TL;DR: The question people ask about this degree is no longer what graduates do. It is whether the degree still means anything now that machine translation is competent. The public employment data falsifies both the pessimistic and the complacent answer. According to 2025 figures from the U.S. Bureau of Labor Statistics, the six occupations this degree typically opens are projected to change between minus 1 percent and plus 2 percent between 2025 and 2035: all flat, none meaningfully different from the others. Median annual pay across those same six occupations ranges from 60,170 dollars to 90,390 dollars, a difference of 50 percent. The highest pay sits where the language skill is bound to a technical domain; the lowest sits where the language skill is the whole job. The return on this degree is decided by what the language is attached to, not by the degree itself. Below: the verified table, the framework derived from it, and four decisions for anyone in or out of the programme.
Most writing about this degree opens with a module list and closes with a list of job titles. Both are accurate and neither helps you decide anything, because they skip the real question: why do two people with the same degree end up thirty thousand dollars a year apart?
That question has a public answer, and it rests on measurement rather than opinion.
What the degree is and what it teaches
English Language and Literature is a three or four year undergraduate programme, depending on the country, that studies the structure and history of the English language alongside the literature written in it. It sits in arts, humanities or social science faculties, and many universities require a language proficiency test or a preparatory year before the degree proper begins.
The programme is typically built on four strands: linguistics and phonology, period literature from the medieval and Renaissance through to the modern, translation theory and practice, and critical reading and academic writing. All four train work on text. The real output of the degree is not a language but a method: the ability to tell what a text says, what it does not say, and why it was built the way it was.
That distinction matters for reading the data that follows.
Verified data: six occupations, two different distributions
The figures below are taken from the U.S. Bureau of Labor Statistics Occupational Outlook Handbook. Absolute pay levels are specific to the United States labour market; read the table for the ordering between occupations rather than for the numbers themselves if you work elsewhere.
| Occupation (United States, 2025) | Median annual pay | Employment, 2025 | Outlook, 2025 to 2035 | Employment change |
|---|---|---|---|---|
| Technical writers | 90,390 dollars | 46,400 | 1% | +400 |
| Editors | 77,920 dollars | 105,000 | -1% | -1,100 |
| Writers and authors | 76,910 dollars | 140,300 | 0% | -500 |
| Public relations specialists | 74,750 dollars | 314,500 | 2% | +5,700 |
| High school teachers | 72,040 dollars | 1,087,500 | 0% | -2,500 |
| Interpreters and translators | 60,170 dollars | 73,900 | 2% | +1,500 |
Verified data. Source: U.S. Bureau of Labor Statistics, Occupational Outlook Handbook, 2025 quick-facts panels for each occupation.
Now read the two columns separately.
The growth column is almost flat. All six occupations sit between minus 1 percent and plus 2 percent, a total spread of three points. Sorting these occupations into growing and shrinking is not a distinction the data supports.
The pay column is not flat. The gap between top and bottom is 30,220 dollars, a difference of 50 percent.
Putting the two distributions side by side produces something neither source states on its own.
| Comparison | Spread | What follows |
|---|---|---|
| Employment growth across the six occupations | 3 points, from -1% to 2% | Occupation choice barely matters for growth |
| Median pay across the six occupations | 50%, from 60,170 to 90,390 dollars | Occupation choice is decisive for pay |
CEOtudent editorial framework: spreads calculated from the verified table above. The source does not draw this comparison.
The ordering makes the pattern legible. The best-paid occupation is the one where the language skill is bound to a technical domain: technical writing. The worst-paid is the one where the language skill is the entire job: translation. The four occupations in between fall along the same axis.
So the variable that determines the return on this degree is not the degree. It is what the language is attached to.
The CEOtudent Domain Attachment Framework
Here is that pattern made usable.
| Level of attachment | What it means | Example | Position relative to AI |
|---|---|---|---|
| Unattached | The language skill is the whole job; no subject domain | General-purpose translation | Most exposed: the work is compared directly against machine output |
| Loosely attached | You work in a sector but the job needs no domain knowledge | General content editing | Partly sheltered: substitutable, because no domain knowledge is required |
| Domain-attached | The language skill operates together with specific technical knowledge | Technical writing, legal translation, medical translation, localisation engineering | Most sheltered: errors are costly and verification requires domain knowledge |
| Domain-attached with accountability | You are answerable for the accuracy of the output | Regulatory documentation, clinical text, court interpreting | Structurally sheltered: accountability cannot be delegated to a tool |
CEOtudent editorial framework. Not survey data; derived from the pay ordering above and the agency statement below.
