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Will AI replace court reporters and simultaneous captioners?

A little.

Software can draft a transcript, but certifying the record and captioning live, overlapping speech still rest with a trained reporter. This job scores 66 out of 100 on (higher is safer). Today AI could do about 22% of the work by itself, people do 45% with AI’s help, and 33% still needs a person.

Updated 3 October 2026 27-3092 4217 2026-Q4
Arts, Design, Entertainment, Sports, and MediaCourt Reporters and Simultaneous Captioners27-3092 · 2026-Q4
22% AI does it45% AI helps33% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 33%AI helps 45%AI does it 22%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Why the record still runs through a person

Court reporters and simultaneous captioners do two jobs at once. They capture spoken words as they happen, and then they stand behind the result. In a deposition or a hearing, the reporter keeps the record usable: stopping counsel when two people talk over each other, asking a witness to repeat a name, reading testimony back when the judge asks for it. Software does not get to interrupt a courtroom.

The second half is certification. A transcript becomes an official record because a qualified person attests that it is true and complete. In many depositions, that same person swears in the witness and marks the exhibits. Accountability here is a legal arrangement, not a technical one, and it does not transfer to a model.

Live captioning has its own version of the problem. Captioners handle accents, crosstalk, proper nouns and specialist vocabulary in real time, with no second pass and no chance to clean the file later. Ask whether AI will replace court reporters in that setting and the honest story is task erosion: drafting gets cheaper and faster, while the parts that carry legal weight stay with people.

What the software drafts, what it assists, and what stays human

Machine transcription is strongest at first-pass drafting. It turns recorded audio into searchable text, labels speakers, and indexes a file so a paralegal can find a passage in seconds. In our task split, the share of task time sitting in the group AI can handle on its own is 22%. Coverage, our measure of how much of the work AI can touch today, reads 38 out of 100; how coverage is measured sets out what that counts.

Assisted work is the bigger day-to-day change. Speech tools feed a rough real-time draft that the reporter corrects, dictionaries expand legal terms and party names on the fly, and automated passes flag likely misheard words before a transcript goes out. The share of task time in that assisted group is 45%.

Then there is the work that needs the person in the room: certifying the transcript, controlling the record when speech overlaps or a witness trails off, and reading testimony back on request. That group comes to 33%.

What has actually been tested

Not much, directly. Our evidence grade for this job is D, which means there is no published head-to-head test of AI against certified reporters under real courtroom conditions in our evidence set. So we publish no parity number for this occupation. Word-error-rate scores on clean, single-speaker audio do not settle it, because the hard minutes are the messy ones.

What would settle it is a blind comparison on genuine multi-speaker proceedings: objections, accented testimony, technical exhibits, and names nobody spells out. The output would need scoring against the accuracy standard courts require for a certified transcript, with disputed passages reviewed by qualified reporters. Until a test like that exists, the parity column stays open. Our scoring method explains how the grades are assigned and why a missing grade never becomes a number.

When this could shift

Most likely between 2036 and 2049 (8 in 10 of our scenarios). The replacement-year method explains what that window measures and how wide it is meant to be.

Two things could pull the change earlier. Deployment needs no hardware: the work is audio in, text out, so there is nothing to build beyond software and better microphones. And where a court simply cannot staff a reporter, the fallback is already recording plus later transcription, which normalizes the machine draft as the starting point.

Two things hold it back. Rules of court and state statutes often specify a certified reporter for an official record, and those rules change slowly, jurisdiction by jurisdiction. Liability is the other brake, because a disputed line in a transcript can move a case and someone has to answer for it. Federal projections also point to a steady, small occupation rather than a shrinking one: BLS 2025-35 projections put the ten-year employment change for this job at about -0.1%. If you want context on jobs moving the other way, see our list of jobs most at risk.

How to stay needed in this work

Lean into the tasks that only work with a qualified person attached. Certifying the record is the first: the signature, the oath, the chain of responsibility. Second, controlling and reading back the live record, which means interrupting, clarifying and fixing a misheard name before it hardens into the transcript. Third, real-time captioning of unpredictable speech for deaf and hard-of-hearing audiences, where there is no second pass and no editing window.

