From dream to reality: shaping the future of localization with AI Globally Speaking
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- Management
“Companies are nowadays expected to seamlessly cater to client preferences and deliver relevant and personalized content on demand. Real-time and just-in-time localization is a key component of this hyper-personalized approach to communication”.
Listen to Loïc Dufresne de Virel, 25-year industry veteran and head of localization at Intel, who couldn’t be more enthusiastic about recent AI developments and their impact on customer experience.
Loïc explains, however, that the key to effectively capitalizing on this major transformation lies not only in the choice of AI but in the ability to integrate it into existing processes at multiple levels. Assigning a specific natural language processing task to an AI worker is relatively easy. The real challenge lies in the compatibility with other technologies, the ability to deploy AI capabilities at scale, and the requirement to support complex content formats - in parallel with the development of more flexible workflows based on AI-generated outcomes.
Knowing how to strike the right balance between AI-enabled automation and the human touch, each complementing and augmenting the other, is undoubtedly the key to turning content localization into a significant driver of incremental revenue.
“Companies are nowadays expected to seamlessly cater to client preferences and deliver relevant and personalized content on demand. Real-time and just-in-time localization is a key component of this hyper-personalized approach to communication”.
Listen to Loïc Dufresne de Virel, 25-year industry veteran and head of localization at Intel, who couldn’t be more enthusiastic about recent AI developments and their impact on customer experience.
Loïc explains, however, that the key to effectively capitalizing on this major transformation lies not only in the choice of AI but in the ability to integrate it into existing processes at multiple levels. Assigning a specific natural language processing task to an AI worker is relatively easy. The real challenge lies in the compatibility with other technologies, the ability to deploy AI capabilities at scale, and the requirement to support complex content formats - in parallel with the development of more flexible workflows based on AI-generated outcomes.
Knowing how to strike the right balance between AI-enabled automation and the human touch, each complementing and augmenting the other, is undoubtedly the key to turning content localization into a significant driver of incremental revenue.