The Impact of Technology on Localisation: Macro and Micro Layers

Localisation was born with technology and it goes on changing with technology. The impact of technology on localisation, however, cannot be read on a single plane. The literature separates that impact into two layers: macro effects, which reshape the whole industry, and micro effects, which change what happens on the translator’s screen. Keeping the two apart makes the transformation far easier to read accurately.

Contents

The distinction rests on the framework proposed by O’Hagan (2013). The macro level describes how general technological progress transforms society and the market. The shift from the static web to the dynamic web, the spread of smartphones and the emergence of cloud-based platforms all belong to this level. The micro level comes down to the localisation task itself, that is, to how the daily work actually proceeds.

This article takes the two layers in turn and then shows how each feeds the other. For anyone buying translation, the distinction is not an abstract academic preference; it lets you see which change affects you and how much, when you set your budget, your timetable and your quality expectations.

Why Is the Impact of Technology on Localisation Read in Two Layers?

Debates about technology usually narrow to a single question: is this tool going to take my job? The subject is far more layered than that. The macro level determines which products become localisable and how the market takes shape. The micro level changes how that work is actually carried out.

The two levels are not independent of each other. The spread of smartphones is a macro development, and the emergence of app localisation as a distinct specialism follows directly from it. Yet the same development means working, on the translator’s screen, with short strings, character limits and fragments of text stripped of context.

Holding the distinction in mind helps on the buying side too. Understanding why the turnaround times you see for a line item in a quotation have shortened, or why the price for certain content types has not fallen, usually depends on reading these two layers separately.

Criterion	Macro effect	Micro effect
Scope	The market, product types, the definition of the profession	The task, the workflow, the work at the screen
Example	The spread of cloud localisation platforms	A machine suggestion appearing when there is no memory match
Pace	Accumulates over years	Can change overnight with a version update
Who decides	Technology providers, large platforms	The project manager, the tool configuration
How it reaches the buyer	New service items, new content types	Turnaround time, unit price, quality profile

Macro Effects: New Media, New Genres, New Platforms

Macro effects arise from forces such as technological progress, the globalisation of the translation market, automation, web-based collaborative working practices and user habits. These forces do not shape individual projects; they determine the forms in which localisation can exist at all. Chapter 12 of the book lists five typical examples at this level.

1. The emergence of new forms of localisation, such as virtual reality localisation.
2. The birth of new localisable digital genres: short video posts, promotional posts and similar content.
3. Practical applications of new technologies, for example machine translation layers embedded in social media posts.
4. The spread of cloud-based localisation platforms and the migration of the work to the server side.
5. The institutionalisation of crowdsourced translation and fansubbing practices in audiovisual material.

Look at the list and the common thread appears: every item brings a content type or a working environment that did not exist before into the scope of localisation. The first consequence of macro effects, then, is not the loss of work but the widening of the job description. A widening description brings new demands for competence with it.

Another feature of macro effects is that they are slow but irreversible. Content management systems did not spread overnight; once they had settled in, however, the older form of web localisation based on exchanging files never came back. A similar process of settling in can be spoken of for artificial intelligence tools today, although the details of the outcome are still uncertain.

Micro Effects: What Has Changed at the Translator’s Desk?

Changes at the micro level affect the actual work of localisers, project managers and engineers. Translation memory workflows supported by machine translation, post-editing of machine translation and interactive machine translation are typical examples at this level. All of them produce one shared result: the translator no longer meets an empty box but a ready-made suggestion.

There is a cognitive side to this change. Starting from a suggestion can speed the process up, but it also affects the product. Guerberof-Arenas and Toral (2022) report that a machine translation suggestion can steer the translator and that the resulting text differs in terms of creativity. Gain and loss sit on the table at the same time.

Nor are micro effects confined to the moment of translation. The online use of termbases and document databases has changed the way research and problem solving are done. Professional networks for translators, for their part, have transformed the practices of finding work and seeking advice. For details, see the technology articles in our knowledge centre.

Continuous Localisation: The Micro Consequence of a Macro Decision

The spread of continuous localisation models is a macro development. Product releases no longer arrive as monthly packages but as a steady stream of small updates. Localisation is obliged to keep to that rhythm. The decision is taken at senior level, yet the party that feels the consequence most is the translator at the desk.

Its micro-level equivalent is this: small packages, short turnaround times, narrow context and frequently repeated quality checks. Working without seeing a text as a whole becomes the norm. That raises the risk to consistency and makes terminology management more critical than it used to be.

