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

Memphis school staff should track a national shift that's already underway: RAND found that in fall 2023, 18% of K–12 teachers were using AI for teaching and another 15% had tried it, while 60% of districts planned teacher training by the end of 2023–24 - signs that automated grading, adaptive content and administrative automation are moving from pilots to practice (RAND report on K–12 teacher AI use and adoption).

States and districts are running pilots and publishing guidance to manage benefits and risks (State education agency guidance and K–12 AI pilot programs), which means Memphis roles that handle grading, attendance, enrollment and routine lesson prep are most exposed.

Practical adaptation is possible: targeted reskilling - such as a focused, 15-week program - can teach prompt-writing and workplace AI workflows in months, not years; see the AI Essentials for Work syllabus and registration for a concrete pathway to preserve and upgrade local education jobs (AI Essentials for Work bootcamp syllabus and details).

“There are challenges with AI, but it has tremendous opportunity to improve the existing education system.”

Selection combined national usage data, common AI use cases, and local job-task mapping: the team prioritized roles that national surveys show are already being automated (Microsoft's 2025 AI in Education Report finds 86% of education organizations using generative AI, with student AI use up 26 percentage points and educator use up 21) and that align to frequent AI tasks - brainstorming and summarizing for students (37%/33%), lesson creation and simplification for educators (31%/24%), and operations/streamlining for leaders (35%) - then mapped those functions onto Tennessee job profiles most likely to perform routine grading, attendance, enrollment, payroll/bookkeeping, and media-center clerical work.

Each candidate role was scored for exposure to repeatable tasks, local demand in Memphis-area districts, and reskilling feasibility; priority went to roles where short, targeted training and workplace AI workflows (prompt-writing, Copilot use, and policy-aware deployment) can preserve jobs and shift workers into higher-value duties.

Read the full Microsoft findings and local guidance used to align criteria in the national report and in our Memphis adaptation guide for practical steps and compliance basics (Microsoft 2025 AI in Education Report, Complete Guide to Using AI in Memphis Schools).

“Teachers are saying, ‘I need training, it needs to be high quality, relevant, and job-embedded…' In reality, people require guidance and that means teachers and administrators going through professional development.” - Pat Yongpradit, Chief Academic Officer, Code.org/TeachAI

Administrative assistants and school office clerks in Memphis face immediate exposure as districts adopt AI and low‑code automation to cut routine work: state reporting shows more than 60% of Tennessee districts are already using AI to reduce teacher and operational workload and manage daily operations (Tennessee educator AI usage survey), and Memphis‑Shelby County Schools has deployed Microsoft Power Apps and Power Automate to auto‑populate forms, streamline reporting, and replace manual spreadsheets - tools that generated operational savings (a $300,000 behavior‑intervention app) and a compliance portal that saves schools an average of 20 hours a week (Memphis‑Shelby County Schools Power Apps case study).

So what: predictable, repetitive tasks like data entry, attendance logging and simple report generation can be automated now, which means clerical staff who learn prompt workflows, low‑code app management, and district privacy practices can shift into higher‑value roles supporting family communications, equity‑focused data checks, and AI governance; for districts planning pilots, see a step‑by‑step approach to test AI with minimal risk (Memphis education AI pilot planning guide).

“People who use AI are going to replace those who don't.”

District data‑entry, enrollment clerks, and payroll/bookkeeping staff in Tennessee are squarely in the path of automation: vendors and districts are replacing manual form transcription, file routing, and repetitive payroll tasks with secure, searchable workflows that push enrollment and HR records directly into the SIS and HRIS. Tools that automate student enrollment, records classification, and payroll approvals reduce transcription errors and accelerate state reporting - see Laserfiche's K–12 solutions for automating student enrollment and payroll workflows (Laserfiche K–12 workflow automation for student enrollment and payroll) - while data platforms that validate and sync across systems turn processes “that took one to two weeks” into minutes according to customer reports (Level Data K–12 data management and SIS integration).

The financial impact is concrete: automated invoice and TE&I automation can cut per‑invoice processing costs dramatically (from about $6.30 to $1.45 in IOFM comparisons cited by SAP Concur), meaning districts can reallocate tens of thousands of dollars and hundreds of staff hours to student‑facing supports rather than manual data cleanup (SAP Concur analysis of invoice automation savings).

So what: clerks who learn low‑code workflow management, SIS integration checks, and automated audit trails can pivot from keystrokes to stewardship - ensuring data accuracy, FERPA‑aware access, and faster family communications.

