How Companies Are Holding Back Their Own Global Growth

Global enterprises are scaling into more markets than ever. Demand for locally adapted content keeps rising. But translations and approvals continue to get stuck in inboxes, spreadsheets and endless review loops.

Two new industry reports reveal a striking truth: in 2026, the bottleneck isn’t the technology, it’s the workflow.

Almost every large organisation report skyrocketing content needs, and more than half added new languages in just the past year.  

Yet the promised economies of scale rarely materialize. Why? Because localization workflows remain fragmented, slow and largely unmanaged. 

The language barrier is gone

Most organisations now use AI somewhere in their translation process. But for 60%*, the benefits stop at faster drafts and quicker turnaround, final delivery still slows to a crawl due to long email chains, reviews and manual steps between systems.

Real transformation happens when AI is orchestrated across the entire chain, from content creation to localisation, approval and publishing.

The most advanced teams report 6.5× faster* localization and global content flows than those still operating in traditional workflows.

The pressure is intensifying. More languages. More content formats. More channels. Higher expectations for cultural relevance. And across all markets, stricter compliance demands. 

Why so many are still stuck at the starting line 

Three barriers show up again and again: 

1. Fragmented systems: A full 67%** of companies say their content and translation processes are only partially integrated. They rely on separate tools that don’t communicate. Every product update or regulatory change must then be handled manually, repeated across every language and every format. Only12%** report a fully connected, automated workflow.

2. Governance and compliance friction: 38%** say that security, legal and compliance teams regularly delay AI adoption. Without clear rules, predictable review steps and traceability, organisations get trapped in prolonged approval cycles. AI stays stuck in pilot mode instead of scaling into daily operations. 

3. The competence gap: AI hesitancy today stems more from lack of understanding than from lack of capability. 58%** lack structured, relevant AI knowledge for localization and beyond. When expertise sits with only a handful of people, progress becomes patchy, and impossible to scale. 

AI’s Breakthrough: From Tool to Engine

According to DeepL**, 70% of translations are now machine-assisted. Yet 35% of companies still run localisation manually, and 33% rely on traditional TMS setups requiring heavy post-editing.

In other words: many companies “have AI somewhere nearby,” but not at the heart of the processes.

When AI instead acts as a conductor, following rules for terminology, tone and compliance built into structured control layers, human post-editing drops dramatically. In some cases, translation and publishing times shrink by 98%, from weeks to minutes. 

A Game-Changer for Growth?

The highest-performing teams have a few things in common: Integrated language technology and unified platforms (1.6× more likely to achieve top ROI), automation at the workflow level, not just in isolated steps.  

This is where AI stops being a tool and becomes a growth engine: more markets, faster launches, higher conversion, consistent quality, without increasing headcount. 

The checklist that reveals whether you’re stuck in manual work

• Does translation still take days or weeks? Then you’re stuck in a project mindset, not an automated workflow. 
• Is content waiting in queues at your agency, reviewer or local market? That’s a process and integration issue, not a language issue.
• Do you see inconsistent terminology or tone across markets? Your AI guardrails and central governance layers are missing.
• Does legal/compliance repeatedly pull the handbrake? Then you need standardized approval steps, otherwise you will never scale. 

If you answered “yes” to several of these, your model is, not scalable in 2026.

This is no longer an optimisation issue; it is an operational transformation. 

AI Can Deliver the Quality - The Question Is Whether You Dare Let It 

The companies seeing the strongest results consolidate tools, connect their systems and clearly define which terms, tone and rules should apply. Then they let AI enforce those rules automatically.

AI issues updates, performs the initial translation, quality-assures output and, where the content type allows, publishes the correct version immediately.

For workflows requiring human input, intelligent flagging ensures that subject-matter experts only step in at clearly defined checkpoints.

No more chasing files. No more hunting down the latest version. Let the human experts be architects, conductors, controllers and value creators, not administrators trapped in outdated manual processes.

Companies that make the shift now will launch faster in more markets, with lower risk and a more consistent customer experience. Those who wait will soon find that competitors have already made the new way of working the standard.

Källor:

*Smartcat. The State of Global Enterprise Growth in 2026. Smartcat, 2026.

**DeepL. Borderless Business: Transforming Translation in the Age of AI. DeepL, 2026.