Two skills carry the most weight. One is realtime output with a well-tuned personal dictionary, so your draft is usable the moment the hearing ends. The other is fast, accurate correction of machine drafts, which is a different skill from typing: it is hearing the gap between what the file says and what was said, and knowing which errors matter legally.

What to do: keep your certification current and get quick at editing machine output, because that is the part of the workflow firms and courts are paying for.

Nearby work worth a look: Interpreters and Translators, Proofreaders and Copy Markers, and Court, Municipal, and License Clerks. You can put any two of them side by side on our job comparison tool, see the wider media and communication workers family, or read how exposure plays out across law firms.

Frequently asked questions

Is court reporting becoming obsolete?

No. The drafting end of the job is getting cheaper, and that pressure is real, especially on routine transcription work. But the certified record, live readback and control of the room are not transcription tasks. The task split above shows how the work divides between what AI can do alone, what it assists with, and what stays with a person.

Are court reporters in demand?

Demand is steady rather than booming. BLS 2025-35 projections put the ten-year employment change for court reporters and simultaneous captioners at about -0.1%, which is close to flat. Local conditions vary a lot: some courts struggle to fill reporter seats while others have moved routine hearings to digital recording with later transcription.

Is there a future in stenography?

Yes, but a narrower and more technical one. The value is shifting from raw typing speed toward realtime output, a strong personal dictionary, clean certified transcripts and fast correction of machine drafts. Reporters who work in live settings, where there is no chance to fix the file afterward, hold the most defensible ground.

How long does it take to become a court reporter?

It depends on the program and on how quickly you reach the required speed, which is the real gate rather than the calendar. Most routes combine a training program with a speed and knowledge exam, and requirements differ by state and by court. Check your state’s certification rules and the exam standards before you commit to a school.

What is the difference between digital recording and a stenographic reporter?

Digital recording captures audio for someone to transcribe later, often with software doing the first draft. A stenographic reporter produces the record live, can stop proceedings to clarify, and certifies the transcript. The difference matters most when speakers overlap, audio is poor, or a passage is later disputed in a filing or on appeal.

Each ridge is a slice of the job's task time.Needs a human 33%AI helps 45%AI does it 22%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Court Reporters and Simultaneous Captioners, O*NET-SOC 27-3092. 33% of the job’s task time still needs a human, so 33 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 33% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 33%AI helps 45%AI does it 22%
The job's task list: the parts AI can do are blacked out.Needs a human 33%AI helps 45%AI does it 22%
Provide transcripts of proceedings upon request of judges, lawyers, or the public.AI does it
Record symbols on computer storage media and use computer aided transcription to translate and display them as text.AI does it
Record verbatim proceedings of courts, legislative assemblies, committee meetings, and other proceedings, using computerized recording equipment, electronic stenograph machines, or stenomasks.AI helps
Record depositions and other proceedings for attorneys.AI helps
Ask speakers to clarify inaudible statements.Needs a human
Proofread transcripts for correct spelling of words.AI helps
File a legible transcript of records of a court case with the court clerk's office.AI helps
Transcribe recorded proceedings in accordance with established formats.AI does it
Take notes in shorthand or use a stenotype or shorthand machine that prints letters on a paper tape.Needs a human
File and store shorthand notes of court session.AI helps
Respond to requests during court sessions to read portions of the proceedings already recorded.AI helps
Swear in witnesses.Needs a human
Log and store exhibits from court proceedings.Needs a human
File exhibits.Needs a human
Verify accuracy of transcripts by checking copies against original records of proceedings and accuracy of rulings by checking with judges.AI helps

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is , and vendor studies are labelled as such.

When could it be replaced?

When AI could largely do this job: 2036–2049

Most likely between 2036 and 2049 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten behind its .

