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

Rochester schools are already feeling AI's ripple effects - Minnesota jumped to 17th in the nation for new AI job postings in education, according to a recent report, so this guide helps local educators and staff turn uncertainty into opportunity (KTTC report on AI impacts in the education workforce).

Rochester Public Schools is piloting practical tools like the VoteSmart RPS chatbot to field community questions, while district programs such as Project MOMENTUM are expanding teacher skills for a system that serves roughly 17,500 students (Rochester Public Schools news on Project MOMENTUM and AI initiatives).

With students leaning into AI and faculty asking for clear training and policy, practical upskilling matters - the 15-week AI Essentials for Work bootcamp lays out workplace-ready AI skills, prompts training, and applied exercises that match district needs (AI Essentials for Work bootcamp registration and program details).

“Not going to necessarily see huge job You're going to see a lot of need, I think, for upskilling right, people are going to need to have more effective understanding of how to use technology, right? And there's going to be a lot of new positions.”

Selections for the top five at-risk education jobs started with Microsoft's practical framework: researchers measured an “AI applicability” score by studying roughly 200,000 anonymized Copilot conversations and three lens-like metrics - how often AI is used for a task (coverage), how well it completes that task (completion rate), and how much of the job that task represents (impact scope) - so the shortlist favors roles where writing, routine communication, and information processing dominate.

That meant school-front-office and district communications duties, student records and enrollment clerical work, and analyst-style roles rose to the top because their day-to-day tasks map closely to what generative AI already does well; think of a steady stream of parent emails and form entries that an LLM can draft or summarize in seconds.

To keep this local, the study's signals were cross-checked against common education functions and Nucamp's applied-skills lens so the guide focuses on practical reskilling, not alarmism.

Read more on the underlying research in Microsoft's AI applicability study at Fortune (Microsoft AI applicability study at Fortune) and the Copilot conversation analysis and methodology from Final Round AI (Copilot conversation analysis and methodology).

“AI is about what types of jobs might find AI most useful, not about outright replacement.” - Kiran Tomlinson, Microsoft researcher

Customer service reps in school front offices face outsized exposure because their work - routing parent emails, answering routine attendance and enrollment questions, and triaging information - maps directly to what chatbots and large language models already do well; Microsoft's ranking names customer service among occupations with high AI applicability, and real-world examples show whole contact centers shrinking as automation takes routine queries (Fortune article on Microsoft generative AI occupational impact).

In Minnesota districts that rely on steady flows of messages, that means a front-office role can shift from drafting and data-entry tasks to supervising AI outputs, resolving escalations, and focusing on relationship-building - skills that the World Economic Forum flags as the human-first strengths that survive automation, and that can turn a potential cut into a career upgrade (World Economic Forum analysis on AI transformation of customer support jobs).

Adaptation starts with practical steps: learn basic AI oversight, get fluent in data literacy and prompt review, and document local workflows so AI can augment - not replace - human judgment; remember the striking image experts use: a customer service center that once employed 500 people might reconfigure into about 50 AI oversight specialists, so front-office staff who lean into oversight, escalation, and community trust will be the ones schools still need.

“AI is about what types of jobs might find AI most useful, not about outright replacement.”

Proofreaders and copy editors in district communications are squarely in AI's crosshairs because the routine tasks that once filled their days - mechanical copyedits, formatting references, and drafting boilerplate releases - are now the most profitable targets for generative tools, yet that same shift creates an opening: editorial work that relies on judgement, cultural context, and narrative trust becomes the premium service schools need.

Practical signals back this up - communications teams report heavy AI use for content creation and research, and many organizations are investing aggressively in Gen AI, so district editors who double down on higher-order skills (policy-driven transparency, nuanced local tone, ethical review, and AI oversight) can reposition themselves as indispensable guardians of voice and accuracy; readers can still tell the difference between a smooth, generic LLM voice and a piece edited for community context and equity.

Upskilling matters - start with structured AI training and documented AI-use policies so editing roles move from error-catching to strategic stewardship (see CIEP's editor perspectives on AI for editors and a roundup of generative AI stats and trends for 2025).

