Art, drama and music professors
Official title Art, Drama, and Music Teachers, Postsecondary (SOC 25-1121)
Also called Art professor, Music professor, Drama professor, Theatre professor, Studio art professor
In brief
In May 2025, BLS counted 93,560 US art, drama and music professors, with median pay of $78,620 a year. Of the BLS counts since 2003, the highest was 101,500, in May 2023. The earliest figure here is an estimate of 4,500 from 1900, not measured the same way as today's count. The last full technology era for art, drama and music professors: Learning Management Systems and online arts education, 2012 to 2023.
What the sources say
Official outlook
BLS projects employment to grow 2.2% from 2025 to 2035.
AI exposure studies
- 59.4% of this job's tasks are exposed to large language models. Not a forecast of job losses. Eloundou and others, 2023
Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend. In May 2021 BLS changed how it estimates these counts (a model-based method using three years of survey data) and moved fully to the 2018 occupation codes, so part of a change across 2021 can come from the method rather than the work.
Last updated .
Cite this page
Future History. (2026, October 11). Art, drama and music professors: jobs and pay since 1900 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/25-1121
Future History. "Art, drama and music professors: jobs and pay since 1900." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/25-1121.
@misc{futurehistory_25_1121, author = {{Future History}}, title = {Art, drama and music professors: jobs and pay since 1900}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/25-1121}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }
The access date is today's date on your device.
≈ $76,604 in 2024 prices (derived by us, CPI-adjusted)
The Oberlin Conservatory of Music opens as the oldest continuously operating conservatory in the United States, establishing the institutional model for postsecondary music teaching. Peabody Institute in Baltimore, founded in 1857, had opened its conservatory division in 1866. The New England Conservatory, Cincinnati Conservatory, and Chicago Academy of Music all opened in 1867, creating a critical mass of institutions that required full-time music faculty for the first time.
Carnegie Mellon establishes the first university drama degree program in the world in February 1914 under Thomas Wood Stevens. The first class is 18 students (nine women, nine men). This marks the formalization of drama and theatre instruction as an academic discipline with its own degree-granting program, creating the category of postsecondary drama faculty.
George Pierce Baker joins Yale to establish what becomes the Yale School of Drama, after Harvard declined to offer a degree in playwriting. Baker's Drama 47 workshop had trained playwrights at Harvard including Eugene O'Neill; its migration to Yale brings graduate drama education into the Ivy League. The school awards its first MFA in 1931 and becomes a separate professional school in 1955, establishing the MFA as the terminal credential for theatre faculty.
The GI Bill (Servicemen's Readjustment Act) passes, setting off the most rapid expansion of US higher education in history. By 1947, veterans account for half of all college enrollment. Colleges and universities recruit professional artists, musicians, and theatre practitioners to meet demand, professionalizing what had been informal studio apprenticeship. This is the formative event of the modern postsecondary arts faculty labor market.
The National Endowment for the Arts, established in 1965, begins funding arts education programs at colleges and universities. NEA grants support artist residencies, ensemble programs, and arts curriculum development, creating additional revenue streams for arts faculty and expanding the range of teaching appointments available. The 1960s baby boom-driven enrollment surge continues to push arts faculty hiring to historic highs.
The American Association of University Professors (AAUP) publishes its first formal statement on contingent faculty employment, marking the institutionalization of concern about adjunctification. In arts programs, adjunctification had been accelerating since the mid-1970s: practical studio instruction was easy to staff per-course with working professional artists and musicians. From 1975 to 2011, part-time faculty hiring would grow 286% while full-time tenure-track hiring grew 23%.
MFA enrollment in visual arts programs peaks and begins a gradual decline, tracking broader higher education enrollment trends and growing skepticism about the return on investment of $50,000-$100,000 graduate arts degrees. Application numbers at major MFA programs had begun declining with the 2008 financial market crash and, per Artnet News reporting, did not recover to pre-crisis levels. This enrollment trajectory will create downstream headcount pressure on arts faculty hiring through the 2010s.
