Content Automation & AI: Creative Production Insights from the Localisation Industry

Many of the fears and challenges of navigating automation in the creative production industry mirror what the translation industry experienced over a decade ago, as Google Translate and other machine translation solutions began to generate interest. In the time since, automation and generative AI such as ChatGPT have proved exciting developments that continue to unlock possibilities for improved customer engagement with brands on a global scale.   

Language services providers (those offering translation and linguistic services) are experiencing the same transformative market dynamics as creative production: international scaling online, reducing barriers to customer acquisition, and an increasingly complex media landscape, often with distinct local market nuances. Integrating automation into language services has required us to be open to new ideas. Language services and content production also share another common nuance: much of the demand is not from originating copy/content, but in iterating
master campaigns to be tailored to local market needs.

With many developed markets facing recession, brands need solutions that open higher growth markets and can deliver on their content needs without high incremental costs. Brands that rely on purely manual processes cannot achieve global omnipresence and consistency in their marketing communications without significant budget increases. To achieve the same success across brand creativity, we suggest four approaches: 

Recognize the human role in automation.

Human post-editing or “Human-in-the-loop machine translation” is now a service that all language service providers working at scale are offering to some extent. The human role of quality-assuring and post-editing content translated by the machine is a different process with different skills required to being a translator. While some individuals are already highly skilled and motivated by this type of work, the supply is still catching up with demand. The talent needed to deliver great campaign assets will shift from pure production roles to more Q.A. and editing roles. Creative production leaders need to anticipate this change and, where there is a skill shortage, take steps to train and build the team. Training freelancers is also great for building loyalty and stronger team bonds as you work together (read more on how to make machine translation work for you).

Use automation to drive creative freedom.

Selective and smart use of technology within production services frees people up to work on value-adding activities that deserve extra attention, excite people, and result in better work. Likewise, as brands seek increasingly integrated marketing solutions, process design will be key to success. Integrating the gig economy with in-house teams, agency teams, and AI is an exciting and strategic task, arguably a better use of production experts’ time than many of the simple, repetitive tasks that automation covers. Creative teams can focus their energy on truly engaging and insight-led campaigns that respond to consumer needs. The world of scaled content production is complex, so another use for this free time is to keep on top of emerging technology and understand how best to use it in different contexts to deliver desired outcomes.

Use performance data to determine if, when, and how automation is needed.

Brands need help making sense of the extensive and quickly evolving automation landscape, with time-cost-quality trade-off assessments that make deciding when and how to use tools across various media, markets, and languages easy. An agency’s job as experts in their field is to advise where it makes sense to automate vs. where the human process is key – while planning for the shades of grey in between. This decision should be informed by performance data, as much of the exponential asset increases come from digital media. Bringing this objective insight into production decisions frees up time for brand owners to focus on how they take their products and services to market and what is core to their business.

Refine and communicate quality standards.

A worldwide pool of flexible, often freelance talent supplies the language services and creative production industries. The content supply chain, be that translators, editors, animators, etc., are already using automation tools to create efficiencies and take on more work. This is a natural response to the growing gig economy driving more significant pressure on individuals’ rates. The onus is on agencies and brands to ensure that their definition of “quality” is up-to-date for the new AI-enabled era, and that robust corrective actions are in place for errors rather than trying to rule out automation.

Creative automation is heating up as brands head into 2023. While the collision of creativity and AI might be scary for some, learning from industries that have gone around the automation curve and found value in its integration can help brands prepare appropriately for future
transformations. 

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Lindsay Hong is Chief Operating Officer at Locaria. Locaria blends insight, data, talent and technology to take global content further for leading brands