Beyond MT: Navigating the New AI-Driven Localization Landscape
Artificial intelligence has revolutionized the localization industry in recent years. Case in point - machine translation (MT) increases output by 30%. Moreover, AI-powered tools and technologies automate tasks from terminology management to quality assurance to workflow management.
As these innovations increase speed and efficiency, they also transform the role of translators, project managers, and other language professionals. This transformation poses a crucial question for anyone in the industry: how do you navigate this new AI-driven landscape? To help you succeed, we’ve compiled four tips based on industry data and trends.
Five AI Trends in Localization
To plan for the future, we must assess where we stand today. Below are five localization trends and their impact on language professionals.
Demand for machine translation post-editing (MTPE) is growing
The neural machine translation (NMT) quality has improved exponentially in recent years, yet it’s still unable to match human translators' quality and accuracy. This is especially true for low-resource languages such as Swahili, Amharic, and Yoruba.
Translation buyers who want to improve MT output can request MPTE services. This AI-powered human-in-the-loop process relies on human reviewers to correct errors and increase fluency. Today, it works well for internal communications, technical manuals, customer support, and other materials that don’t require a deep understanding of linguistic nuances.
As MT trains on more data sets and languages, it will reach the degree of accuracy necessary for more use cases. When that happens, the translator’s role will shift toward tasks such as:
MTPE
AI output validation
AI prompt engineering
Development of multilingual data sets for AI applications
Human translation will be reserved for marketing campaigns, literature, and other types of creative writing that use metaphors, humor, and euphemisms.
Hyper-localization is enhancing personalized content
Personalization already plays a crucial role in localization. For instance, when a customer visits an online store, the website can detect their location and offer localized content such as language, currency, and product recommendations. Hyper-localization goes one step further to create content based on regional and city-level data, and this allows organizations to:
Send offers and promotions based on local trends
Give geo-targeted customers immediate access to local content
Create content that resonates on a more personal level
Brands with a hyper-localization approach to multilingual content will reach more customers and increase engagement. At the same time, it offers language service providers (LSPs) new opportunities to develop strategies for clients. Language professionals can help them implement hyper-localization by using data to conduct geo-targeted research and provide guidance on hyper-local content initiatives.
AI-powered multimedia localization is improving accessibility
With a compound annual growth rate of 12.1%, Fortune Business Insights predicts the video streaming market will reach $932 billion by 2028. As a result, businesses looking to reach global customers will increasingly need closed-captioning and subtitling services to meet demands for multimedia content. And that’s where AI comes in.
AI helps solve the challenges of scalability and cost. Automatic dubbing and subtitling options enable businesses to quickly localize video content for multiple languages. Like machine translation, adding a human-in-the-loop step to the process improves accuracy. Transcript correction and translation will ensure higher-quality dubs and subtitles for news broadcasts, corporate videos, and user-generated content.
As automatic options increase in popularity, linguists will shift to editing and modifying AI output for low to mid-budget projects. Human dubbing and subtitling will be reserved for high-budget projects like films and TV shows.
Conversational AI is streamlining multilingual customer support
Companies increasingly turn to chatbots and virtual assistants to streamline customer support and reduce costs. The global chatbot market is expected to grow from $5.44 billion in 2022 to $6.92 billion in 2023. And the demand for multilingual chatbots will only rise as businesses expand into global markets.
Localization providers will play a key role in creating frictionless, native-like experiences that resonate with customers worldwide at scale. That could involve:
Building datasets for multilingual chatbots
Training machine translation engines to address conversational AI needs
Customizing interactions using prompts to power chatbot-to-customer dialog
Like hyper-localization, chatbots open up new opportunities for businesses and LSPs to create AI-powered content that connects with customers on a deeper level.
Localization project management is shifting to program management
Regarding day-to-day translation tasks, AI-powered predictions and workflow decisions can already do most of the work. For example, AI-powered workflow management tools can automatically assign tasks to translators, track progress, and send notifications when tasks are completed. As these processes advance, project management roles will shift to program management.
Project managers will spend less time coordinating job assignments, managing project-related tasks, and selecting suitable resources. They will take on strategic and tactical roles to ensure projects meet business goals. They might develop strategies for monitoring and mitigating risks. The ability to analyze data will become an essential part of their job duties.
Four Tips for Navigating the AI-driven Localization Landscape
In addition to the biggest AI trends in localization, let's explore four ways to future-proof your career.
Upskill in strategy, data analysis, and program management
Regardless of your current position, seek out opportunities to enhance your skills in other areas. Upskilling will make you more competitive in the job market and better equipped to take on larger tasks and multifaceted roles. Upskilling in strategy, data analysis, and program management is especially critical as AI takes on more complex tasks.
Localization providers should also offer opportunities to upskill via webinars, eLearning courses, and collaborations with technology partners, which will help employees and freelancers prepare for the ever-changing localization industry.
Stay up-to-date with AI tools and trends
AI is becoming increasingly integrated into translation and localization. You need to know about the latest tools and trends to understand how AI can improve your work. Stay up-to-date by:
Attending conferences and workshops.
Following top AI influencers.
Reading industry news and publications.
Staying up-to-date will alert you to opportunities to experiment with various tools and integrate them into your workflow.
Build relationships with AI vendors
To fully benefit from AI advances, localization providers must focus on building relationships with technology vendors. Doing so will:
Give you access to cutting-edge technology. AI vendors are often at the forefront of new developments and can give partners access to prototypes before they are on the market.
Enable collaborative development of AI-powered tools. You can work with AI vendors to create custom tools to improve speed, efficiency, and accuracy.
Improve workflow integration. AI vendors can help you integrate and streamline AI technologies to improve ease of use.
Create partnership opportunities. AI vendors can refer clients to your organization. You can provide feedback on their tools' usability and effectiveness.
Localization providers with solid vendor relationships will gain a competitive advantage.
Invest in Diversity, Equity, and Inclusion (DEI) initiatives
AI algorithms rely on data, and if the data used to train them is biased, so is the output. For example, an algorithm trained using data within a specific age, culture, gender, or language may show bias in its output, posing a problem when adapting inclusive, culturally sensitive content.
Localization providers should prioritize DEI initiatives to hire employees from diverse backgrounds to combat bias. Employees can train algorithms on multilingual data sets, flag offensive content, and develop strategies to ensure more inclusive language. This training is especially critical for low-resource languages with small data sets for machine translation.
AI and the Future of Localization
AI-driven localization is at the forefront of innovation. However, it still requires human intervention to harness its power. Language professionals will take on new roles as the industry evolves, and the key to future success lies in continuing education in AI best practices.
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