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

Denver's education sector is at an AI inflection point because statewide strategies and rules are arriving at the same moment schools are piloting generative tools: Colorado's Office of Information Technology lays out a GenAI policy framed around governance, innovation and education, districts from Jeffco to Aurora are testing classroom assistants with mixed results, and state-level rules such as SB24-205 are reshaping procurement and oversight - creating clear efficiency gains (faster lesson drafts, translations, first-pass feedback) alongside real risks to instructional depth and equity.

For Denver educators and staff, practical upskilling is the immediate response: Nucamp's AI Essentials for Work bootcamp (15 weeks) teaches prompt design and workplace application, while Colorado's GenAI guide and local reporting on classroom pilots are essential references for choosing responsible tools and safeguards.

"Senate Bill 205 is one of the first of its kind in the United States to try to regulate artificial intelligence with the algorithms in mind." - Rep. Brianna Titone

The methodology combined task-level job analysis with local pilot evidence and legal guardrails: roles were scored by how many routine, automatable tasks they perform (e.g., scheduling, first-pass grading, translations), by documented tool performance in Denver pilots - most notably the multilingual chatbot Sunny, which deflected up to 35% of calls and completed nearly 95% of interactions for Denver families - and by exposure to student-data limits and classroom safeguards described in Nucamp's guides; see the Nucamp guide on using ChatGPT as a study companion with classroom guardrails (AI Essentials for Work syllabus and classroom guardrails), the Sunny case study on cost and efficiency impacts in Denver (Solo AI Tech Entrepreneur Denver chatbot case study), and the data-privacy overview for FERPA and COPPA considerations when deploying AI in Colorado schools (Cybersecurity Fundamentals: FERPA and COPPA data-privacy guidance).

K–12 classroom teachers face the clearest mix of risk and opportunity because routine, high-effort tasks - lesson planning, first‑pass assessments, and differentiation - are exactly what generative assistants like Microsoft Copilot can automate: Copilot can draft standards‑aligned lessons, create PowerPoint slides and map multi‑day plans in minutes, which Denver pilots and district trials are already testing in practice (Edutopia guide to using Microsoft Copilot for lesson plans, Microsoft 365 AI lesson planning guide).

Early evidence shows a real “AI dividend” for teachers - weekly AI users saved an average 5.9 hours per week (roughly six weeks per school year), a gain that could be redeployed to small‑group instruction or recovery time (The 19th article on teachers using AI and planning).

Caveats matter: researchers found AI‑generated lessons often default to lower‑order tasks and miss multicultural and technology‑rich opportunities, so effective practice is to drive lesson design and use AI to brainstorm, refine, and free time for higher‑order, equitable instruction.

“The teachers are innovating. They are trying to figure out how this can benefit their students, how it can benefit their educational practice and their teaching at school.” - Andrea Malek Ash

Curriculum content developers in Denver - those who draft standards‑aligned units, lesson sequences, and assessments - are already seeing AI shift from a slow collaborator to a first‑draft engine: generative tools can quickly unpack standards and produce multiple assessment options, but research and practice warn that speed can hollow substance.

Edutopia's supervisor guide shows how prompt-driven workflows can break a standard into clear learning goals and generate aligned assessment choices (Edutopia guide to AI‑assisted lesson planning), while an EdWeek analysis found AI plans disproportionately target lower‑order tasks (about 45% recall) and only about 4% prompt analysis or creation - so Denver districts that replace human curation risk lowering cognitive demand in core curricula (EdWeek study of AI lesson‑plan quality).

Practical adaptation: use AI to generate multiple, diverse assessment options, require designers to re‑engineer prompts for Bloom's higher levels, and invest in Level‑2/3 workflows (contextual inputs and custom GPTs) so AI amplifies, not erodes, rigorous, culturally responsive Colorado curriculum work.

“The teacher has to formulate their own ideas, their own plans. Then they could turn to AI, and get some additional ideas, refine [them]. Instead of having AI do the work for you, AI does the work with you.”

School administrative assistants - registrars, schedulers, and front‑office staff - face near‑term disruption because the exact tasks they do every day (scheduling, enrollment intake, record‑keeping, routine reporting) are already reliable targets for AI automation; practical pilots and vendor guides show these tools can both speed workflows and shift work upstream, so staff focus on exceptions and family support rather than form‑filling.

