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

In Boulder and across Colorado, pilots at UNC and CU Boulder show generative AI can boost student engagement and accessibility while exposing accuracy, usability and policy gaps - local reporting documents classroom experiments and educator concerns (KUNC report: AI in Colorado classrooms), and national coverage finds instructors increasingly using ChatGPT in course materials (New York Times: professors using ChatGPT in college courses).

That mix of promise and risk means routine education roles (TAs, graders, registrar clerks) face change, while oversight, accessibility and curriculum design grow in value; as one local advocate warned,

“It'll definitely be a net good. But the question is, is it going to be so good?”

For Boulder educators and staff looking to reskill, Nucamp's AI Essentials for Work program teaches practical prompt-writing and applied AI skills to shift into higher-value work (Nucamp AI Essentials for Work bootcamp - prompt writing and applied AI skills).

Our methodology combined local evidence, higher‑ed policy analysis, and practical adaptation guidance to identify the five Boulder education jobs most at risk from AI: we reviewed regional job postings and role descriptions (e.g., teaching assistant, tutors, library data consultants that list Generative AI familiarity) to measure task exposure and wage/hours vulnerability (UNC student job postings for teaching assistants and tutors); we examined university ethics and faculty guidance to capture policy, academic‑integrity risk, and instructor response - critical for roles tied to grading and assessment (UNC policy: the ethics of students using ChatGPT); and we cross‑checked implementation roadmaps and local audits to map realistic reskilling pathways for Boulder staff (Nucamp AI Essentials for Work bootcamp syllabus and AI adoption roadmap).

We treated faculty training, task automability, and local policy as primary criteria:

“We don't want witchhunts for AI generated writing. What we need to do is work with the students so they know when it's appropriate to use ChatGPT and when it's not.”

Teaching assistants (TAs) in Boulder are among the most exposed campus roles because generative AI already handles routine FAQs, draft feedback, slide generation and parts of formative grading - activities UNC's faculty guidance warns must remain instructor‑supervised and documented (UNC Chapel Hill generative AI teaching usage guidance).

National risk assessments show classroom AI assistants can boost TA productivity but also deliver biased or inaccurate recommendations unless a human stays in the loop, so local departments should require review workflows and clear syllabus disclosure (Common Sense Media report on risks of AI teacher assistants).

“Tools are popular and save teachers time, but risks arise when used without oversight.”

Practical adaptation for Boulder TAs means shifting from repetitive grading to higher‑value tasks - mentorship, oral assessments, accessibility checks, and AI‑validation - paired with training in prompt design and tool auditing; districts and campuses can follow a local AI adoption roadmap and reskilling pathway to implement these changes (Nucamp AI Essentials for Work bootcamp registration and syllabus).

Adjunct instructors and freelance course‑content writers in Boulder face immediate pressure as generative AI can rapidly draft lectures, quizzes, and module text that departments or online program managers may accept - an issue captured when a student found a professor's ChatGPT prompt in course notes and complained,

“He's telling us not to use it, and then he's using it himself.”

To manage risk locally, Colorado adjuncts should combine clear syllabus policies and AI‑literacy practices (don't ban; teach safe use and citation), adopt prompt‑validation workflows, and shift toward high‑value tasks - customized assessment design, multimedia assignments tied to local events, accessibility remediation, and human review of AI outputs - advice echoed in institutional guidance for instructors.

Practical campus recommendations and tool lists are summarized in Montclair State's teaching resources for AI, while national reporting shows how faculty use of ChatGPT is reshaping expectations for course authorship; workforce research also flags broad demand for AI preparation among students and employers.

For Boulder educators, reskilling paths include prompt engineering, RAG-based content validation, and curriculum auditing so adjuncts remain authors and editors rather than mere content deliverers (New York Times article on professors using ChatGPT, Montclair State University practical AI teaching responses, ASCCC November 2024 Rostrum on AI in community colleges).

Accessibility specialists and image‑description staff in Boulder remain indispensable because classroom pilots at UNC and CU Boulder show image‑captioning AIs (CoPilot, Be My Eyes' AI feature) can be helpful yet frequently hallucinate, omit critical details, or break screen‑reader workflows - problems that create real safety and equity risks for students with disabilities (UNC and CU Boulder AI accessibility classroom study - Longmont Leader).

