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MRI technologists

Official title Magnetic Resonance Imaging Technologists (SOC 29-2035)

Also called MRI tech, MR technologist, MR tech, Magnetic resonance technologist, MRI specialist

In brief

In May 2025, BLS counted 43,390 US MRI technologists, with median pay of $95,480 a year. Of the BLS counts since 2012, the May 2025 count is the highest. The earliest figure here is an estimate of 2,000 from 1985, not measured the same way as today's count. The last full technology era for MRI technologists: AI safety tools and implant management platforms, 2018 to 2022.

What the sources say

Official outlook

BLS projects employment to grow 7.7% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

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
APA

Future History. (2026, October 11). MRI technologists: jobs and pay since 1985 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/29-2035

Chicago

Future History. "MRI technologists: jobs and pay since 1985." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/29-2035.

BibTeX

@misc{futurehistory_29_2035, author = {{Future History}}, title = {MRI technologists: jobs and pay since 1985}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/29-2035}}, 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.

drag to travel through time
2000now
2026
Known then as NMR Technologist / NMR Operator (research-site era, pre-commercial)
Known then as MRI Technologist / MR Technologist (early clinical adoption, no formal credential)
Known then as MRI Technologist / ARMRIT-certified MR Tech (post-1991 ARMRIT credential; ARRT MR as postprimary add-on from 1995)
Known then as Magnetic Resonance Imaging Technologists (BLS SOC 29-2035; ARRT MR as independent primary credential from 2006)
Known today as Magnetic Resonance Imaging Technologists (BLS SOC 29-2035; ARRT MR as independent primary credential from 2006)
Projected to still be called Magnetic Resonance Imaging Technologists (BLS SOC 29-2035; ARRT MR as independent primary credential from 2006)
Data from the May 2025 survey
US Employment
43K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$95,480
Est.

≈ $93,032 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1977

July 3, 1977: Raymond Damadian, Larry Minkoff, and Michael Goldsmith complete the first whole-body MRI scan of a living human on their custom machine "Indomitable" at SUNY Downstate Medical Center in Brooklyn. The scan took nearly five hours to produce one cross-sectional image of Minkoff's thorax. This is the birth moment of the occupation: someone had to build and operate these machines, and the first MRI "technologist" was part physicist, part inventor, part clinician.

Beat · 1984

The FDA grants approval for clinical MRI scanning in the United States. Prior to this, MRI use was research-protocol or investigational. FDA clearance opened the commercial market: GE, Siemens, Picker, Technicare, and other manufacturers could now sell and market MRI systems directly to US hospitals. The clinical workforce need became acute.

Beat · 1991

ARMRIT (American Registry of Magnetic Resonance Imaging Technologists) is founded as the first credentialing body dedicated exclusively to MRI. Its mission: to certify the large workforce of technologists who had been trained entirely on the job since 1983, with no standardized examination or competency verification. ARMRIT marks the moment MRI technologist becomes a recognized, certifiable professional identity rather than a specialty skill held informally by radiologic technologists at scanner-equipped sites.

Beat · 2003

Nobel Prize in Physiology or Medicine awarded jointly to Paul Lauterbur and Peter Mansfield for their discoveries concerning magnetic resonance imaging. The Nobel committee did not include Raymond Damadian, who had conducted the first human whole-body scan; Damadian publicly protested the omission with full-page newspaper advertisements. The Nobel citation validated MRI as one of the most significant medical advances of the 20th century, which was already the practical reality for the thousands of MRI technologists who had built and operated the equipment since the 1980s.

Beat · 2006

ARRT redesignates MR imaging as an independent primary credential, no longer requiring prior radiologic technologist certification. This is the formal recognition that MRI is its own discipline -- not a specialty grafted onto radiographic technology, but a distinct clinical occupation with its own physics principles, patient safety requirements, and scope of practice. The change opened direct-entry educational pathways and helped the profession develop a distinct occupational identity.

Beat · 2021

AI-accelerated MRI reconstruction reaches mainstream clinical deployment. GE HealthCare's AIR Recon DL (2021), Siemens Healthineers' Deep Resolve, and Philips' SmartSpeed are all FDA-cleared and begin shipping as standard features on new scanner hardware. This is the single largest workflow change for MRI technologists since 3T scanners became standard. The practical effect: 30-50% shorter scan times at equivalent image quality, enabling meaningfully higher patient throughput per scanner per shift without adding staff. The tech's job description does not shrink -- the safety screening, patient management, and coil placement tasks remain fully human -- but the reconstruction step, which previously required skilled parameter optimization, is now largely automated.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace MRI technologists? 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 published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
+7.7%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 29-2035 (Magnetic resonance imaging technologists): 43.9 thousand jobs in 2025, projected 47.3 thousand in 2035, a change of +3.4 thousand (+7.7%). Matrix employment counts all jobs in the occupation, including self-employed workers. The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
22.2%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 29-2035.00 Magnetic Resonance Imaging Technologists. Shown: human-rated β = 0.222, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.133 and γ (all LLM-assisted) 0.311; GPT-4-rated β 0.322. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for MRI technologists