On the buyer’s side, expectations have to be reset. In a continuous model there is no single large delivery but a regular flow of small ones. Budget planning follows a monthly flow, and quality control is run not at one point but distributed across the cycle.

How Has the Localisation Team’s Content Remit Widened?

Torres del Rey (2022) draws attention to a side effect of the continuous localisation model: some localisation units no longer work only on the digital product. Customer support databases, training and human resources portals, social media accounts, search engine content and digital marketing copy now fall within the same team’s remit.

At the micro level this widening calls for new skills. The same person may deal with interface strings one day, a support article the next and an advertisement the day after. Each genre asks for a different style, a different quality criterion and a different tool configuration.

Briva-Iglesias and O’Brien (2022) note that in the age of automation and artificial intelligence the localiser’s role is moving closer to language engineering. This is not the disappearance of the translator’s job description but the settling of a technical layer into it. We set out which services fall within this scope on our services page.

Working from a Suggestion: The Unseen Price of the Speed Gain

In most tools today, translation memory and machine translation work side by side. If there is a memory match, it comes up; if not, a machine suggestion steps in. The translator therefore almost always edits a suggestion instead of writing the segment from scratch. The process speeds up, but the starting point is no longer neutral.

Adaptive and interactive machine translation architectures take this picture a step further. The system learns from the choices post-editors make and reduces the burden of correcting the same error or the same term choice over and over. This is less a form of automation than of human-guided adaptation.

The question to ask on the buying side is this: for this content type, is speed the priority or original phrasing? For technical documents with a high repetition rate, working from suggestions is a reasonable choice. For creative marketing copy, the same workflow can produce an unwanted uniformity.

The Türkiye context

In Türkiye, macro effects mostly arrive from outside: the tool ecosystem, the cloud platforms and the engine providers are in the hands of global players. The local side is in the position of adopting these tools. That means the burden of adaptation at the micro level stays with teams in Türkiye.

The linguistic structure of Turkish can make that burden heavier. Its agglutinative structure and relatively free word order make it hard to choose the right inflection in short interface strings without context. An expression that is a single word in an English source may take different suffixes in Turkish depending on the sentence it sits in.

Another heading is data management. Cloud-based platforms and engines are a convenience at the macro level; but where texts contain personal data, KVKK obligations call for concrete decisions at the micro level. Which file may be uploaded to which environment should be settled in writing before the project starts.

What does this mean for you?

If you are buying translation, it makes life easier not to treat technology as a single box. Macro changes determine which services you can buy; micro changes determine how the service you buy is produced. Separating the two lets you ask the right questions when you compare quotations.

1. List your content types and decide, for each one, whether speed or originality is the priority.
2. Ask your supplier whether machine suggestions are used in the workflow and have the answer written into the quotation.
3. If you are moving to a continuous delivery model, prepare the term list and the style guide in advance.
4. Make the supply of a screenshot or a context note for interface strings a standard step in the process.
5. Define a separate processing rule for files containing personal data and add it to the contract.

These steps let you benefit from the speed technology brings while keeping the risk to quality manageable. If you are not sure which approach your project needs at which layer, share your content inventory and request a quotation; we can draw up a map of priorities together.

Frequently asked questions

What is the distinction between macro and micro effects good for?

The distinction lets you see whether a change affects the market or the daily workflow. At the macro level, new product types and platforms come into being; at the micro level, the translator’s relationship with the text changes. When you set budgets and timetables, the two need to be assessed separately.

Is continuous localisation a macro change or a micro one?

It can count as both. Adopting a continuous delivery model is a macro transformation; but the translator’s consequent work with small packages, short deadlines and narrow context is a change at the micro level. The bill for a macro decision is usually paid at the micro level.

Does working from a machine translation suggestion affect the product?

Research shows that starting from a ready-made suggestion can steer the translator’s choices. The study by Guerberof-Arenas and Toral reports that texts post-edited from machine translation were found less creative than texts translated directly by a human. The gain in speed can come at a price.

What content does a localisation team look after today?

The remit is not limited to the product interface. Customer support databases, training and human resources portals, social media, search engine content and digital marketing copy can all fall within the same team’s remit. This widening moves the localiser’s role closer to language engineering.

Sources

• Jiménez-Crespo, M. A. (2024). Localization in Translation. Routledge, pp. 243-245.
• O’Hagan, M. (2013). The impact of new technologies on translation studies. Handbook of Translation Studies.
• Guerberof-Arenas, A. & Toral, A. (2022). Creativity in translation: machine translation as a constraint for literary texts. Translation Spaces.
• Torres del Rey, J. (2022). Localization. Routledge Handbook of Translation and Technology.