State of AI in Localization
It’s 2024. It's been some time since OpenAI crashed the party with the public release of ChatGPT in late 2022. Since then, we went through varied stages of hype, collective anxiety, and rolling up our sleeves to try and find our footing in a world moving too fast and where being fluent in the latest tech is necessary for survival.? ?
No one learned GenAI at localization school. And so, we wondered—is there a blueprint to make it work at an organization? This month, we are highlighting the Beyond the Hype: State of AI in Localization report, which shares insights from those first in line tasked with operationalizing AI in localization, the localization and globalization managers at some of the largest and most innovative companies.??
We distill their real-life experiences into 13 short lessons, which you can read more about in the report. Today, we share a few select excerpts with you. ?
AI in localization today?
The year 2023 can be largely dubbed the experimentation period. For most, experimentation isn’t over yet — the expectation is for companies to continue testing and implementing large language model (LLM) or GenAI-driven solutions well into 2024.?
Lesson #1: Start by considering AI for the low-hanging fruit?
By and large, localization teams have been pragmatic with their AI efforts. Given the pace of development and cost of AI solutions, teams have been primarily looking at parts of the localization process (such as quality processes) that mesh well with AI’s current capabilities and would allow for short- to medium-term AI deployment.?
Lesson #2: With the possibilities and limitations of the current crop of AI tech known, teams are working out a roadmap?
Always keep a firm grasp on your current priorities while you plan for the future. But remember: AI does not require years of practice to get started, nor do you need to wait for the perfect AI solution (it will take a while to get to one). AI can start helping in a matter of weeks or months.?
Lesson #3: AI is a productivity tool?
Productivity and cost optimization are the primary raisons d’être for AI in localization. The drive for more AI comes from within the company, looking for ways to optimize production or existing processes across its varied functions. AI in localization mirrors this logic. Interviewees agree that current AI-powered tools serve a primary objective of minimizing human effort on repetitive or tedious tasks or can be used to create automated solutions for ad hoc tasks. ?
Lesson #4: AI as a tool for expanded language coverage?
As AI solutions become more commonplace, cheaper, and more effective in low-resource languages, using them to expand language coverage might be one of the sources of the oft-mentioned content explosion.?
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Lesson #5: The long-term fit of AI in localization is yet to be fully realized?
One of the more surprising research takeaways is that no one has a definite or confident response to whether they have found a place for AI in the localization process. Yes, companies are at different stages of experimentation, and according to some, the early results of experiments are promising. However, even teams with a very pointed, meticulously thought-out use case they are now implementing are grappling with the same unknowns as everyone else when trying to predict how new tech developments and new tools will continue to impact the way they work.??
AI strategy: how can localization fit?
Lesson #6: Context is everything?
There are different models for how a company crafts a strategy for AI. This depends on the combination of industry, product type, markets the company is present in, etc. Internal organization related to AI is likely partly circumstantial, too — after all, not many have anticipated AI crashing the party so hard. How far localization teams can get with AI today is extremely context-dependent.?
Lesson #7: The great AI inequality?
You may have your work cut out for you with AI. That doesn’t mean you should remain idle — actively seek out and initiate conversations with stakeholders about AI. Go for the low-hanging fruit. Propose initiatives to put it to the test. Don’t ask for permission; ask for forgiveness (and, of course, don’t forget to keep compliance and security in mind, too).??
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Lesson #8: The proactive path may lead to better outcomes?
A strong sentiment shared by several research participants is the need to be proactive with AI. This is a bigger deal-maker or deal-breaker than how a company organizes its AI effort. Most interviewees have initiated conversations about AI unprompted, actively seeking contact with executives and establishing how incorporating AI into localization aligns with larger company growth objectives.?
Lesson #9: Localization can benefit from AI?
There is the idea that localization professionals can validate what AI produces or help set up guardrails and mitigate its risks. They know what works in what language, in what country, and for what type of content.?
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Lesson #10: Unlock the (lifelong) learner in you?
Opinions converge around the idea that today is the time to level up AI skills. There may not be much leaders can do about the context of their companies, but what individuals can influence is becoming fluent with AI: Everything from the lingo, how it works under the hood, what are the use cases now, what to keep an eye out for in the future, what are the current limitations and workarounds, listening to and exchanging information with peers, reading up on research papers, etc. The key is that while tech may evolve, an individual’s knowledge will be transposable, and they will carry it into the future.?
Repositioning localization for the AI future?
Lesson #11: AI doesn’t (yet) fundamentally change the day-to-day reality of localization teams?
On balance, the emergence of AI added yet another thing onto the plate of localization and globalization teams in a world where they arguably already have plenty to do. In the meantime, resources haven’t magically doubled to allow them to tackle this new reality. Yes, teams have been adjusting strategies, upskilling, and rolling out AI initiatives on the go — all with a sense of urgency. The consensus is that it’s better to be proactive to maintain control over the direction of the AI discussion. And yet, the underlying feeling is that tasks such as educating stakeholders, seeking internal alignment — or justifying what the team does and why — were already part of the mission brief before AI arrived on the scene.?
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Lesson #12: Bridge the knowledge gap?
Everyone in the industry is in the same boat, with insufficient personnel, limited bandwidth to experiment, or a lack of foundational AI expertise. AI is a new field for all. Knowing everyone is equal doesn’t necessarily help solve the brief the executives have handed the localization team.?Still, it informs their next steps: educate themselves and their stakeholders.?
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Lesson #13: Make peace with imperfection?
AI right now is imperfect. This may be the root of the collective frustrations and anxieties whenever we talk about AI. The language industry is used to working with definite commodities — a translated word, a quality threshold of XYZ, etc. These define the systems we have built and condition our expectations and those of our clients. We quickly determine a good and bad translation because we have objective ways of assessing it.
The challenge is that systems and ways of working that have been honed to perfection don’t mesh with the idea of imperfection that comes with AI being in a state of flux for the foreseeable future. We must make peace with imperfection and the scary part — that our jobs may no longer look the same a few years from now.?
Including sections on...?
- How AI fits into?localization today: the status quo?
- AI strategy and how can localization fit into it?
- Repositioning localization for the AI future?
Bonus question for the road: Can AI become more than an ancillary part of the localization process??
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By The Alan Turing Institute
It does seem like we have our work cut out for us. There is still a lot to learn about GenAI and how it fits into the enterprise localization ecosystem — but the good news is that you’re not going at it alone. Others are experiencing similar growing pains but are also finding first successes with their AI initiatives. We should bank on more AI — not less — being part of our daily professional lives. Stay with us as we’ll continue covering the topic of AI, bringing you the latest actionable insights you can draw from to keep on top of your game.???