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereAcquire and quality-review MRI images before releasing studies to the PACS, evaluating each acquired image series for diagnostic acceptability (adequate SNR, no motion artifact, correct FOV and slice coverage, no susceptibility artifact obscuring the target anatomy, no reconstruction-specific AI denoising artifacts), deciding whether to accept or repeat individual sequences, and releasing the complete study to the PACS worklist for radiologist interpretation.

Acquire and quality-review MRI images before releasing studies to the PACS, evaluating each acquired image series for diagnostic acceptability (adequate SNR, no motion artifact, correct FOV and slice coverage, no susceptibility artifact obscuring the target anatomy, no reconstruction-specific AI denoising artifacts), deciding whether to accept or repeat individual sequences, and releasing the complete study to the PACS worklist for radiologist interpretation.[1],[11]

Where your edge is

AI image quality tools (Siemens AI-Rad Companion, Philips IntelliSpace AI) now flag suboptimal image quality at the PACS level after acquisition, reducing the tech's cognitive load on routine quality checks. However, MRI image quality assessment is more complex than CT because MRI artifacts are more varied (motion, susceptibility, chemical shift, Gibbs ringing, Nyquist ghosting, B1 field inhomogeneity, deep learning denoising over-smoothing) and more anatomy- and protocol-specific. Develop systematic artifact recognition across modalities and body regions (the ability to distinguish a clinically acceptable susceptibility artifact from a non-diagnostic one, or to identify the specific DL reconstruction artifact pattern that slightly alters T2 tissue contrast in the posterior fossa) is a genuine expert skill that AI quality tools do not replicate.

AI is sitting alongside you hereOperate GE, Siemens, or Philips MRI scanner with AI-accelerated reconstruction, selecting clinical protocol from scanner console, activating AI deep learning reconstruction (GE AIR Recon DL, Siemens Deep Resolve, Philips SmartSpeed, or Subtle Medical SubtleMR) for 30-50% scan time reduction at maintained diagnostic quality, monitoring acquisition in real time for artifacts or motion, and managing protocol deviations (failed sequences, coil connectivity errors, patient motion) mid-scan with adaptive protocol adjustments.

Operate GE, Siemens, or Philips MRI scanner with AI-accelerated reconstruction, selecting clinical protocol from scanner console, activating AI deep learning reconstruction (GE AIR Recon DL, Siemens Deep Resolve, Philips SmartSpeed, or Subtle Medical SubtleMR) for 30-50% scan time reduction at maintained diagnostic quality, monitoring acquisition in real time for artifacts or motion, and managing protocol deviations (failed sequences, coil connectivity errors, patient motion) mid-scan with adaptive protocol adjustments.[5],[6],[7]

Where your edge is

AI-accelerated MRI reconstruction (AIR Recon DL, Deep Resolve, SmartSpeed) is now the default protocol mode at most major MRI sites equipped with thousands of scanner hardware: the tech selects a protocol and the AI handles reconstruction automatically, enabling 30-50% more patients per scanner shift without sacrificing image quality (RSNA AI 2025; ISMRM 2024). This is augmentation, not displacement: AI cannot manage scanner hardware failures, respond to patient emergencies mid-scan, or adapt to unexpected patient anatomy or motion patterns that fall outside standard protocol assumptions. Build cross-vendor proficiency (GE SIGNA, Siemens MAGNETOM, Philips Ingenia) and develop expertise in recognizing AI reconstruction artifacts, the deep learning denoising failures that can produce subtly altered tissue contrast on undersampled acquisitions, so your quality review catches what the AI smooths over.

AI is sitting alongside you herePerform dedicated cardiac MRI examinations with AI-assisted analysis, acquiring multi-sequence cardiac protocols (cine SSFP for ventricular function, T1/T2 mapping, LGE for fibrosis/scar, stress perfusion, CMRA coronary MRI) using real-time cardiac gating and breath-hold coaching

Perform dedicated cardiac MRI examinations with AI-assisted analysis, acquiring multi-sequence cardiac protocols (cine SSFP for ventricular function, T1/T2 mapping, LGE for fibrosis/scar, stress perfusion, CMRA coronary MRI) using real-time cardiac gating and breath-hold coaching; ensuring adequate cardiac gating quality and image quality for quantitative analysis; and releasing studies to Circle CVI42 or equivalent AI cardiac MRI analysis software for automated LV/RV volumetrics and ejection fraction computation before cardiologist/radiologist interpretation.[10],[11]

