Reimagining the Content Lifecycle

With Strategic Use of Generative AI

By Kajetan Malinowski


s companies grapple with ever-changing global marketplaces and as consumers become more discerning about digital content, many content marketers are reconsidering their localization strategy as they aim to achieve the next stage of growth. Marketing and business leaders across all industries (including highly regulated ones like finance, life sciences, and law) face a key question: should they continue to create content in one language and then localize it for many markets, or should they leverage generative artificial intelligence (GenAI) to produce customized content for each market in the local language?

The answer is not obvious, especially with AI technology evolving rapidly. While GenAI is certainly impressive — challenging the long-standing paradigms of content services and localization — it comes with significant limitations and hard-to-assess return on investment (ROI). Companies that go all-in on GenAI are often disappointed with the outcomes or struggle to deliver on the promise of a fully automated content lifecycle.

For now, the best approach depends on the particular use case and the value of the transformed content. As GenAI matures, the scope of use cases will grow and the output quality will improve. But one thing is certain: for the foreseeable future, we will see traditional localization coexist with GenAI-created custom content. The main challenge will be finding the right mix of these two approaches in order to hit key performance indicators (KPIs) consistently and at scale.

Pablo Navascués, CEO of content marketing agency Key Content, says, “The true opportunity lies in avoiding binary thinking and in discerning the optimal utilization of workflows for specific use cases. For instance, a global company may want to generate unique digital content, automate millions of product descriptions, enable multilingual customer support, and ensure regulatory compliance. In the past, there might have been just one way of covering all these needs, which meant it was not optimal for most.”

In other words, businesses that can leverage GenAI strategically alongside more traditional localization will be well-positioned for a long-term competitive advantage.


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.


A New Approach

The goal of creating content at scale that resonates with global customers and hits brand voice consistently is making language probably the most important business problem to solve today. A novel approach to localization that uses GenAI strategically is needed for sustained business growth powered by multilingual content.

For marketers and content creators, more effort will go into strategy and research rather than pure execution of the content. For language professionals, the workload will move left in the overall content lifecycle; linguists will spend more time reviewing and curating language assets — such as style guides, glossaries, and translation memories — which are necessary to deliver high-quality content with GenAI. Building language assets is not a one-off, set-it-and-forget-it effort — it is an integral and ongoing part of the process that will need to be built into content lifecycles in order to act on any feedback or fluctuations in the content KPIs. This necessitates going beyond the localization paradigm and supporting businesses during more parts of the content lifecycle.

“GenAI is disruptive in the sense that it will do what should have happened a long time ago,” says Anouk Perquin of Lean Localization, a localization strategy advisory company. “We will move away from word prices, include linguists in the process, and remove the need for a middle man. On top of this, GenAI will make C-level executives understand the value of creating local content, and therefore be more invested in what it takes to make it valuable.”

While the localization industry is painfully conscious of the value of high-quality language data, it has struggled to convey that value to business leaders; the advent of GenAI gives our industry the opportunity to make a stronger business case for higher-quality data, since it has become more closely tied to financial performance. Additionally, translators and localization professionals can add value by guiding businesses on GenAI best practices and helping them forge new approaches to content operations.

Transforming marketing, content, and localization teams will require persistence and a strong sense of purpose. While this will be a significant change-management exercise, it’s worth it; companies that organize their content operations in this way will more effectively reach their customers with more engaging content and better digital experiences. There is nothing more human and personal than language, and yet, paradoxically, GenAI will make us better at it.

Kajetan Malinowski is a Growth Strategy Leader and the owner of, an advisory that provides localization and marketing strategy services and helps companies accelerate growth in global markets.


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