Most organizations rely on human-centric services for translation of documents and communications, which are both costly and time-consuming. Long, complex documents are typically translated at an average pace of just 300 words per hour. In addition, when dealing with different variations of contracts or policies, translators taking a full document translation approach will wind up translating common clauses and content repeatedly. The process is highly inefficient, resulting in redundant translation work and introduces risk of inconsistencies in translations of common or regulated content.

Because of the cost and time involved, most organizations translate only the bare minimum of customer-facing materials — typically just enough to meet regulatory requirements — rather than proactively catering to the diverse language needs of their entire customer base.

AI translation is advancing rapidly, opening up avenues for businesses to automate and accelerate translation and translation accuracy checks. Research from the University of Washington shows that AI, when combined with human oversight, can produce high-quality translations at just 5% of the cost of traditional methods. For large, regulated organizations, the decision should not be whether or not to adopt AI — instead, the question becomes: What is the best way to securely and effectively leverage it? There are several approaches available in the market today that can help organizations increase efficiency and accuracy, while reducing the cost of translation.

Standalone AI tools like ChatGPT or DeepL may seem like the natural choice due to their effective translation capabilities; however, using them independently of the systems that document teams rely on to create and manage communications forces users to waste time copying and pasting content between systems. Additionally, they can introduce security risks when teams are given access to these platforms without robust guardrails in place. Users may inadvertently input proprietary information or sensitive customer data that is used to train public AI models, increasing the risk of breaches, compliance violations and damaging leaks.

Another option for leveraging AI translation is a post-composition process in which AI translates completed documents from the original language to another after they are personalized and generated by an upstream composition system, but before being sent to members. This on-demand approach may seem appealing because it promises automation without touching the existing CCM architecture. However, it comes with significant limitations.

With many post-composition translation processes, there’s no way to precisely control what will be sent to customers. You can review sample translations AI produces, but the variable nature of AI algorithms means just because one sample appears accurate doesn’t mean each individual translation will be consistent. While glossaries and translation memory can help ensure specific terms and phrases are translated accurately, with variable data and dynamic content added in, achieving broader consistency would require building and maintaining such an extensive library of approved translations that it requires replicating much of the manual processes you're trying to replace. This lack of control is particularly risky for regulated communications, where even minor translation errors can result in customers receiving incorrect information, compliance violations with fines and reputational harm. While AI translation has become incredibly sophisticated, it still requires oversight from people who understand the nuances of your industry, your company and your products and can validate approved content.

Another consideration is that because AI translates documents after personalized customer data has been added, sensitive PII and PHI will be processed by the platform’s AI algorithm. This makes it essential for users to ensure the platform has robust safeguards in place to prevent unintended exposure or data leaks.

Automating document layouts with AI can also pose risks to the visual integrity of communications, as different languages often require adjustments to spacing, pagination and design due to variations in text length. Without oversight, AI may produce distorted fonts, misaligned elements or missing content that compromise readability and brand presentation. Additionally, the on-demand nature of this approach—translating documents each time they are accessed or sent — can result in unpredictable and substantially more translations with high processing costs.

CCM solutions with integrated AI translation capabilities empower document teams to manage the entire authoring, translation and approval process within a single secure system. This approach offers distinct advantages over standalone AI platforms, including eliminating the inefficient process of transferring content to and from a separate AI translation tool. Translated content is stored alongside English versions for effective management and revision as required. Look for a platform built with the needs of regulated communications in mind, one that provides safeguards to protect customer data and proprietary information from being leaked or used as training data by third-party platforms. These systems should also include granular permissions so administrators can control who can edit content and utilize AI translation capabilities, along with full audit trails of content changes in the system.

Unlike post-composition tools that require you to fully relinquish control to AI, these platforms can offer both automated translation accuracy checks and support a “human-in-the-loop” approach to enable corrections and human-led validation before documents are distributed to customers. By integrating these translation processes into a comprehensive workflow, you can automate translation as content is changed in the primary language, and quickly introduce new languages.

It’s critical to recognize that not all customer communications management platforms are created equal and that selecting the right platform requires closely examining how AI is implemented, the ability to ensure the security of your content and inject human led manual controls when needed. By applying AI to translation processes and choosing the right approach, businesses can improve the speed and cost-effectiveness of translating customer communications, freeing up resources to proactively cater to today’s increasingly diverse, multilingual customer base. In doing so, organizations can help create a more inclusive and equitable environment for non-English speakers, enhancing customer experiences and outcomes and improving trust, loyalty — and, ultimately, revenue.