The last column is not speculation. On its interpreters and translators page, the Bureau of Labor Statistics states that computer tools including artificial intelligence are making the work of translators and localisation specialists more efficient, and that many of these jobs cannot be entirely automated because computers cannot yet produce work comparable to what human translators do. The same agency projects 2 percent growth for the occupation over the decade and roughly 6,000 openings a year on average.
Read together, those three facts sit outside both popular narratives. The occupation is not ending, and it is not expanding either. Hiring comes from replacement rather than growth.
The real difficulty of the degree
What makes this degree hard is usually not the level of English. A preparatory year and the first undergraduate year mostly level that out. The difficulty is spending three or four years dismantling the structure underneath a language you thought you already knew, while reading across history, philosophy and anthropology alongside the literature.
That difficulty is also the degree’s most transferable output. Seeing the assumption behind a text, telling which claim rests on which evidence, and rebuilding a statement are skills that become more useful, not less, in an environment where the volume of produced text is rising fast. It is one of the more concrete illustrations of why human judgment is becoming so valuable.
Who does well in this programme
The public data does not answer this directly, so what follows is observation rather than claim: students who get the most out of the programme tend to treat reading volume as an input rather than a burden. Patience, attention, strong memory and verbal ability are the usual list. One item is almost always missing from it: an interest in a second subject.
On the evidence of the table above, that is not a personality trait. It is a career variable. A language graduate with no second field stays in the unattached row.
Four decisions for anyone studying or holding the degree
One. Choose the second field and write it down. Law, health, software, finance, energy, public policy. Which one matters less than that there is one. Write the choice in a sentence and date it.
Two. Learn the field’s vocabulary, not the field. You do not need an engineering degree to be a technical writer. You need to understand correctly what engineers are saying, and to notice when you have not. That is where the gap sits.
Three. Use AI tools as a measuring instrument rather than a rival. Draft a text yourself, have the machine draft it, then compare the two. Write down where the difference appears. After thirty days you hold evidence of where your own contribution concentrates, which is both a career input and a negotiating one.
Four. Look at work that carries accountability. The bottom row of the framework is not an accident. Work where you are legally or professionally answerable for the accuracy of the output is the hardest to automate, because what gets automated is text production and what cannot be transferred is responsibility.
An honest note about pay
An earlier version of this piece carried salary ranges with no source attached. They have been removed. Pay data moves quickly with country, sector, experience and year, and an unsourced range is good for nothing except supporting a bad decision. The table above states its source and its year, and should be read for the ordering between occupations rather than as a figure to expect.
Frequently asked questions
Does machine translation make this degree pointless?
The data does not support that. The Bureau of Labor Statistics projects 2 percent growth for interpreters and translators between 2025 and 2035, roughly 6,000 openings a year, and states that computers cannot yet produce work comparable to human translators. The correct reading is that the occupation is not ending but is not expanding either. That makes the choice of attached field decisive, not the degree pointless.
Which of these occupations pays best?
Among the six in the table, technical writing, at a median of 90,390 dollars a year. Interpreting and translation is the lowest at 60,170 dollars. The gap is 50 percent, and it cannot be explained by growth rates, because the growth rates are almost identical.
Is teaching still a sensible route?
On the table, high school teaching has a median of 72,040 dollars and a projected 2025 to 2035 employment change of minus 2,500. It is neither contracting sharply nor growing. That does not make it a poor occupation; it makes entry competitive and the degree alone insufficient as a differentiator.
What should I do while I am still studying?
One thing: acquire a second field and read in it. That is the single clear message in the data above. The language skill alone occupies the lowest-paid position; attached to a field it occupies the highest.
Do these figures apply outside the United States?
The absolute numbers do not; pay levels and employment volumes vary by country. What transfers is the ordering between occupations and the mechanism behind it: attaching language work to a domain raises pay because it raises the cost of error and the difficulty of verification. That mechanism is not country-specific.
Sources
United States Bureau of Labor Statistics, Occupational Outlook Handbook, Interpreters and Translators, 2025 quick facts and job outlook section.
United States Bureau of Labor Statistics, Occupational Outlook Handbook, Technical Writers, 2025 quick facts.
United States Bureau of Labor Statistics, Occupational Outlook Handbook, Editors and Writers and Authors, 2025 quick facts.
United States Bureau of Labor Statistics, Occupational Outlook Handbook, Public Relations Specialists, 2025 quick facts.
United States Bureau of Labor Statistics, Occupational Outlook Handbook, High School Teachers, 2025 quick facts.
United States Bureau of Labor Statistics, industry and occupational employment projections overview for the 2025 to 2035 period.
United Nations Educational, Scientific and Cultural Organization, International Standard Classification of Education definitions for humanities programmes in higher education.
This content was compiled with the support of AI following in-depth research, then written and prepared for publication by the CEOtudent editorial team.
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