Vendors and researchers note AI systems that automate scheduling and enrollment reduce manual churn (Automating administrative processes in schools – XenonStack case study), while Microsoft Copilot trials report measurable time savings (St.

Francis College saw an average 9.3 hours saved per week) and Copilot scenarios promise 70–90% reductions on data analysis and report generation - concrete gains that could turn a full day of weekly clerical work into time for outreach or equity checks (Mastering Microsoft 365 Copilot in education – Microsoft Education blog).

Local Denver examples reinforce the point: the multilingual chatbot Sunny deflected roughly 35% of calls and completed about 95% of interactions for families, showing how frontline volume can move to automated channels if roles aren't redesigned (Denver multilingual chatbot “Sunny” case study).

So what: without intentional reskilling and process redesign, those reclaimed hours and efficiencies risk shrinking headcount; with them, administrative staff can become the human escalations and equity‑focused coordinators the district still needs.

"As St Francis College Principal John Marinucci observed, Copilot transforms education by expediting administrative tasks that often overwhelm educators, resulting in more energy and time for teaching."

Adjunct instructors and contract graders in Denver's community‑college circuit are among the most exposed to automation because the day‑to‑day task they perform - reading and scoring large volumes of student work - is exactly what modern systems can accelerate: automatic assessment tools excel at objective items and unit‑tested programming, while LLM‑powered, AI‑assisted grading can already produce first‑pass scores and feedback for essays at scale (AI and Auto‑Grading in Higher Education: capabilities, ethics, and evolving role of educators).

National trend analysis flags adjuncts who teach high‑enrollment survey and developmental courses as most at risk, even as new “AI‑native” campus roles emerge to oversee those systems (AI Impact on College Jobs Over the Next 10–20 Years).

For Denver adjuncts the practical implication is immediate: AI can shave grading hours (one TA reported using ChatGPT to handle 70–90 papers in a single run) but it also introduces bias, transparency and integrity concerns that require audits and human oversight; hybrid models - AI drafts plus instructor validation - are the recommended path, paired with targeted upskilling so part‑time faculty convert time savings into higher‑value mentoring and assessment design (AI‑Powered Teaching: practical tools for community college faculty).

“I had to grade something between 70 to 90 papers. And that was a lot as a full‑time student and as a full‑time worker.”

Denver's translators and interpreters sit at the sharp end of AI's push into language work: rigorous analyses show machine translation adoption correlates with falling translator employment and reduced demand for foreign‑language skills (CEPR analysis on AI's impact on translators and foreign-language skills), while advocacy groups and court experts warn that automated interpreting is still unreliable for high‑stakes, nuance‑dependent settings (American Translators Association warning on automated interpreting reliability) - the WHO's test of a commercial AI interpreter passed only 1 of 90 evaluations, a sharp reminder that accuracy failures can be consequential.

Practical adaptation for Denver: treat AI as an assistant, not a replacement, require human review in courts, health and IEP meetings, and scale local upskilling (for example MSU Denver Foundations of Translation and Interpreting course page) so bilingual staff convert time saved into higher‑value mediation, community outreach, and quality control rather than being sidelined by cost‑cutting automation.

“AI should not be used to replace human interpreters for real‑time interpretation in court due to risks with context, nuance, and errors.”

Colorado leaders and Denver school teams should treat the next 12–18 months as a policy and skills window: state law (SB22‑113) already bars new school contracts for facial‑recognition services through July 1, 2025, creating a legal pause districts can use to audit vendor risk, codify meaningful human review, and pilot governance procedures before scaling AI tools (Colorado SB22‑113 law on facial recognition in schools).

At the same time, Colorado's Digital Access initiative shows a pragmatic path to equity - its Digital Navigator pilot logged 1,730 navigator appointments (58% in the Denver metro area), signaling ready local capacity to close digital‑skills gaps and reach bilingual families as tools roll out (Colorado Digital Access & Empowerment Initiative Digital Navigator pilot).

Practical next steps: require human‑in‑the‑loop checkpoints for any classroom or administrative AI pilot, route reclaimed administrative time into student‑facing equity work, and enroll key staff in targeted, work‑focused reskilling (for example, Nucamp AI Essentials for Work bootcamp: registration and syllabus) to convert automation gains into higher‑value roles rather than headcount cuts.

The clear “so what?”: with statutory guardrails and local digital‑navigation capacity, Denver can choose whether AI amplifies human educators or quietly substitutes them - planning and reskilling decide the outcome.