Benefits of GenAI
GenAI can help increase productivity for translation, review, and quality assurance, allowing organizations to improve machine-translated text and spot more language issues. With GenAI, companies can quickly craft and deliver on-brand, high-quality content across all digital channels, languages, and markets. This allows them to target smaller groups of customers with a more tailored message that resonates better and converts faster. Reaching this higher content volume and velocity allows businesses to capture more of their total addressable market (TAM) and hit their growth goals faster with fewer resources.
For the first time in history, fully automated, multi-variant copy testing has become not only feasible, but also commercially viable — enabling companies to iterate quickly and optimize for performance on the fly. This means that businesses can target and capture their TAM with unprecedented precision. By shifting from an output-focused approach to an outcome-driven one, companies can optimize content for performance at a fraction of the cost and at a higher content velocity.
GenAI also brings businesses the ability to design unique, multilingual digital experiences and buyer journeys to drive their growth. For example, companies can build personalized support or sales agents that work across any number of languages and product lines.
Challenges of GenAI
Today, GenAI is still less effective at translating content than purposefully built machine translation (MT) engines. Besides the lower quality, the costs of running GenAI are still orders of magnitude higher than those of MT. GenAI will not be able to fully automate content generation either — a human still needs to write a prompt, provide all the vital information, and feed the large language model (LLM) with language data to train it.
As organizations create thousands of content deliverables every month, they will have to support shorter content lifecycles. Multi-variant copy testing will further increase the number of content pieces that require building and managing. This content explosion is likely to overload existing marketing, content, and localization teams, budgets, and infrastructure. Modern content management systems lack the capabilities to support this. Even translation management systems are not fully ready and will have to further and more strongly embrace LLMs to ensure the quality of the deliverables.
Additionally, it will not suffice to move all your localization budget to your marketing teams and flood your customers with automatically generated content. Companies that have chosen that path are learning this the hard way. Despite the astonishingly authoritative and very readable content created by GenAI, hitting the brand voice and quality metrics consistently is much harder and requires a focused content strategy and upfront work to set up the AI engines. It also requires alignment and a disciplined approach to content and localization operations.
Finally, GenAI comes with uncertainty and unknown risks. With phenomena like hallucinations, businesses relying on GenAI heavily will have to be on the lookout in order to capture issues early on and minimize any negative impact to the brand. GenAI’s impact on search engine optimization (SEO) is unclear, with Google still determining how automatically generated content should be positioned in search results. Moreover, the lack of a legal framework regulating intellectual property rights and defining plagiarism adds to this already complex environment. The ongoing debate about what constitutes copyright violation is illustrated by The New York Times (NYT)’s lawsuit against OpenAI and Microsoft, which argues that NYT content was used illegally to train OpenAI’s LLMs.