So I've been working in translations for a few years now and here are the issues I've seen and why, honestly, AI taking over is actually for the best:
It's extremely insular: The industry is weighed down by rigid traditions. Many veterans who have followed "traditional" routes refuse to embrace new problem-solving methods or track emerging trends.
When you try to apply a statistical or data-driven take on linguistic issues, it’s often met with hostility.
Outdated infrastructure: "Industry standard" tools are clunky and archaic. Compared to the agility of modern AI-driven platforms, traditional CAT (Computer Assisted Translation) tools feel like a relic of the past.
Technical defeatism: There is a weirdly pervasive view that nothing can be done about recurring technical glitches, like track changes errors. Instead of fixing the workflow, teams just accept the friction as inevitable.
Quality is an afterthought: Delivery teams frequently prioritize logistics and speed when building new solutions, only considering quality assurance as a final, rushed step rather than a core requirement.
Toxic "Diva Energy": There is a high level of ego in the field that can become incredibly toxic. This elitism often gets in the way of practical collaboration and progress.
Flawed error logic: Some translators view one major error in 60,000 words as a bigger failure than a minor error in a few hundred words. It’s the weirdest logic I’ve ever heard, ignoring the statistical reality of scale and human margin of error.
Dismissiveness toward clients: There is often a "not my problem" attitude toward the end-user, especially regarding preferential changes. Dismissing a client’s specific stylistic choices as "wrong" rather than a brand requirement is a bizarre and unhelpful attitude.