Develop instructional materials and products and assist in the technology-based redesign of courses. Assist faculty in learning about, becoming proficient in, and applying instructional technology.
U.S. Workers
210,850
Median Salary
$74,720
10-Year Growth
+1.3%
Annual Openings
21,900
Typical entry: Master's degree
23 of 23 tasks have some AI capability
Exposure Trend
This score reflects estimated AI technical capability for tasks in this occupation. It does not predict employment changes, and it does not account for company-specific constraints, regulation, or adoption barriers.
Present and make recommendations regarding course design, technology, and instruction delivery options.
AI: Fully automatable - AI can synthesize evidence, produce presentations, and generate tailored recommendations on course design, technologies, and delivery options at a professional level.
Define instructional, learning, or performance objectives.
AI: Fully automatable - AI can define clear, measurable instructional and performance objectives from standards, job analyses, and learning outcomes reliably and quickly.
Develop instructional materials and products for technology-based redesign of courses.
AI: Fully automatable - AI can develop instructional materials and digital products for course redesign, including multimedia content, assessments, and interactive assets, often producing ready‑to‑use artifacts.
Design learning products, including web-based aids or electronic performance support systems.
AI: Fully automatable - AI can design learning products such as web aids and electronic performance support systems by producing information architecture, content, interaction flows, and prototype code or specs.
Provide analytical support for the design and development of training curricula, learning strategies, educational policies, or courseware standards.
AI: Fully automatable - AI excels at providing analytical support—data analysis, research synthesis, modeling, and standards recommendations—for curricula, learning strategies, and courseware development.
Design instructional aids for stand-alone or instructor-led classroom or online use.
AI: Fully automatable - AI can produce high-quality slide decks, visuals, interactive modules and facilitator guides for classroom or online use end-to-end given inputs and constraints.
Develop instructional materials, such as lesson plans, handouts, or examinations.
AI: Fully automatable - AI can generate complete lesson plans, handouts, quizzes and exam items tailored to objectives and standards with minimal human input for many use cases.
Develop instruction or training roadmaps for online and blended learning programs.
AI: Fully automatable - AI can design detailed online and blended learning roadmaps (sequencing, modalities, milestones) from goals, constraints, and learner data.
Analyze performance data to determine effectiveness of instructional systems, courses, or instructional materials.
AI: Fully automatable - AI systems can analyze performance and learning-data at scale, identify patterns, and produce evidence-based conclusions about effectiveness with high reliability when data are available.
Adapt instructional content or delivery methods for different levels or types of learners.
AI: Fully automatable - AI can adapt content, scaffolding, pacing and modality to different learner levels and profiles automatically using personalization algorithms and content-generation capabilities.
Recommend instructional methods, such as individual or group instruction, self-study, lectures, demonstrations, simulation exercises, and role-playing, appropriate for content and learner characteristics.
AI: Fully automatable - By 2025 large language models and instructional design tools can analyze content and learner profiles to generate appropriate instructional method recommendations that are routinely useful, though human oversight may refine context-specific nuances.
Edit instructional materials, such as books, simulation exercises, lesson plans, instructor guides, and tests.
AI: Fully automatable - AI editing tools and models are capable of revising and polishing books, lesson plans, simulations, and tests for clarity, structure, and grammar, and can perform substantive edits with domain prompts.
Provide technical advice on the use of current instructional technologies, including computer-based training, desktop videoconferencing, multimedia, and distance learning technologies.
AI: Fully automatable - AI systems can provide up‑to‑date technical advice, configuration steps, and troubleshooting for common instructional technologies and distance‑learning tools and are widely used for this purpose.
Interview subject matter experts or conduct other research to develop instructional content.
AI: Partial - AI can generate interview guides, synthesize existing research and transcribe/summarize SME interviews, but cannot reliably conduct nuanced live SME interviews or replace stakeholder rapport and judgment.
Conduct needs assessments and strategic learning assessments to develop the basis for curriculum development or to update curricula.
AI: Partial - AI can analyze data, stakeholder inputs, and produce needs-assessment reports, but strategic interpretation and stakeholder engagement required for final curriculum decisions remain human-led.
Assess effectiveness and efficiency of instruction according to ease of instructional technology use and student learning, knowledge transfer, and satisfaction.
AI: Partial - AI can process learning analytics, surveys, and usability metrics to evaluate effectiveness, but comprehensive judgments about transfer, contextual factors, and action planning need human interpretation and validation.
Develop measurement tools to evaluate the effectiveness of instruction or training interventions.
AI: Partial - AI can draft surveys, rubrics and assessment items and run initial analyses, but creating fully validated measurement instruments with appropriate psychometric properties requires human expertise and piloting.
Research and evaluate emerging instructional technologies or methods.
AI: Partial - AI can rapidly survey literature, synthesize vendor claims and summarize emerging methods, but real-world evaluation and hands-on testing of new technologies still require human-led trials and contextual judgment.
Teach instructors to use instructional technology or to integrate technology with teaching.
AI: Partial - AI can deliver tutorials, simulated coaching, and step‑by‑step guidance for instructional technologies, but fully teaching instructors—including hands‑on, adaptive interpersonal coaching—still benefits from human facilitators.
Recommend changes to curricula or delivery methods, based on information such as instructional effectiveness data, current or future performance requirements, feasibility, and costs.
AI: Partial - AI can analyze effectiveness data and constraints to propose curricular or delivery changes, but comprehensive recommendations require stakeholder judgment, feasibility validation, and policy considerations that limit full automation.
Observe and provide feedback on instructional techniques, presentation methods, or instructional aids.
AI: Partial - AI can observe recorded instruction and give detailed feedback on pacing, clarity, and some techniques, but nuanced, real‑time pedagogical coaching and affective judgments remain partially automated.
Develop master course documentation or manuals according to applicable accreditation, certification, or other requirements.
AI: Partial - AI can generate master course documentation and draft manuals aligned to stated accreditation criteria, but ensuring full compliance and final signoff requires expert human review and institutional knowledge.
Provide technical support to clients in the implementation of designed instruction or in task analyses and instructional systems design.
AI: Partial - AI can provide extensive technical guidance, diagnostic troubleshooting, and scripted support for implementation and task analysis, yet hands‑on system integration and client coordination still need human practitioners.