seven assessments, and it aligns its rubrics to ISTE or AECT by career path. It does not explicitly require a dedicated AI course, however. Western Michigan University's fully online MA in Educational and Instructional Technology includes one required AI course and one AI elective.¹ Boston University's 30-unit M.Ed. in AI and Education takes a deeper route: seven core courses plus a two-unit capstone, though it does not include a separate teaching practicum or licensure field placement.

Employment outcomes are thin

Several programs list target roles such as instructional designer, e-learning developer, technology coach, curriculum developer, or learning-experience designer. East Texas A&M's competency-based M.Ed. in Instructional Design names similar paths.³ What the published materials generally do not show is placement rates, earnings, or year-one employment comparisons. Most of the employment evidence is occupational, not statistical. That does not mean the programs underperform; it means buyers should ask for program-level outcomes, including career outcomes data, rather than assume they exist.

Questions to ask before enrolling

• Curriculum: Is AI addressed across multiple courses in design, data, ethics, and evaluation, or only in one elective?
• Practicum or capstone: Does the required field experience or final project ask you to use AI in a real instructional setting?
• Accreditation alignment: Is the program approved by your state, aligned to ISTE or AECT, or carrying CAEP accreditation? These are not interchangeable. Georgia's M.Ed. in Learning, Design, and Technology holds Georgia Professional Standards Commission approval and can lead to a certificate upgrade,² but that approval is limited to Georgia. CAEP status is not stated for many programs.

A program that advertises one AI tool lesson or "ChatGPT for teachers" as its AI component is likely underserving you. Look for repeated practice in prompt design, bias and privacy review, accessibility, transparency, and human agency.

Teacher certification and AI

Certification and AI preparation overlap unevenly. State certification requirements are program- and state-specific, and teacher license reciprocity is not established. In many states, AI competency is still not a named certification standard. Treat any claim about AI certification readiness as something to verify against current state rules before you enroll.

Your 12-Month Action Plan, and How to Treat Predictions

Use the quarter-by-quarter plan below alongside the related articles on mastersineducation.org covering instructional design, community college careers and choosing an M.Ed. program. Treat every forecast with caution. Labor data shifts quickly: Indeed's reported 59 percent rise in machine-learning engineer postings and CompTIA's finding of modest IT job growth in early 2026 are snapshots, and published lists of AI-safe jobs are informed opinions, not guarantees, so revisit your plan each quarter and base decisions on current job postings rather than predictions.