“Laserfiche is our Swiss Army knife. Whether we need to augment some other process or figure out how to input data - Laserfiche is our answer.” - Derek Moore

Paraprofessionals and instructional aides - who often deliver one‑on‑one and small‑group support in Tennessee classrooms - face both risk and opportunity as AI moves into tutoring and adaptive instruction: research shows AI that coaches the tutor (not the student) boosted overall mastery by about 4 percentage points and produced the largest gains for weaker or novice tutors (about a 9 percentage‑point improvement), meaning paraprofessionals who adopt AI coaching tools can materially increase student learning rather than be sidelined by automation (Tutor CoPilot study (EdWeek & Stanford research), NSSA summary of Tutor CoPilot research).

Tennessee's own tutoring practice notes - like TN ALL Corps' attendance challenges for out‑of‑school programs - underscore a practical takeaway: embed AI‑augmented tutoring during the school day and train aides in human‑in‑the‑loop skills (prompt workflows, curriculum alignment, FERPA‑aware documentation); AI can also power personalized special‑education supports (speech, adaptive paths, progress tracking) that paraprofessionals can manage with focused upskilling (AI for special education use cases (AbleSpace)), so the clear path is reskill to supervise and interpret AI rather than compete with it.

“It's not the tutor's background in education that makes tutoring successful. It's how you support the tutors with training and structure.” - Hannah Zey, Fulton County Public Schools

Teachers' assistants in Memphis who grade, prep lessons, and create content are highly exposed because AI can now grade objective assessments, draft differentiated lesson materials, and produce instant feedback - tasks that, when properly supervised, free classroom time for deeper student support (see research on AI teaching assistants at SchoolAI: research on AI teaching assistants at SchoolAI).

Yet a Common Sense–backed risk assessment covered by EdWeek found these tools can introduce hard‑to‑detect bias, mislevel texts, and generate problematic IEP drafts unless districts require teacher oversight and training (EdWeek coverage on AI teacher assistant reliability and risks).

So what: a Memphis TA who masters prompt‑writing, curriculum alignment checks, and FERPA‑aware review can pivot from repetitive grading into leading small‑group interventions, equity audits, and teacher‑assisted personalization - turning an at‑risk job into a higher‑value instructional role.

“As somebody who was a novice teacher once, speaking for myself, I was not aware of what I didn't know. Using an AI chatbot, you could see unintended consequences of a new teacher making decisions that could have long-term impacts on students.” - Robbie Torney, senior director of AI programs, Common Sense Media

Library and media clerks in Tennessee should watch two concurrent developments: machine learning can already handle straightforward bibliographic facts but struggles with controlled‑vocabulary subject work, and multilingual embedding workflows are making AI‑assisted subject recommendations practical for non‑English collections.

The Library of Congress' Exploring Computational Description experiment used ~23,000 ebooks and found transformer models reliably predicted titles, authors and some identifiers (one MARC field reached a 95% F1 threshold) while subject and genre prediction lagged (Annif ≈35% accuracy; LLMs ≈26%), underscoring that human‑in‑the‑loop (HITL) review remains essential (Library of Congress ECD metadata experiment results).

At the same time, multilingual FAST recommendation pipelines - built with embeddings and a vector database and tested on East Asian materials - can surface candidate headings from roughly 486,000 FAST records to speed cataloger review, not replace it (Multilingual FAST recommendation and embeddings for cataloging).

Ethical and privacy risks persist - participants at recent metadata forums warned about consent, bias, and deskilling - so clerks who learn HITL workflows, provenance checks, and privacy audits can move from repetitive tagging to supervising trustworthy, multilingual discovery systems (AI metadata management ethics and privacy concerns), preserving local jobs while improving access for diverse communities.

“Protecting privacy is crucial; patrons' reading habits are private.” - Kira Smith, Ask a Librarian

Start with a simple, local plan: audit daily tasks you handle (grading, attendance, enrollment, payroll, circulation) and map each to a mitigation - either human-in-the-loop review, equity checks, or an automated workflow - using the University of Memphis' curated guidance (UM3D Generative AI resources - University of Memphis guidance) and the UofM Libraries' AI research guide for ethics, tools, and classroom use (Artificial Intelligence in Higher Education - UofM Libraries AI research guide).

For concrete reskilling, consider a focused, 15-week pathway that teaches prompt writing, workplace AI safety, and practical workflows - Nucamp's AI Essentials for Work syllabus outlines a ready curriculum and registration options (AI Essentials for Work - 15-week syllabus and registration details) - early-bird tuition is $3,582 and can be paid in 18 monthly payments with the first payment due at registration.

So what: within a semester staff can shift from repetitive keystrokes to supervisory roles that enforce FERPA-aware access, run equity audits, and lead small-scale pilots; join campus AI communities (UM3D accepts resource submissions at um3d@memphis.edu) and test one low-risk automation (attendance or newsletter drafts) with clear oversight before scaling.