Top 5 Jobs in Education That Are Most at Risk from AI in Buffalo - And How to Adapt

Buffalo educators should pay attention to AI because the World Economic Forum Future of Jobs Report 2025 finds technological change will reshape roles nationwide - with 40% of employers expecting workforce reductions where AI automates tasks and millions of roles exposed to disruption by 2030 - meaning routine clerical and entry-level functions common in school systems are especially vulnerable (World Economic Forum Future of Jobs Report 2025).

Locally, Buffalo schools and edtech providers are already piloting AI tutors and wellbeing prompts that cut grading time and surface student needs faster (AI tutoring pilots in Buffalo improving grading efficiency and student support), so the practical next step for educators is targeted upskilling - Nucamp's short AI Essentials for Work bootcamp offers a 15-week pathway to use AI tools and write effective prompts for classroom and admin work (Nucamp AI Essentials for Work bootcamp - 15-week AI training for educators).

Without action, many staff may need retraining: the report estimates 59 of every 100 workers will require reskilling by 2030.

Methodology: the analysis began with the World Economic Forum's Future of Jobs Report 2025 - a global employer survey covering more than 1,000 companies and 14 million workers - to identify occupation families WEF flags as vulnerable (the report finds 86% of respondents expect AI and information processing to transform businesses and explicitly names clerical and administrative assistants among declining roles) (World Economic Forum Future of Jobs Report 2025).

Next, a task-based risk filter was applied: prioritize roles dominated by routine, rule-based tasks (scheduling, repetitive data entry, standardizable grading), where broadening digital access makes automation feasible.

That filter was cross-checked with Buffalo-specific signals from local Nucamp research and use cases - for example, pilot AI tutors and wellbeing prompts that are already cutting grading time and routing students to local resources - to confirm immediacy of local exposure (AI tutoring pilots and efficiency gains in Buffalo).

Roles scoring high on routineness, employer-intent (WEF survey evidence), and local adoption were ranked as most at-risk and prioritized for concrete upskilling recommendations.

One vivid takeaway: when 86% of employers anticipate AI-driven change, routine school-system tasks become the most actionable targets for retraining now.

School secretaries and payroll clerks in Buffalo are squarely in the automation crosshairs because their day-to-day work - attendance tracking, repetitive data entry, standard payroll reconciliation and routine scheduling - is rule-based and easily standardized; federal reporting flags those kinds of clerical tasks as most vulnerable to automation (GAO report on workers affected by automation).

The Board of Governors of the Federal Reserve finds 20–40% of U.S. workers already using AI at work, so school districts could soon adopt tools that speed record-keeping and error-checking the way tax-prep and electronic records have been automated (Federal Reserve report on AI uptake in the workplace).

Locally, Buffalo pilots that cut grading time show how rapid gains translate to back-office tasks too - meaning administrative roles face real near-term change unless districts pair technology rollout with targeted upskilling in digital process skills, credential programs, and wraparound supports recommended by workforce researchers (Buffalo AI tutoring pilots improving grading efficiency and student support); the practical “so what?”: proactive training can convert a potential job loss into an opportunity to manage and audit automated systems.

Registrar and scheduling clerks in K–12 and higher education face acute exposure because many core duties - campus-visit self-scheduling, application tracking, routine enrollment updates and automated decision notifications - are already features of modern student information platforms (Blackbaud higher‑education student data management and self‑scheduling platform), and analyses flag “Registrar Office Clerks” as among roles most likely to be replaced by AI-driven automation (list of jobs AI will replace - registrar clerks highlighted).

The practical consequence is concrete: when automated feeds or scheduling bots misroute a record or a faculty grade isn't reconciled, the registrar's office can lose the ability to certify graduation, probation status, or even trigger financial‑aid actions - outcomes already described in practitioner forums as high‑stakes if grades are missing (practitioner discussion on missed grade feeds blocking graduation and aid decisions).

So what: Buffalo registrars should prioritize hands‑on skills in data governance, audit logging and vendor workflow‑testing now, turning vulnerability into leadership over trustworthy automation rather than a downstream staffing crisis.