Rather than compete with automation, local specialists should pivot to auditing and validating machine descriptions, building verification checklists, conducting VoiceOver and assistive‑tech walkthroughs, and curating contextual metadata for campus‑specific symbols and people - tasks that require human judgment and local knowledge.

“Anyone working within technology, whether you're developing or you're designing, you need to have an understanding of every single type of person that is using technology, not just people that can have all five senses,”

Practical Boulder steps include deploying automated accessible lecture summaries where they reliably help students, then pairing them with human QA and retrieval‑augmented validation; see examples of automated study guides for accessible summaries and a staged adoption plan for schools to follow (Automated study guides for accessible lecture summaries in Boulder - example guides, Boulder schools AI adoption roadmap and accessibility checklist - staged plan).

Registrar clerks and administrative customer‑service staff in Colorado face significant task‑level exposure as scheduling, transcript processing, routine eligibility checks, and common inquiries are increasingly automatable - but the registrar's office also stewards FERPA‑protected records, so any deployment demands strong governance, privacy review, and human oversight.

National practitioner guidance stresses caution: registrars should “start with the business need” and consider intelligent automation (rule‑based workflows) before energy‑intensive generative models, adopt Fair Information Practice Principles for data use, and require procurement and legal review for third‑party AI tools - advice summarized in AACRAO guide: Artificial Intelligence in the Registrar's Office.

At the same time, Microsoft's AI in Education research highlights that leaders and educators are already using AI to boost operational efficiency but need clear policies and training in practice, as detailed in the Microsoft AI in Education report: insights on policy and training, so Colorado offices should pair modest automation pilots with staff reskilling in data governance, prompt auditing, and escalation rules.

Practical local resources and staged adoption plans can help registrars shift from transactional processing to higher‑value roles - policy, compliance, and student casework - using a localized guide such as the Boulder AI adoption roadmap for K-12 and higher education (2025).

“It's amazing how ChatGPT knows everything about subjects I know nothing about, but is wrong, like 40% of the time about things I'm an expert on.”

Test graders and data‑entry staff in Boulder are among the most exposed roles because automated assessment tools and intelligent OCR already handle bulk scoring and routine record work; research finds auto‑grading is highly effective for structured items while AI‑assisted grading can help with open responses but brings bias, transparency, and fairness concerns, so universities should favor hybrid workflows rather than wholesale replacement (Ohio State University report on AI and auto-grading in higher education).

Practical local pathways shift workers from transaction processing into higher‑value oversight: auditing AI outputs, designing robust assessment rubrics, running retrieval‑augmented validation, and owning data governance and FERPA compliance; Nucamp's Boulder examples and staged adoption guides show how automated study guides and targeted training can make that transition feasible (Nucamp AI Essentials for Work syllabus and automated study guides).

Policymakers and institutions should heed critiques about over‑automation and lowered standards to preserve educational quality as tasks shift away from human graders (Analysis of education automation and lowered standards).

Conclusion: Next Steps for Boulder Educators and Administrators - Colorado should move from discussion to coordinated action by using the state's collaboratively built Colorado Roadmap for AI in K‑12 Education as a policy scaffold, pairing district pilots with clear privacy and FERPA review, rubriced human‑in‑the‑loop workflows for grading and accessibility, and explicit syllabus language for AI use; equip staff through targeted professional development such as the aiEDU professional learning resources for educators.

Prioritize accessibility QA, registrar data governance, and staged automation pilots that emphasize validation and student equity, while offering reskilling pathways into oversight roles - prompt design, RAG validation, and audit workflows - for affected workers.

“AI literacy should be a basic component of every student's education.”

For Boulder practitioners seeking practical training, consider applied programs that teach promptcraft and workplace AI skills: Nucamp AI Essentials for Work bootcamp (AI skills for the workplace, 15 weeks).

Implement quickly, evaluate often, and center human judgment and accessibility as Colorado scales AI across campuses.