The foundation of effective globalization cannot be robust and remain sustainable without artificial intelligence (AI) and smart data powerhouses in the digital age. At the same time, the role both drivers will play in the long run has triggered vibrant debates and opposing views among global product and content leaders, specifically regarding if and how they will replace human resources at scale. These opinions have also been reflected in articles describing how digital may dehumanize work and workers. These subjective, yet interesting views are turning AI from a given revolution factor into a challenging evolution path to deliver global products, services, and content across local markets. More than ever true cost and time effectiveness is the name of the game and humanization has a card to play in this game in the interest of both globalizing organizations and local customers.
From a digital globalization perspective, in-depth localization remains the fastest and safest track to engage and delight individuals where they are geographically and when they are most likely to become customers. As such it provides them with the level of linguistic, cultural, and functional convenience they expect, regardless of where they stand in their customer journey. Localization teams actually create a singular opportunity to add and increase value for global businesses and leaders by stewarding local and personal experiences in the framework of AI-driven processes. Personalization cannot go without humanization efforts that should make a difference in terms of human resources and technology enablement.
First human resources that are involved in global content workflows and product lifecycles will not disappear with the broadening scope of AI. They will change and move. They will be recycled or transform themselves. They will have to learn, re-learn, and unlearn to be in-sync with the ever evolving nature of international customer journeys and product leadership. AI will relieve them from the most repetitive, iterative, and low-level tasks through intelligent automation. It will enable them to change practices, save time, and focus on what truly creates value for local customers.
Conversational commerce, unassisted support, online recruitment, self-training modules, or social community moderation require content that has to be emotionally relevant and engaging. By looking at some chatbots and e-commerce platforms it is easy to feel the importance of such content and see how functional performance cannot cut it without linguistic and cultural authenticity. Human resources involved in localization efforts will also be able to lift themselves up to become intelligence ambassadors in their respective areas of expertise. For example, linguists will become more than “traditional” translators as they will be able to upgrade their knowledge of local brand voices, user-generated content nuances, and hyperlocal variances. In addition to linguistic intelligence, they will have more opportunities to develop cultural intelligence and contribute to functional intelligence. They will significantly boost local content by getting closer to the values, emotions, and functionality that resonate with local customers. Linguists will be able to extend their area of influence, expertise, and performance within their organization or for their client. The same personal and professional development should be available to product designers, developers, producers, testers, marketers, and trainers who should also keep in mind that their audiences are human beings.
From a company-centric standpoint, technology enables human resources and business processes to deliver value more simultaneously and quickly in content lifecycles. From a customer-centric standpoint, it creates the functional engagement that customers need to look for information, make a decision, and proceed to purchase. When multiple markets are at stake, technology has to face the challenge of being as agile and powerful as the diversity of local customers requires. Human beings are in the driver seat and cannot be ignored to avoid internal disruption as well as external disappointment. In other words, technology has to remain human-centered in every possible way.
From an organizational perspective it means that it must be implemented and usable to perform as much as possible with as little as possible. AI is a major driver of cost and time effectiveness and it should be considered as an invaluable assistant to those who are empowered by technology. Considering the increased complexity of addressing a variety of markets and customers content and product localization has been enhanced and accelerated with technology for quite a long time and AI is now the extra layer of efficiency. Yet it creates the most value when it is focused on some tasks, some types of content, and, as a result, a combination of a human and automated approach. Neural machine translation is one of the most obvious examples of this as it speeds up the overall translation process while keeping a sequence of human editing or review that may vary according to the type of content. This case of AI humanization in localization processes could be replicated in other areas of content and product management as it highlights where AI can take over at some workflow stages when it makes sense and still let human beings chime in when they create value.
From a customer-centric angle, localization forces AI humanization as linguistic effectiveness is rather subjective and cultural effectiveness is very personal. While AI allows content leaders to understand customers more quickly and leverage best practices more consistently it cannot talk holistically to customers who react with human intelligence implying individual sensitivity, empathy, and authenticity. Technology facilitates local and personal reach but does not replace it currently. For instance, it is fine to better identify and target local customer touchpoints with machine learning, but it is also necessary to let local customers interact with people who are not robots, specifically if they need to have a detailed conversation. Chatbots have proven to be perceived and received as useful in some international markets to deal with standardized or simple interactions. However, they have not quite met customer expectations to discuss tricky issues or to have a discussion on more subjective matters.
Ultimately, localization elevates AI humanization and vice versa by following the rule that AI is as good/human as human beings who create and maintain it. This is another reason to consider localization as a business booster and a profit driver rather than just a cost center, at least as long as local customers are human too.