In 2025, SaaS companies can no longer have the luxury of relying on a single-language strategy. To ensure success on international markets, high-quality localisation is a key tool for growth. AI, post-editing or human translation – what is the right approach for each situation?
This guide will help you determine the best approach depending on your needs. You will learn:
- Why localisation has become a key factor in the success of SaaS companies
- What AI can and cannot do for your translation strategy
- When to opt for post-editing over human translation
- The limits of each method and the pitfalls to be avoided
- How to structure a hybrid and scalable strategy, tailored to the challenges of your business.
Why localisation is a strategic tool for SaaS companies
Driven by the digital transformation of companies, the Software as a Service (SaaS) market is currently experiencing phenomenal growth throughout the world, with a value set to rise from USD 315.68 billion in 2025 to USD 1,131.52 billion by 2023 (Fortune Business Insights, July 2025).
However, this impressive growth is less reliant on national markets that are reaching saturation point. To ensure continued growth, SaaS companies must look beyond the borders of their local market. Against this backdrop, localisation is emerging as a key issue. According to CSA Research:
- 2/3 of consumers state that they prefer accessing content in their native language
- 40% of consumers state that they won’t buy products or services not available in their native language
Localisation therefore has a direct impact on turnover and uptake, but also on user experience and retention. Quality is of utmost importance. The challenges are more complex than they may seem – of course, localised content must be translated accurately, but it must also reflect the tone, format and cultural sensitivities of the target market.
While advances in AI and automation have made these tools invaluable for large-scale international expansion campaigns, the human factor remains crucial to ensuring the desired level of quality. They key is finding the right balance.
AI translation – fast and budget-friendly, but has its limits
Is it possible to rely on a strategy based entirely on AI, without human intervention? The development of LLMs (Large Language Models) and other neuronal networks, considerably more effective than older machine translation tools, has undoubtedly opened the door to new opportunities.
With AI, it is now possible to translate large amounts of content at a lower cost and with unprecedented quality. It also allows for relatively easy integration into business workflows and, above all, enables the mass processing of content in multiple languages.
However, this solution has major limitations:
- Data confidentiality issues with certain tools
- Tools prone to misinterpretation, requiring a higher degree of expertise and vigilance
- Difficulties with colloquial expressions, specific references or humour
- Difficulties managing specialised terminology
- Difficulties with UI content, which is extremely fragmented, and often lacks context
- Limited understanding of the cultural sensitivities of the target market
- Lack of consistency when it comes to the brand’s “message”
All these reasons make it difficult for SaaS companies to consider using AI without human expertise for the vast majority of their content.
However, it remains an excellent starting point, in particular for the rough translation of non-sensitive internal content, for technical support, or as a basis for post-editing.
AI post-editing – the right balance between scalability and quality?
Post-editing, or MTPE (machine translation post-editing), consists of first having the content translated using machine translation, then having it reviewed and corrected by a human linguist, who will check that the meaning and terminology are correct, and ensure that the style and tone are appropriate.
This blended approach has gained widespread acceptance in recent years because it reduces costs by 30 to 50% compared to traditional translation/editing/proofreading processes, and reduces lead times by 40%. When it comes to quality, it resolves around 80% of rough AI translation issues, in particular by eliminating inconsistent translations and critical errors, and ensures the consistent application of glossaries, termbases and style guides.
However, these cost savings and increased productivity are only possible if the post-editing required by the linguist remains limited. Poor machine translation, whether due to an overly complex source text or a poor-quality translation tool, will require extensive corrections, cancelling out the expected time savings.
Similarly, for products to remain profitable, post-editing aims to achieve a “satisfactory” level of quality rather than excellence. Improvements in machine translation quality, bolstered by the advent of AI, are making it an increasingly reliable, profitable and effective tool, which requires fewer human corrections than in the past.
MTPE can therefore meet the needs of SaaS companies between Seed and Series C funding rounds, who regularly need to translate large volumes of content, whether product updates or documentation. In general, it offers a good trade-off between profitability, roll-out speed and quality, and is particularly well suited to help pages, knowledge bases and simple marketing pages, FAQs and large-scale automated emails.
Human translation by native speakers – when and why this is the best option
Fully human translation, carried out by specialist native speakers, remains the most reliable approach to date, and offers the best quality – human expertise ensures a better understanding of the context, linguistic nuances and cultural sensitivities, but also compliance with client instructions and the terminology specific to the sector.
It is therefore particularly well suited to strategic and high value-added content, where quality requirements are at their highest. This could involve highly emotive marketing content, or key UI or UX content, which automated solutions struggle with due to the lack of context.
This solution also offers the most guarantees in terms of regulatory and compliance issues, particularly important in sectors such as healthcare, LegalTech, finance and e-learning.
Its main drawbacks include longer lead times and higher costs, making it a solution best kept for key content for companies that don’t want to strain their budgets.
It should also be noted that it offers a higher return on investment in priority markets, where its advantages can be crucial.
Comparison – AI, post-editing, native-speaker translation
| Criterion | AI alone | AI with post-editing | Human translation |
| Cost | Low | Moderate | Higher |
| Speed | High | Moderate | Lower |
| Brand consistency | Limited | Satisfactory | High |
| Linguistic quality | Limited | Satisfactory | High |
| Best use case | Non-sensitive internal documents, technical support, rough translation as a basis for post-editing | Help pages, FAQs, onboarding, emails | Landing pages, UI, UX, brand content, regulatory and compliance issues |
What is the best localisation strategy in 2025?
As you can see, each translation method has its advantages and disadvantages in terms of cost, speed and quality.
The more automated an approach is, the faster and more cost-effective it is, but it is also less reliable and less focused on quality. Although post-editing might offer a good trade-off between these different factors, it is not the best option in all situations. “Hybrid” models, combining all three approaches, are now considered the most appropriate within the sector: the most successful SaaS companies segment their content by type, criticality and market in order to tailor the method to their needs.
While every company has its own unique needs, the following model can serve as a good starting point:
- Rough AI translation for internal content or non-critical support content
- Post-editing for documentation (help pages, FAQs) and large-scale marketing resources.
- Human translation for key content and strategic markets.
Your translation strategy – a key factor in your growth
In 2025, international growth is a must for the SaaS sector, and poor-quality localisation can be costly – loss of potential clients, lower uptake and retention rates, damage to brand image and reputation, but also a waste of time and resources.
SaaS companies that thrive internationally understand this challenge and place localisation at the heart of their international growth strategy. These companies are not content with a single, generic approach, but give themselves the tools to succeed by skilfully combining technology and human expertise.
We’ll help define the best strategy for you.