“We want our team to have every tool at their disposal that is going to make them efficient, optimized and smart,”

District data entry clerks - the people who keep student records and enrollment flowing - are among the most exposed to automation because their day is built on structured, repetitive tasks that optical character recognition (OCR) and intelligent capture can absorb; OCR can convert scanned forms and handwritten notes into searchable, editable records in minutes, and industry summaries estimate automation can cut manual data-entry work by roughly 80% (OCR's role in efficient data entry, 67 Data Entry Statistics for 2025).

For Minnesota districts that manage steady seasonal surges during enrollment, the practical response is to shift job descriptions from keystroke volume to oversight: validate AI-extracted fields, manage exceptions, and own privacy and compliance reviews so human judgment catches the subtle errors OCR misses; think of a clerk who previously typed forms now becoming the district's quality-control and data-governance specialist.

Workforce guides flag this transition as urgent but actionable - reskilling in intelligent-capture workflows, basic data literacy, and AI oversight preserves opportunity while trimming routine load (AI impact on administrative roles).

Paralegals and legal assistants who handle school compliance and HR in Minnesota are squarely in AI's crosshairs because much of their day - contract and policy review, FERPA/COPPA checks, personnel forms and routine legal research - maps to what generative tools automate best; experts warn AI could take as much as 40% of a typical paralegal workday while shifting human roles toward verification, policy oversight, and “legal prompt” work (Artificial Lawyer analysis of paralegal automation).

That means district teams should treat paralegals as the district's AI safety net: validate AI outputs, catch hallucinations (remember the high-profile sanction when fabricated ChatGPT citations slipped into a brief), and own data-privacy workflows so student records stay protected.

Practical adaptation combines technical chops (prompting, secure-tool use) with human strengths (judgment, client-facing communication and ethics), echoed in practical guidance for school leaders wrestling with legal risk and AI policy (MBM Law legal considerations for school administrators) and Clio's upskilling advice on how paralegals can refocus on higher-value, client-centered work (Clio upskilling advice for paralegals).

“A human (paralegal) interface with AI will be essential for the foreseeable future.”

Market research analysts who support enrollment and community engagement in Rochester are squarely in AI's path because their daily work - survey synthesis, social listening, and predictive enrollment modeling - matches the exact strengths of generative tools that can scrape, summarize, and forecast at scale; SG Analytics shows AI now turns what used to take weeks (think district-wide sentiment maps and competitive scans) into minutes, and Microsoft's occupational ranking flags market-research roles as highly exposed to LLMs (AI in education market trends and industry analysis).

The escape hatch isn't denial but reskilling: shift from data collection to strategic intelligence - architecting research systems, validating AI outputs, and translating patterns into action - exactly the role the Academy of Continuing Education calls “strategic intelligence” (learn prompt engineering, build dashboards, and design monitoring stacks to keep community voice front and center).

Practical steps for Rochester teams: master a small set of AI tools, document quality controls for sources and bias, and package insights as tight executive briefs that guide enrollment decisions and community outreach rather than raw spreadsheets.

“You're not going to lose your job to an AI, but you're going to lose your job to someone who uses AI.”

Rochester schools can move from anxiety to action with three practical next steps: adopt the Minnesota Department of Education AI in Education guiding principles to center people, equity, and privacy (Minnesota Department of Education AI in Education Resources); pilot low-risk training that pairs teachers and students - mirroring the University of Minnesota Rochester's approach where faculty require students to use AI for selective lab-report sections so learners see when AI helps and when human judgment is still essential (University of Minnesota Rochester AI case study: Leaning into the Unknown of AI); and invest in targeted upskilling - start with a practical program like the 15-week AI Essentials for Work bootcamp to build prompt-writing, oversight, and applied AI skills for non-technical staff (AI Essentials for Work bootcamp registration).

Pair these moves with clear local policies, small pilots that measure time-savings and accuracy (the St. Charles pilot expects teacher prep time reductions), and a plan to redeploy staff into oversight, equity review, and community-facing roles so technology augments trusted human work rather than replaces it.

"It's our responsibility as a school system to give them the skills that they're going to need."