Today
Will AI replace this job?
A little.
By 2045
90%
of our scenarios have AI largely doing this job by 2045 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)
By 2060
100%
of our scenarios have AI largely doing this job by 2060 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: AI could do a little of this job (A little.)100%Today2030: 30.0% of scenarios: AI could do a little of this job (A little.)30%2030: 70.0% of scenarios: AI could partly do this job (Partly.)70%20302035: 30.0% of scenarios: AI could partly do this job (Partly.)30%2035: 50.0% of scenarios: AI could mostly do this job (Mostly.)50%2035: 20.0% of scenarios: AI could largely do this job (Largely.)20%20352040: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2040: 60.0% of scenarios: AI could largely do this job (Largely.)60%20402045: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%2045: 90.0% of scenarios: AI could largely do this job (Largely.)90%20452050: 100.0% of scenarios: AI could largely do this job (Largely.)100%20502055: 100.0% of scenarios: AI could largely do this job (Largely.)100%20552060: 100.0% of scenarios: AI could largely do this job (Largely.)100%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%100.0%0.0%
20300.0%0.0%70.0%30.0%0.0%
203520.0%50.0%30.0%0.0%0.0%
204060.0%40.0%0.0%0.0%0.0%
204590.0%10.0%0.0%0.0%0.0%
2050100.0%0.0%0.0%0.0%0.0%
2055100.0%0.0%0.0%0.0%0.0%
2060100.0%0.0%0.0%0.0%0.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.1 out of 5 for consequence and decisions 3.4 out of 5 for impact; someone has to answer for them.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Clients want a personFace-to-face contact is rated 3.7 and physical closeness 2.9 out of 5; caring for or serving people is 1.6 out of 5 in importance.
LicensingUsual entry requirement (BLS): postsecondary nondegree award, then short-term on-the-job training.
Physical work7% of the task time is physical; robots have been shown on 100% of that time.
RegulationWorkers rate responsibility for others' health and safety 1.1 out of 5.

What would it cost to hand the work to AI?

The share of the year AI could handle (782 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$80–$7,820
A person’s wage for the same hours
$15,840–$49,090

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

7%
of the task time is physical work
None needed
the kind of robot the physical work would need
Little of this job is physical, so robotics is not what holds AI back.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 33%AI helps 45%AI does it 22%
Writing · 21.3% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 5.2% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 8.4% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 0% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 27% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 12.4% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 19.5% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 6.2% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 33%AI helps 45%AI does it 22%
How exposed is it?

Still needs a human: 66/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 33% needs a human, 45% AI helps, 22% AI does it. Still needs a human: 66/100 ↑ safer. Will AI replace them? A little.

People are asking

How often people ask whether AI will replace this job: on Google, and by estimate, in AI assistants.

In the US

140
Google searches a month, 12-month average to August 2026
Google searches a month, September 2025 to August 2026: from 110 to 210
7
estimated questions to AI assistants in September 2026
Estimated questions to AI assistants a month, October 2025 to September 2026: from 2 to 7
11
Google searches a month for every 1,000 people in the job
5th of 197 among all jobs we have search data for

In the UK

10
Google searches a month, 12-month average to August 2026
28
Google searches a month for every 1,000 people in the job in the UK (estimated)
2nd of 197 among jobs we have UK search data for

Source: DataForSEO, US and UK, fetched October 3, 2026. Google figures are Google Ads’ rounded monthly averages. The AI figure is DataForSEO’s estimate from Google’s “People also ask” data, not a count from any AI assistant. UK workers are ONS employment figures matched to this job, so the UK rate per 1,000 is an estimate. Search figures are not part of our open dataset.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 66/100 ↑ safer. Will AI replace them? A little.

ChatGPTPartly

AI will automate more transcription tasks, but human court reporters will still be needed for accuracy, certification, complex proceedings, and legal accountability.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudePartly

AI will automate much of the transcription workload, but courts will likely still need human reporters for certification, real-time accuracy in complex proceedings, and legal accountability, at least within the next decade.

claude-sonnet-5 · asked 2026-10-03
GeminiPartly

While AI will increasingly handle routine transcription and create hybrid workflows to address labor shortages, human court reporters will remain essential for complex proceedings requiring high-stakes accuracy, legal accountability, and real-time discernment.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will automate routine transcription and reduce demand, but human reporters will likely remain essential for certified, high-stakes proceedings.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Court Reporters and Simultaneous Captioners? A little. Still needs a human: 66/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/court-reporters-and-simultaneous-captioners/ (accessed 4 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

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The badge updates itself with each release and links back to this page.

Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.