AI Is Making Lawyers Faster—But Translation Workflows Are Falling Behind

Artificial intelligence is no longer a theoretical issue for the legal profession. It is already influencing how lawyers review information, communicate with clients, and manage complex matters. The real question is no longer whether AI has entered legal practice. It has. The more important question is where adoption is actually happening—and where it is still lagging behind.

That distinction matters because legal work does not end with research, drafting, and document review. In many matters, especially those involving cross-border business, multilingual clients, foreign-language evidence, medical records, immigration filings, patents, and international disputes, translation remains a core operational requirement. And while AI adoption is rising in legal practice generally, multilingual workflows appear to be modernizing more slowly.

Note on approach: In high-stakes legal translation, accuracy, confidentiality, and accountability remain critical. At GTS, we do not rely on raw machine translation for legal document translation services. Our workflows are built around professional human translators, with technology used to support consistency, terminology management, and efficiency—not to replace legal judgment.

AI Is Already Delivering Measurable Results in Legal Practice

One reason AI has become such a dominant topic in the legal sector is simple: the productivity gains are no longer hypothetical. According to Clio’s 2026 Legal Trends report for Canadian law firms, lawyers using AI say it is helping them respond faster to clients, improve the quality of their work, and increase firm revenue.

Those are not trivial benefits. Faster response times affect client experience. Better quality affects work product and internal efficiency. Increased revenue affects the economics of the firm. In other words, AI is not only changing how lawyers work. It is changing how firms operate.

That makes one point clear: the legal profession is past the stage of asking whether AI can help. In many contexts, it already does.

But Adoption Is Still Uneven

At the same time, adoption remains incomplete. Even where interest is high, full implementation appears limited. That is why the current moment is best understood not as a question of technical feasibility, but as a question of workflow maturity.

This is not a technology gap. It is a strategy gap.

Many firms and legal departments now understand what AI can do in principle. The harder issue is deciding how to integrate it into actual legal operations without compromising quality, confidentiality, accountability, or client trust. That is where implementation slows down.

Translation Workflows Are a Good Example of the Lag

Translation is one of the clearest examples of this uneven adoption. While AI tools are increasingly used for drafting assistance, summarization, and review support, multilingual legal workflows often remain manual or only partially automated.

That is not surprising. Legal translation sits at the intersection of language, risk, and legal accuracy. In many matters, the translated document is not just informational. It may be submitted to a court, reviewed by counsel, relied on in a transaction, filed with a government agency, or used to communicate rights and obligations to a client.

That raises the stakes considerably.

According to DeepL’s Borderless Business: Transforming Translation in the Age of AI study, 35% of companies worldwide still handle translation entirely manually, while 33% rely on more traditional translation automation tools that still depend heavily on human review and editing. Only 17% report deploying next-generation AI tools.

That means the majority of translation workflows remain either manual or only partially modernized, even as AI becomes more accepted elsewhere in professional work.

Why Legal Translation Is Harder to Automate Than Other Tasks

There are several reasons translation workflows may be slower to modernize in legal settings than more general office tasks.

Risk sensitivity: Legal translation errors can affect admissibility, compliance, negotiations, claims, filings, and client communication.

Document complexity: Legal materials often involve contracts, evidence, medical records, corporate filings, patents, court documents, and certified personal records.

Terminology and nuance: Accuracy depends not only on language fluency, but also on legal context and document purpose.

Privacy and confidentiality: Law firms are often reluctant to upload sensitive client materials to cloud-based AI tools. Legal documents frequently contain privileged information, personal data, or confidential business details, and uncontrolled use of external platforms can raise concerns around data security, client confidentiality obligations, and regulatory compliance.

Human accountability: In many matters, law firms still need qualified human review, even when technology is used in the workflow.

For those reasons, translation in legal practice is less likely to be treated as a pure automation problem. It is more often treated as a controlled workflow problem: where can technology improve speed, consistency, and turnaround without compromising the reliability, confidentiality, and defensibility of the final output.

What the Legal Market Seems to Be Saying

Taken together, the available signals point in the same direction. Legal professionals are increasingly open to AI. Many are already seeing operational benefits. But that does not mean every legal workflow is modernizing at the same pace.

A LinkedIn poll shared by a legal professional recently found that 77% of respondents said AI had changed their approach to reviewing complex legal matters, either significantly or to some extent. That is not a scientific survey, and it should not be treated as one. But it does show how normalized AI has become in legal discussion and day-to-day thinking.

By contrast, translation-related adoption data suggests a slower and more cautious pattern. That makes sense. In legal work, multilingual workflows are often where efficiency gains collide most directly with risk tolerance.

The Real Opportunity Is Not AI Alone—It Is Better Workflow Design

The firms that benefit most from AI are unlikely to be the ones that merely “use AI.” They are more likely to be the ones that integrate it intelligently into well-defined workflows.

That is especially true for translation.

In practice, the future of legal translation is unlikely to be fully manual on one side or fully autonomous on the other. The more realistic model is structured use of technology inside a workflow that still includes expert human oversight, especially for high-stakes legal content.

That is why the real competitive advantage may not come from adopting AI first. It may come from adopting it well.

What This Means for Law Firms

For law firms, the takeaway is straightforward. AI is already changing legal work. But not every operational area is moving at the same speed, and translation is one of the clearest examples.

Where multilingual matters are involved, firms still need workflows that are:

• Fast enough for real deadlines
• Reliable enough for legal scrutiny
• Flexible enough to handle different document types and language pairs
• Transparent enough to support budgeting, estimates, and client communication

That is why firms increasingly want not just translation itself, but a better process around translation: faster estimating, clearer turnaround expectations, and dependable review.

Conclusion

AI has already proved that it can improve legal work. The measurable gains are there. But adoption is not uniform, and translation workflows remain an area where modernization appears to be lagging behind broader legal AI enthusiasm.

The lesson is not that translation is resistant to innovation. It is that high-stakes multilingual work demands better implementation choices than many firms have yet made.

That is not a technology problem.

It is a workflow problem.

Sources and Notes

This article draws on public claims and summary figures cited from Clio’s 2026 Canadian legal trends reporting, DeepL’s “Borderless Business: Transforming Translation in the Age of AI” study, and a recent LinkedIn poll of legal professionals about AI’s impact on complex legal review. LinkedIn poll results are directional and anecdotal rather than scientific, but they are useful as an indicator of current professional sentiment.