Will AI Replace Instructional Designers? The High-Exposure Role That Is Evolving, Not Disappearing

Designing Learning in the AI Age

Among education professions, instructional designers face some of the highest AI exposure. This makes intuitive sense: their work centers on creating content, structuring learning sequences, and designing assessments -- all areas where AI capabilities are advancing rapidly. Yet the story is far from simple elimination.

The Anthropic Labor Market Report (2026) and Eloundou et al. (2023) show instructional designers at "high" AI exposure, with 58% overall exposure in 2025, 75% theoretical exposure, and 48% automation risk. Critically, the automation mode remains "augment," signaling that AI is reshaping the role rather than eliminating it.

What Instructional Designers Do

Instructional designers design, develop, and evaluate instructional materials and learning experiences using pedagogical theories, multimedia tools, and learner analytics to improve educational outcomes across academic and corporate settings.

Their work encompasses:

• Learning needs analysis: Identifying what learners need to know and the gaps in their current knowledge
• Curriculum architecture: Structuring learning pathways, modules, and sequences based on pedagogical research
• Content development: Creating text, visuals, interactive elements, assessments, and multimedia learning objects
• LMS management: Configuring and maintaining learning management systems
• Learner experience design: Applying UX principles to make learning intuitive and engaging
• Assessment design: Creating valid, reliable measures of learning outcomes
• Stakeholder management: Working with subject matter experts, faculty, and organizational leaders

Where AI Is Disrupting Instructional Design

High-Exposure Tasks

The data shows 75% theoretical exposure by 2025. These tasks are most affected:

1. Content authoring: AI can generate draft learning content, including explanatory text, examples, and case studies from brief prompts.
2. Assessment creation: AI tools generate quiz questions, rubrics, and scenario-based assessments aligned with learning objectives.
3. Storyboarding: AI can create initial storyboards for e-learning modules from learning objectives and content outlines.
4. Multimedia scripting: AI generates scripts for instructional videos, podcast episodes, and animation narration.
5. Accessibility compliance: AI tools can check content against accessibility standards and suggest corrections.

Lower-Exposure Tasks

1. Strategic learning design: Determining what an organization's learning strategy should be requires understanding business context, culture, and goals.
2. Learner empathy: Understanding why learners struggle and designing interventions requires human psychological insight.
3. Stakeholder negotiation: Working with resistant subject matter experts, managing scope creep, and aligning competing priorities requires interpersonal skill.
4. Innovation and experimentation: Pioneering new learning approaches -- gamification, immersive simulations, community-based learning -- requires creative vision.
5. Quality judgment: Evaluating whether a learning experience actually works requires pedagogical expertise and learner observation.

Projections Through 2028

The numbers are significant and worth understanding in full. In 2023, overall exposure sits at 42% with 35% automation risk and 22% observed exposure. By 2024, those figures rise to 50% overall, 42% automation risk, and 30% observed. The 2025 numbers show 58% overall exposure, 48% automation risk, and 38% observed. Moving to 2026, exposure reaches 64% overall with 53% automation risk and 44% observed. By 2027, it is 69% overall, 57% automation risk, and 49% observed. At the 2028 horizon, overall exposure reaches 73% with 61% automation risk and 53% observed exposure.

By 2028, over 61% automation risk means that the majority of tasks currently performed by instructional designers could theoretically be automated. But observed exposure (53%) and the "augment" classification indicate the profession is evolving, not vanishing. You can explore the full data breakdown on the Instructional Designers occupation page.

The Transformation of Instructional Design

What is emerging is a new kind of instructional designer -- one who works with AI rather than doing what AI can do:

The Old Model

• Spend 60% of time on content creation
• Manually build assessments and interactions
• Work on 3-5 projects per year
• Focus on individual course development

The New Model

• Spend 60% of time on strategy, analysis, and quality assurance
• Use AI to generate first drafts, then refine and improve
• Manage 10-15 AI-assisted projects per year
• Focus on learning ecosystem design and organizational impact

Market Dynamics

Despite high AI exposure, several factors sustain demand for instructional designers:

• E-learning explosion: The post-pandemic shift to digital learning is permanent, and organizations need professionals to design effective online experiences
• AI training demand: Every organization needs training on AI tools -- creating massive demand for instructional designers who understand both AI and learning design
• Quality standards: As AI-generated content floods learning platforms, expert curation and quality assurance become critical
• Regulatory training: Healthcare, finance, and other regulated industries require professionally designed compliance training
• Higher education transformation: Universities are redesigning curricula for the AI age, requiring instructional design expertise

Salaries for instructional designers range from $55,000 to $90,000, with corporate and tech-sector positions at the high end.

Surviving and Thriving

1. Become AI-fluent: Instructional designers who can effectively prompt, evaluate, and refine AI-generated content are in high demand.
2. Move upstream: Shift from content creator to learning strategist. AI handles production; you handle vision.
3. Master measurement: Using data to prove learning impact justifies your role and commands higher compensation.
4. Specialize in AI learning design: Designing AI-enhanced learning experiences is a growing niche with few qualified practitioners.
5. Develop consulting skills: As organizations navigate the AI transition, instructional designers who can advise on learning strategy have significant value.

The Bottom Line

Instructional designers face real and significant AI exposure -- among the highest of any education profession. But the "augment" classification tells the key story: AI is making instructional designers more productive, not unemployed. The profession is evolving from content production to learning strategy, and those who evolve with it will find their expertise more valuable than ever. The instructional designer of 2028 will look very different from 2020, but the role itself will persist because effective learning still requires human understanding of human learners.

Sources

• Anthropic. (2026). The Anthropic Labor Market Impact Report.
• U.S. Bureau of Labor Statistics. Instructional Coordinators — Occupational Outlook Handbook.
• O*NET OnLine. Instructional Designers and Technologists.
• Eloundou, T., et al. (2023). GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models.
• Brynjolfsson, E., et al. (2025). Generative AI at Work.

Update History

• 2026-03-21: Added source links and ## Sources section
• 2026-03-15: Initial publication based on Anthropic Labor Market Report (2026), Eloundou et al. (2023), and BLS Occupational Projections 2024-2034.

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This analysis is based on data from the Anthropic Labor Market Report (2026), Eloundou et al. (2023), Brynjolfsson et al. (2025), and U.S. Bureau of Labor Statistics projections. AI-assisted analysis was used in producing this article.

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