The rapid commercial release of generative AI image tools (Midjourney V5, Stable Diffusion), AI music generators (Suno, Udio), and AI video tools (Runway Gen-2) creates an acute curriculum crisis in postsecondary arts programs. The College Art Association, College Music Society, and Theatre Communications Group all convene task forces and publish guidance. The defining institutional question is whether AI-generated work constitutes student academic work for portfolio or assessment purposes. Institutional responses range from full prohibition (some studio art faculty) to required critical engagement (RISD, Pratt, Yale School of Drama policies). No consensus emerges by 2025-2026.
Will AI replace art, drama and music professors? What the research says
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.
Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.
What's changing day to day for art, drama and music professors
Three parts of your work where AI is already doing real lifting, and what stays yours.
AI is sitting alongside you hereEvaluate and grade student work (visual art portfolios, musical compositions and performances, dramatic scene work, and written critical analysis) navigating the absence of an AI detection equivalent for music and visual art (no Turnitin exists for Suno-generated compositions or Midjourney-derived paintings as of 2026) by designing evaluation rubrics that require process documentation, in-studio process work, and live performance defense that AI tools cannot fake.
Evaluate and grade student work (visual art portfolios, musical compositions and performances, dramatic scene work, and written critical analysis) navigating the absence of an AI detection equivalent for music and visual art (no Turnitin exists for Suno-generated compositions or Midjourney-derived paintings as of 2026) by designing evaluation rubrics that require process documentation, in-studio process work, and live performance defense that AI tools cannot fake.[8],[6]
The absence of AI detection tools for music and visual art is the defining academic integrity challenge for this SOC in 2025–2026: the College Music Society (2025) survey found that faculty at many institutions had documented student use of Suno or Udio for composition assignments, with no reliable detection method. The solution is assessment redesign: require process portfolios with iteration documentation (sketches, drafts, rehearsal recordings, revision logs) that AI tools cannot produce; require in-studio composition or creation exercises where you observe the student making work; require the live performance, not just the recording, AI cannot walk into a practice room and play. Use Turnitin for written components (program notes, critical essays, artist statements) while acknowledging that it was not designed for arts-specific work. Use ChatGPT Edu to draft rubric criteria, then apply disciplinary expert judgment in the evaluation itself. The RISD and Pratt policies both converge on process portfolio and in-person defense as the most assessment-robust formats.
AI is sitting alongside you herePrepare course materials (syllabi, assignment prompts, reading lists, and lecture notes) using ChatGPT Edu to generate first-draft weekly schedules and assignment prompts, then applying disciplinary expertise to design studio projects and performance requirements that sequence skill development coherently and culminate in portfolio-ready or production-ready work that will hold up to professional industry review.
Prepare course materials (syllabi, assignment prompts, reading lists, and lecture notes) using ChatGPT Edu to generate first-draft weekly schedules and assignment prompts, then applying disciplinary expertise to design studio projects and performance requirements that sequence skill development coherently and culminate in portfolio-ready or production-ready work that will hold up to professional industry review.[12],[1]
Syllabus scaffolding is the highest-leverage AI time-recovery for arts faculty: a first-draft semester-long Drawing I syllabus, a Music Theory II weekly schedule with practice assignment structure, or a directing course reading list can all be generated with ChatGPT Edu in minutes. Then invest your expert effort in the curricular architecture that AI cannot design: the studio project sequence that builds from value studies to color to composition before introducing conceptual work, because you know from several years of teaching when students are ready to think conceptually about what they are making. Use NotebookLM to synthesize uploaded artist monographs, theory texts, and score analyses for lecture prep. The Inside Higher Ed consensus on arts curriculum (2025–2026): AI accelerates the scaffolding dramatically; the pedagogical arc, the argument about what the course is building toward over a semester, requires human authorship from someone who knows both the discipline and the students.