Where your edge is

Cardiac MRI is the highest-growth MRI subspecialty and one of the most technically demanding: cardiac gating, breath-hold coaching, stress perfusion protocol management, and multi-coil cardiac coil positioning require a level of expertise that creates real market differentiation among MRI techs. Circle CVI42 and equivalent AI cardiac analysis tools automate the quantitative analysis step (LV/RV volumes, EF, LGE quantification) after acquisition, but your value is in the acquisition quality: poor cardiac gating or inconsistent breath-hold compliance produces unusable LGE or T2 mapping datasets that no post-processing AI can fix. Pursuing CMR technologist certification (Society for Cardiovascular Magnetic Resonance, SCMR) and developing stress perfusion and LGE acquisition expertise positions you in a subspecialty commanding clear compensation premiums at academic cardiac programs.

Where MRI technologists go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

A direction you could grow

Medical and Health Services Managers

Senior MRI technologists with lead tech, charge tech, or MRI safety officer experience are well-positioned for MRI department manager, imaging services director, and medical imaging administrator roles tracked under Medical and Health Services Managers. As imaging departments deploy AI-accelerated MRI platforms (GE SIGNA AIR, Siemens MAGNETOM Cima.X) and manage growing cardiac and specialty MRI program volumes, health systems need imaging managers who understand both the MRI clinical workflow and the vendor evaluation, AI protocol governance, accreditation management (ACR MRI accreditation, Joint Commission), and staff training required for responsible AI adoption. AHRA Certified Radiology Administrator (CRA) examination and an MHA or ARRT's Leadership Certificate are the credential investments that accelerate this path.

What you'd add
  • · AHRA Certified Radiology Administrator (CRA) examination: standard credential for imaging department management; covers operations, finance, human resources, and quality/safety compliance
  • · ARRT Radiologic Technology Leadership Certificate or MHA (Master of Health Administration) with healthcare operations focus
  • · Healthcare finance for imaging: APC/CMS reimbursement for outpatient MRI, budget management, scanner utilization and throughput benchmarking, capital equipment evaluation for MRI platform replacement cycles
  • · AI vendor management in MRI: evaluating AI reconstruction platforms (GE AIR Recon DL vs. Siemens Deep Resolve vs. Philips SmartSpeed), negotiating deployment agreements, managing AI algorithm performance post-deployment, preparing for ACR accreditation with AI-integrated protocols
  • · Workforce management in MRI: staffing models for multi-scanner MRI departments, cardiac and specialty MRI program development, ARRT MR credential verification, ABMRS safety certification compliance, on-call and per-diem pool management
What it takesSome new skills to pick up
Tools of the era

How has the work of MRI technologists changed since 1977?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Research NMR / prototype whole-body scanners (Damadian Indomitable era)

    The first whole-body MRI scans were conducted on custom-built research machines requiring multi-hour acquisition times and a team of physicists, engineers, and technicians to operate. The "technologist" at these sites was not a credentialed clinical worker but a hybrid of radiologic tech, physics graduate student, and hands-on experimenter. There were no standardized protocols, no safety screening checklists (the hazards of ferromagnetic objects near high-field magnets were being discovered in real time), and no formal training curriculum. The operator's craft was entirely improvised from the underlying physics.

  • First commercial clinical MRI scanners (FONAR 1980, Siemens MAGNETOM 1983; on-the-job trained workforce)

    The arrival of the first commercial MRI scanners created an urgent practical need: someone had to operate them. Hospitals that installed early Siemens, GE, or Picker MRI systems retrained their existing radiologic technologists or, in some cases, hired physics or engineering staff to operate the machines. There was no dedicated credentialing pathway. Scanners required hands-on management of superconducting magnet shimming, patient setup, coil placement for the anatomical region, and careful safety screening -- a practice being improvised from first principles as the risks of ferromagnetic objects near a 1.5T magnet became viscerally apparent to early operators. The first formal credentialing effort, ARMRIT, was founded in 1991 explicitly to certify the large workforce that had accumulated through on-the-job training over the preceding eight years.

    Effect on the work

    The US MRI scanners installed by end of 1985 required an estimated 2,000+ trained operators, created entirely through on-the-job cross-training from the radiologic technology workforce with no standardized curriculum.

  • Formal credentialing era (ARMRIT 1991; ARRT MR postprimary credential mid-1990s; 1.5T superconducting systems as the standard platform)

    The founding of ARMRIT in 1991 and the subsequent introduction of the ARRT MR postprimary credential in the mid-1990s transformed MRI technologist work from on-the-job craft into a credentialed profession with examinations, continuing education requirements, and documented competencies. Simultaneously, the technology standardized: 1.5T superconducting systems became the dominant clinical platform, replacing the patchwork of 0.35T, 0.5T, and higher-field experimental units from the early 1980s. Protocol books began to emerge, scanner manufacturers developed structured training programs, and the field developed its own safety culture -- the ACR MRI safety guidelines were first published in the 1990s. The workforce that had grown informally now had an institutional framework.

