(by Logos Group)

Are you tired of the AI hype yet? We are too. Fortunately, the conversation is finally maturing — shifting from the “will AI save us or doom us” narrative to a more practical one: what role should AI actually play in business?

Business leaders everywhere are feeling the pressure. They’re expected to apply AI to cut costs, boost efficiency, and deliver more — all with fewer resources.

At Logos Group, we don’t claim to have the perfect formula. But after decades of experience helping global brands like Stellantis, SACMI, and Electrolux manage complex multilingual ecosystems, we’ve learned a few things about where AI truly adds value — and where it doesn’t.

What Separates Great Content from AI Output

Generative AI is often presented as a stand-alone solution. In reality, once you look closer, the illusion fades quickly.

AI can generate text, yes — and research (like the recent Microsoft studies) shows it’s already quite capable. But stringing words together is only half the job.

The other half is context, domain knowledge, and intent. That’s where human intelligence still matters — supported by structured data, domain-specific training, and a continuous feedback loop.

Without the right input, the output remains hollow. Polished, perhaps — but wrong.

AI Is Scaling. Human Validators Can’t Keep Up. Something Has to Give.

At a recent Logos Group client roundtable, we discussed how to move from “AI as a buzzword” to “AI as a trusted business partner.”

The consensus was clear: quality remains non-negotiable. Humans must stay part of the process — not just as one-time reviewers, but as continuous validators ensuring that AI-generated content aligns with brand voice, terminology, and intent.

At the same time, clients are rapidly integrating AI to accelerate workflows and lower costs. The result? The classic three-way tension between quality, speed, and cost.

• If quality didn’t matter, companies would machine translate everything.
• If cost and speed didn’t matter, humans could do it all.

Meanwhile, content volumes keep growing, but budgets do not. The bottleneck sits squarely at the human review stage. Machine translation accelerates throughput — but reviewers are overloaded. AI must help them, not replace them.

Guiding Human Effort Where It Matters Most

Even Logos Group faces the same balancing act as our clients. When localising our own websites and AI-solution pages, we focus human validation only where it has measurable business impact.

High-visibility assets — such as websites, campaigns, or training materials — require full creative translation and review.
Other content types — like internal updates or routine documentation — may rely on hybrid workflows with AI-driven quality estimation (AIQE) and AI-assisted post-editing (AIPE).

The key insight? Quality is not a fixed target.
Chasing “maximum quality” for every text dilutes resources. Teams end up polishing internal memos instead of focusing on customer-facing materials that actually move the needle.

The smarter question is: What’s the right level of quality for each content type — within time and budget — so human expertise is applied where it truly matters?

That’s exactly how Logos Group’s AI-powered multilingual content ecosystem (myLogosys) is designed: to dynamically adapt quality levels per project, optimizing human involvement through predictive AIQE scoring.

Customers Want More Automation — Without Losing Control

Determining the right quality level is only the first step. Our customers increasingly look to automation to alleviate the human review bottleneck.

As one automotive client put it:

“Our reviewers are overloaded. We need automation to reduce their workload and accelerate go-live — without sacrificing quality.”

That’s where AI-driven Quality Assurance comes in.

Using AIQE and AIPE, Logos Group’s systems automatically evaluate and improve translations before a human even opens them:

• AI Quality Estimation (AIQE): predicts the quality of each segment, highlighting only those that require review.
• AI-assisted Post-Editing (AIPE): proposes fluent, stylistically improved alternatives — ready for final validation.

These features don’t replace linguistic expertise; they amplify it. The result is a leaner, smarter process — humans focus where their judgment adds real value.

AI’s Real Place in Localisation — and Beyond

So, where does this leave us?

AI is not a replacement for human intelligence — it’s a multiplier. Used deliberately, it streamlines workflows, enhances scalability, and frees experts to do what they do best: ensure that every piece of content carries the right message, tone, and impact.

For large-scale, low-risk content, full automation may be the right choice.
For regulated or brand-critical materials, a hybrid workflow — combining machine translation, AI-driven QA, and expert review — offers the best balance of efficiency and accuracy.

The real opportunity lies in making conscious choices about quality levels, automation, and human oversight.
Companies that master this balance not only reduce costs but also strengthen their global communication — with content that’s faster, smarter, and consistently on brand.

At Logos Group, this is exactly our mission:
to help organizations orchestrate their multilingual content with the right blend of AI automation, human expertise, and structured intelligence — from authoring to translation to delivery.