AI is sitting alongside you herePrepare and deliver lectures and seminars on art history, music theory, dramatic literature, and arts-related topics: using ChatGPT Edu to scaffold first-draft lecture outlines and generate discussion questions, using NotebookLM to synthesize secondary scholarship from uploaded readings, and using Midjourney or Adobe Firefly to generate visual reference images for art history comparisons and contemporary AI-art case studies, then applying disciplinary expertise to build an interpretive argument the AI cannot make.
Prepare and deliver lectures and seminars on art history, music theory, dramatic literature, and arts-related topics: using ChatGPT Edu to scaffold first-draft lecture outlines and generate discussion questions, using NotebookLM to synthesize secondary scholarship from uploaded readings, and using Midjourney or Adobe Firefly to generate visual reference images for art history comparisons and contemporary AI-art case studies, then applying disciplinary expertise to build an interpretive argument the AI cannot make.[7],[12]
Lecture scaffolding is where arts faculty recover the most time with AI assistance: an art history survey lecture outline on the Harlem Renaissance, a music theory lesson on modal interchange, or a dramatic literature seminar on Brecht's Verfremdungseffekt can all be first-drafted with ChatGPT Edu in minutes. Use NotebookLM to synthesize several uploaded PDFs on a topic into a thematic overview with inline source references for lecture prep. The interpretive work that makes the lecture worth attending (your reading of why Romare Bearden's photomontage is formally revolutionary, your analysis of what makes Coltrane's "A Love Supreme" spiritually and musically unprecedented, your argument about why Beckett's stage directions are as important as his dialogue) is your scholarly contribution. Faculty at RISD and Pratt (2025 guidance) also recommend using Midjourney outputs as explicit lecture examples of AI image generation to teach students to distinguish AI aesthetic from human artistic intent, turning the tool into pedagogical content.
Where art, drama and music professors go next
Natural next steps for someone with your foundation: not exits, evolutions.
- Education Administrators, Postsecondary
- US median pay
- $104,590 (May 2025)
- BLS outlook 2025-35
- +1.8%
- Fine Artists, Including Painters, Sculptors, and Illustrators
- US median pay
- $55,490 (May 2025)
- BLS outlook 2025-35
- -2.9%
- Actors
- US median pay
- $26,460 (May 2003)
- BLS outlook 2025-35
- 0%
What each move takes
Education Administrators, Postsecondary
Art, Drama, and Music faculty move into department chair, dean of arts, and provost office roles at significant rates, particularly those who have served on curriculum committees, led MFA or BFA accreditation reviews (NASAD for art and design, NASM for music, NAST for theatre), or built AI policy frameworks for their programs. In 2025–2026, postsecondary education administrators are being called to lead institutional AI governance with specific expertise in arts curriculum, digital intellectual property, student performance rights, and the pedagogical stakes of AI creative tools: all domains where arts faculty hold rare disciplinary depth. The CRI increase reflects that administrator roles have stronger institutional stability than faculty positions in arts programs facing enrollment pressure, and that AI governance expertise built in this SOC translates directly to senior administrative value.
- · Arts program accreditation: NASAD (National Association of Schools of Art and Design), NASM (National Association of Schools of Music), and NAST (National Association of Schools of Theatre) standards, self-study documentation, visiting team protocols, and ongoing outcomes assessment
- · Higher education budget and enrollment management: faculty line modeling for arts programs, studio and equipment capital planning, program viability analysis using institutional research data, and the enrollment management decisions specific to competitive BFA/MFA applicant pools
- · Institutional AI governance for creative programs: developing AI-use policy that is pedagogically coherent for studio arts, music, and performance contexts, translating CAA, CMS, and TCG disciplinary guidance into enforceable institutional policy with faculty buy-in
- · Development and alumni relations for arts programs: annual fund for arts scholarships, donor cultivation for named endowed chairs, artist-in-residence funding, and the case-making for arts program value in a university political environment that increasingly demands vocational ROI justification
- · Facilities and production infrastructure planning: studio renovation, performance venue and stage technology upgrades, virtual production lab investment decisions, and the AV/lighting/recording infrastructure that defines a competitive arts program's market position
How has the work of art, drama and music professors changed since 1865?