  • ARRT MR as independent primary credential; 3T and high-field scanners; PACS integration; ACR accreditation

    In 2006, the ARRT redesignated MR as an independent primary credential -- no longer requiring prior radiologic technologist certification. This recognized that MRI is a distinct clinical discipline not based on ionizing radiation, with its own patient safety requirements, physics principles, and scope of practice. The profession's identity fully separated from radiography. Simultaneously, 3T scanners moved from research to clinical deployment, expanding the protocol complexity (and the expertise required) for advanced neurological, cardiac, and body MRI. PACS integration made MRI studies part of the shared radiology digital workflow for the first time. ACR MRI Accreditation became an expectation at most clinical sites, standardizing phantom QC testing as a formal technologist responsibility.

  • AI safety tools and implant management platforms (ABMRS credentialing; implant registry databases)

    As the number of patients with cardiac implantable electronic devices, neurostimulators, cochlear implants, and other metallic implants grew, MRI safety screening became substantially more complex. The American Board of Magnetic Resonance Safety (ABMRS) launched the MRSO (MRI Safety Officer) and MRSE (MRI Safety Expert) credentials to formalize the knowledge base required for managing the growing landscape of MRI-conditional and MRI-unsafe implants. Digital implant management tools and registry databases began to supplement the paper-based screening process. This era did not displace technologist work; it deepened the specialized safety knowledge the role requires.

  • AI-accelerated MRI reconstruction (GE AIR Recon DL, Siemens Deep Resolve, Philips SmartSpeed; AI auto-positioning; cardiac MRI AI analysis)

    Deep learning MRI reconstruction algorithms became the default protocol setting at most modern MRI sites equipped with 2021-or-later scanner hardware. GE HealthCare's AIR Recon DL, Siemens Healthineers' Deep Resolve, and Philips' SmartSpeed each enable 30-50% scan time reduction at maintained or improved diagnostic image quality by reconstructing undersampled k-space data with convolutional neural networks. All three are FDA-cleared and deployed at thousands of sites globally. The technologist's role in this era is not eliminated but reoriented: AI handles reconstruction automatically once the tech selects the protocol; the human contribution concentrates on safety screening (entirely non-automated), patient management during the extended scan time (many minutes, a durable human necessity), coil placement for complex protocols, and quality review that distinguishes AI reconstruction artifacts from genuine pathology. AI auto-positioning tools (Siemens BioMatrix Body Positioning AI) assist landmark placement for standardized protocols. Circle CVI42 AI automates quantitative cardiac MRI analysis, raising the value of cardiac MRI subspecialization.

    Effect on the work

    AI-accelerated MRI reconstruction increases per-scanner throughput by 30-50% without additional technologist headcount, effectively making existing staff more productive. The occupation is projected to grow 7.1% from 2024-2034, outpacing the all-occupations average -- AI is expanding the diagnostic capability of existing MRI infrastructure rather than reducing the need for technologists.

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Magnetic Resonance Imaging Technologists employment and pay by year

On record since1977
Latest US employment43,390 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$95,480 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook+7.7% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 19 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
19852,000n/aEst., Steinberg EP (1986) Researched contextReport
199312,000n/aEst., Aeon Health Researched contextReport
1995n/a$36,000Est., ASRT Radiologic Technologist Wage and… Researched contextReport
200027,000n/aEst., BLS OOH Researched contextReport
2001n/a$46,000Est., ASRT Radiologic Technologist Wage and… Researched contextReport
201229,560$65,360BLS OEWS May 2012 Official statisticReport
201332,000$66,050BLS OEWS May 2013 Official statisticReport
201433,130$67,090BLS OEWS May 2014 Official statisticReport
201533,460$67,720BLS OEWS May 2015 Official statisticReport
201635,850$68,420BLS OEWS May 2016 Official statisticReport
201737,490$69,930BLS OEWS May 2017 Official statisticReport
201838,540$71,670BLS OEWS May 2018 Official statisticReport
201937,900$73,410BLS OEWS May 2019 Official statisticReport
202039,270$74,690BLS OEWS May 2020 Official statisticReport
202138,070$77,360BLS OEWS May 2021 Official statisticReport
202238,380$80,090BLS OEWS May 2022 Official statisticReport
202341,340$83,740BLS OEWS May 2023 Official statisticReport
202441,530$88,180BLS OEWS May 2024 Official statisticReport
202543,390$95,480BLS OEWS May 2025 Official statisticReport
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