Adjunct tutors and grading assistants in Buffalo's colleges and dual‑enrollment programs are among the roles most exposed because routine, rubric‑driven scoring and first‑pass feedback are already automatable: higher‑ed analyses predict large‑enrollment survey courses will shift toward AI tutors overseen by fewer “master” instructors (Analysis of AI impact on college jobs over the next 10–20 years), while technical reviews of assessment tools show clear strengths and limits - auto‑grading excels at objective and code assignments, AI‑assisted grading can scale essay feedback but raises bias and transparency concerns, and hybrid human+AI workflows are the recommended guardrail (Research on AI and auto‑grading in higher education: capabilities, ethics, and evolving educator roles).

A recent study also found LLMs grade faster but rely on shortcuts unless guided by human rubrics, and instructors reporting less weekend grading is a concrete sign of time reclaimed - so Buffalo adjuncts should push for co‑designed rubrics, auditable workflows, and reskilling toward AI oversight and mentoring to convert grading time into higher‑value student support rather than face undefined workload cuts (UGA study: AI speeds up grading and reduces instructor weekend workload).

“Many teachers told me, ‘I had to spend my weekend giving feedback, but by using automatic scoring, I do not have to do that. Now, I have more time to focus on more meaningful work instead of some labor-intensive work,'”

Curriculum content creators and junior instructional designers in Buffalo face fast, tangible disruption: historically, crafting one hour of interactive course content took up to 10 hours, but generative AI now shortens that workstream to days by automating outlines, quizzes, video scripts, translations and basic assessments - so routine drafting is the immediate exposure point (2025 analysis of AI in course creation).

That pressure makes the practical “so what” clear: rather than compete with bulk content generation, local creators should specialize in AI oversight - designing auditable rubrics, prompt libraries, accessibility checks, and adaptive learning paths - and partner with campus teaching centers to push discipline‑specific standards and vendor vetting, a need highlighted by higher‑education research calling for institutional guidance, secure tools, and faculty training (Ithaka S+R findings on making AI generative for higher ed).

One concrete pivot: convert time saved by auto‑drafts into evidence‑based instructional design work - pilot adaptive modules, run bias checks on generated content, and document prompts so Buffalo districts control quality instead of outsourcing trust to black‑box vendors.

Imagine creating a quality online course in days from start to finish - that's now possible with AI.

Library technicians and classroom technicians in Buffalo should treat AI as a tool to move beyond routine tasks and toward systems-level work: library staff can learn how AI‑augmented Alma Analytics workflows are being taught at practitioner gatherings to turn raw circulation and usage logs into actionable service improvements (ELUNA 2025 AI and Alma Analytics session details), while classroom technicians can lead the integration and operational testing of AI tutors and wellbeing‑triage prompts already piloted locally to reduce grading load and surface student needs faster (Buffalo school mental health triage AI prompts case study, AI tutors grading efficiency in Buffalo case study).

So what: a modest, targeted investment in prompt design, analytics basics, and vendor testing can convert a role that once focused on shelving and AV setup into one that documents auditable AI workflows and competes for local funding and partnerships - concrete leverage highlighted in Buffalo's edtech guidance and funding guides.

Buffalo educators can take three practical steps now to limit disruption and shape how AI is used in local schools: (1) train quickly and purposefully - use New York's no‑cost Coursera access through the NYS Department of Labor to earn short AI and data‑skills certificates (eligibility for unemployed and underemployed NY residents) (New York State Department of Labor Coursera online learning); (2) join local practitioner forums that address ethics, privacy and classroom integration - University at Buffalo's AI + Education Learning Community Series runs monthly and covers data privacy, equity and vendor testing that districts must adopt as policy (University at Buffalo AI + Education Learning Community Series); and (3) pivot job roles from routine execution to AI oversight and prompt‑engineering by enrolling in targeted programs like Nucamp's 15‑week AI Essentials for Work bootcamp to learn prompt design, auditing workflows, and practical classroom applications (Nucamp AI Essentials for Work bootcamp registration).

The concrete payoff: staff who convert grading, scheduling and content drafting time into audited, vendor‑tested AI oversight will protect student outcomes and create new, higher‑value roles inside Buffalo districts.

“Many teachers told me, ‘I had to spend my weekend giving feedback, but by using automatic scoring, I do not have to do that. Now, I have more time to focus on more meaningful work instead of some labor-intensive work,'”