The tools that defined the work, one line per era. Select an era to see how it reshaped the work.
Instrument, easel, and voice: pre-recorded transmission (no amplification, no recording)
The defining technology of the conservatory and studio era was the absence of recording or amplification: instruction was entirely live, one-on-one, and dependent on the physical co-presence of teacher and student. A piano professor at Oberlin in 1870 could not play back a recording of the student's performance; the teacher listened, demonstrated on the same instrument, and corrected in real time. A drawing professor could not project a reference image; they pinned an actual engraving on the wall or sat next to the student and drew on the same paper. Drama instruction depended on the teacher's own vocal and physical demonstration. The technology of instruction was the teacher's own body and instrument. This era established the irreducibly embodied character of arts pedagogy that persists to the present day.
Phonograph and radio: recorded music enters the classroom
The phonograph, by the 1920s widely affordable and mechanically reliable, allowed music faculty to play recordings in class for the first time, separating listening and analysis from live performance. For music history and appreciation courses, this was transformative: a professor could now demonstrate Beethoven's Fifth or a Gregorian chant from an RCA Victrola rather than requiring live performance. For theory and composition courses, recorded playback enabled comparison and analysis in ways that pure notation study could not. For drama faculty, the emergence of talkies (1927) and radio drama gave new reference material for vocal and theatrical technique. In the visual arts, the lantern slide projector (which preceded the 35mm slide) allowed art history lectures to project images for the first time, transforming art history from a lecture-before-prints discipline into a comparative-projection discipline that would define art history pedagogy for the next seventy years.
Effect on the workThe phonograph did not reduce demand for music faculty; it expanded what music courses could teach and contributed to the growth of music appreciation and music history as mass-enrollment survey courses that required faculty staffing.
GI Bill expansion: mass credentialization of arts teaching
The Servicemen's Readjustment Act of 1944 (the GI Bill) is not typically framed as a technology, but it was the catalytic event that transformed arts teaching from a craft-apprenticeship model into a credentialed academic profession. By 1947, veterans made up half of all US college enrollment; by 1950, hundreds of thousands of Americans graduated from college each year. Colleges and universities recruited professional artists, musicians, and theatre practitioners to teach this wave of students, professionalizing what had previously been informal studio transmission. The GI Bill also catalyzed the consolidation of the MFA as the terminal credential for arts faculty: by the 1960s the MFA was the standard requirement for a faculty appointment in studio art, and by 1970 it was near-universal in art and drama programs. This era created the occupational category that BLS now counts as 25-1121.
Effect on the workTotal postsecondary faculty in the US grew between 1940 and 1970, with arts faculty expanding proportionally. The GI Bill-driven expansion is responsible for most of the mid-century growth in this SOC.
35mm slide projector and hi-fi audio: the audiovisual classroom
The 35mm Kodachrome slide, widely adopted in art history teaching by the 1960s, became the defining teaching technology of the visual arts classroom for three decades. A two-projector setup (standard equipment by the 1970s) let art history faculty project two images side by side for comparison: Raphael next to Leonardo, Impressionism next to Post-Impressionism, ancient next to Renaissance. Reel-to-reel tape recorders and then cassette decks gave music faculty the ability to record student performances for playback analysis and critique. The Wollensak, Nagra, and later the Sony TC-series tape recorders became standard teaching tools in music programs. For drama faculty, the 16mm film projector brought the work of Stanislavski, Brecht, and the Method to students through documentary and filmed performance footage. These audiovisual tools expanded the reference library available in the classroom enormously without displacing the core studio and performance instruction.
Adjunctification and MIDI: the contingent labor era meets digital music production
Two parallel developments reshaped arts faculty in the 1980s. Arts programs were disproportionately affected because practical studio instruction was easy to staff with per-course adjuncts who were working professionals. On the technology side, MIDI (Musical Instrument Digital Interface), standardized in 1983, brought digital sequencing to music programs: a composer could now produce a fully orchestrated mockup on a single workstation, transforming music composition and recording curricula. Electronic music and computer music programs became standard at major conservatories and music schools by the late 1980s, and faculty who could teach electronic production became a distinct hiring category.
Effect on the workAdjunctification restructured the economic floor of arts teaching: by the mid-1990s, a significant fraction of arts instruction at US universities was delivered by adjunct instructors earning per-course rates that annualized to well below the poverty line. This compressed the median wage reported for the SOC downward and created a two-tier faculty labor market (tenured professors vs. adjuncts) that persists today.
Digital production tools: Photoshop, Final Cut Pro, Pro Tools (the democratization era)
Adobe Photoshop (1990, mass adoption by mid-1990s), Apple's Final Cut Pro (1999), and Digidesign Pro Tools (professional standard by the late 1990s) radically lowered the cost of studio-quality visual and audio production, transforming what arts programs could teach and what they needed to teach. Graphic design programs shifted from paste-up and darkroom work to entirely digital workflows. Film and video production programs moved from 16mm film to digital video, lowering per-project costs by orders of magnitude. Music recording programs built Pro Tools labs where students could produce professional-grade tracks in school facilities. The net effect was not a reduction in faculty demand but a transformation in the technical skills faculty needed to hold a credible appointment: a photography professor hired in 1990 needed to retrain in digital darkroom techniques or risk irrelevance by 2000. The early 2000s expansion of MFA enrollment at US universities drove significant hiring of arts faculty, with total postsecondary arts faculty estimated to exceed 78,000 by 2000.
Learning Management Systems and online arts education (Canvas, Zoom, critique culture shifts)
The rise of Canvas, Blackboard, and similar Learning Management Systems brought administrative layers to arts teaching that the studio had never had: documented learning outcomes, online grade submission, digital portfolio platforms, accessibility compliance requirements. For arts faculty this was largely administrative overhead rather than a transformation of the teaching core. The more significant shift was Zoom's arrival in the COVID-19 period (2020-2022), which forced studio critique, music lesson, and theatre workshop formats into a distributed video format for the first time. The results were instructive: online music lessons and art critique proved workable for some purposes and deeply inadequate for others. Ensemble rehearsal online was largely unworkable due to latency. Individual voice lessons online lost the physical placement and tactile cuing that defines the best vocal pedagogy. Studio critique online lost the ability to walk up to a canvas. The COVID-19 experiment demonstrated both the potential of distributed arts teaching and the irreducible advantages of physical co-presence for the most central activities in arts pedagogy.
Effect on the workThe COVID period accelerated adjunctification in some arts programs (laid off per-course instructors are easier to shed during enrollment contraction) while creating urgent demand for faculty who could adapt studio formats to online delivery. MFA enrollment began declining at some institutions from its 2011 peak, partly due to cost concerns and partly due to skepticism about online-delivered arts education.
Generative AI in arts education: Midjourney, Suno, Runway, ElevenLabs (the curriculum disruption era)
Midjourney V5 (2023), Suno (2023), Runway Gen-2 and Gen-4 (2024), and ElevenLabs voice synthesis entered arts curricula not as tools faculty chose to introduce but as tools students were already using. The College Art Association's 2025 Technology in Arts Education Task Force documented widespread student use of AI image generation in MFA and BFA programs; the College Music Society's 2025 survey found student use of AI music generation (Suno, Udio) for composition assignments at many institutions, with no reliable detection method. Adobe's integration of Firefly AI generation across Creative Cloud (2023-2024) placed AI image and audio generation inside every tool students already used. For arts faculty, this created the defining curriculum question of the era: when AI can generate technically adequate images, compositions, and performances from text prompts, what is the pedagogical purpose of arts education? The answer that leading programs (RISD, Pratt, Yale School of Drama, Juilliard) converged on by 2025-2026 was: the purpose is the development of artistic judgment, conceptual authorship, and embodied craft that AI tools demonstrably cannot provide. Faculty who could teach students to use AI tools critically, professionally, and with aesthetic authority found themselves at the center of the most consequential curriculum debate in higher arts education.
Effect on the workThe indirect employment risk is larger than the direct: if AI tools displace entry-level illustration, concept art, session music, and voice-over work for arts graduates, enrollment pressure on arts programs will mount, creating institutional headcount pressure on faculty positions even though the teaching itself cannot be automated. The 2025-2026 period is too early to quantify this effect in BLS employment data.
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Browse all rolesArt, Drama, and Music Teachers, Postsecondary employment and pay by year
View all 29 years of cited US data, each linked to its source
| Year | US employment | Annual pay (median unless marked) | Source | Report |
|---|---|---|---|---|
| 1900 | 4,500 | n/a | Est., National Center for Education Statistics Researched context | Report |
| 1940 | 12,000 | n/a | Est., National Center for Education Statistics Researched context | Report |
| 1970 | 42,000 | $11,000 | Est., National Center for Education Statistics (employment) Researched contextEst., AAUP Faculty Compensation Survey (pay) Researched context | Report |
| 1980 | 58,000 | n/a | Est., National Center for Education Statistics Researched context | Report |
| 1990 | n/a | $34,000 | Est., AAUP Faculty Compensation Survey… Researched context | Report |
| 2000 | 78,000 | n/a | Est., National Center for Education Statistics Researched context | Report |
| 2003 | 60,120 | $47,980 | BLS OEWS May 2003 Official statistic | Report |
| 2004 | 63,730 | $48,780 | BLS OEWS May 2004 Official statistic | Report |
| 2005 | 69,260 | $51,240 | BLS OEWS May 2005 Official statistic | Report |
| 2006 | 72,100 | $53,160 | BLS OEWS May 2006 Official statistic | Report |
| 2007 | 73,890 | $55,190 | BLS OEWS May 2007 Official statistic | Report |
| 2008 | 76,810 | $57,820 | BLS OEWS May 2008 Official statistic | Report |
| 2009 | 80,790 | $60,400 | BLS OEWS May 2009 Official statistic | Report |
| 2010 | 86,860 | $62,040 | BLS OEWS May 2010 Official statistic | Report |
| 2011 | 90,030 | $62,330 | BLS OEWS May 2011 Official statistic | Report |
| 2012 | 92,570 | $62,160 | BLS OEWS May 2012 Official statistic | Report |
| 2013 | 92,930 | $62,830 | BLS OEWS May 2013 Official statistic | Report |
| 2014 | 97,500 | $64,300 | BLS OEWS May 2014 Official statistic | Report |
| 2015 | 98,310 | $65,340 | BLS OEWS May 2015 Official statistic | Report |
| 2016 | 99,020 | $68,650 | BLS OEWS May 2016 Official statistic | Report |
| 2017 | 95,110 | $66,930 | BLS OEWS May 2017 Official statistic | Report |
| 2018 | 94,310 | $69,960 | BLS OEWS May 2018 Official statistic | Report |
| 2019 | 94,060 | $69,530 | BLS OEWS May 2019 Official statistic | Report |
| 2020 | 91,170 | $69,690 | BLS OEWS May 2020 Official statistic | Report |
| 2021 | 94,720 | $75,940 | BLS OEWS May 2021 Official statistic | Report |
| 2022 | 97,830 | $77,280 | BLS OEWS May 2022 Official statistic | Report |
| 2023 | 101,500 | $80,360 | BLS OEWS May 2023 Official statistic | Report |
| 2024 | 97,890 | $80,190 | BLS OEWS May 2024 Official statistic | Report |
| 2025 | 93,560 | $78,620 | BLS OEWS May 2025 Official statistic | Report |
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