Localizability has always been a challenge small issues in source content often lead to big problems later in translation. In this post, I explore how AI is giving localization teams a powerful new way to improve source quality, reduce friction, and create better content for every market right from the start.
What if inclusive localization isn’t just the right thing to do but also the smartest way to break free from outdated pricing models? In this post, I explore the core elements of an inclusive localization strategy and why it might be the key to escaping the trap of price-per-word thinking.
We all talk about the importance of localization metrics, but where do you actually get them? This question hit me hard during a recent panel, and it made me realize something I had been overlooking. If you’ve ever struggled to find the right data to prove localization’s value, this post is for you.
Localization has always evolved alongside technology, yet its core principles remain unchanged accuracy, efficiency, and speed. Each major shift, from translation memories to machine translation, and now AI-driven workflows, has sparked the same question: Has localization become an engineering problem? That’s for you to decide. But if you’re ready to embrace this new phase, there are plenty of skills to develop and resources available to help you stay ahead
Certain words in business settings push all my buttons: 'synergies,' 'strategic meetings,' and 'thought leadership.'
The worst offender? Synergy. Lately, though, another term has been creeping up my list: 'educated.' In localization, we often say, 'We need to educate stakeholders.' But do they really want to be educated? No, they want to understand how localization impacts them.
Instead of teaching, we need to translate localization into business value.
Getting buy-in for localization feels like a big win, until the requests start piling up and it’s impossible to keep up. More teams want your help, more content needs translation, and suddenly, you’re overwhelmed. In this post, I share my experience and the signs that show it’s time to grow your localization team
With tools like LLMs and GPT, we’re at a turning point, and staying curious, planning carefully, and aligning efforts are key. Missing any crucial element could hinder progress. A "slow and steady" approach is essential to navigate the AI wave.
AI is everywhere, and localization teams feel the pressure to "do something with AI." However, without a clear strategy, AI adoption can become an expensive distraction rather than a real value driver. In this post, I explain how to define an AI localization strategy that enhances efficiency, improves quality, and delivers real business impact without just following the hype.
Localization professionals often focus on translation quality and best practices, but decision-makers care about customer impact and revenue. If we frame localization as a cost, it risks being deprioritized. Instead, we must highlight its value driving engagement, trust, and business growth.
Yesterday I was enjoying a delicious cappuccino and a croissant. I was looking out the window and shut up in my thoughts. Mentally I was going over my Christmas break, we had great family moments that I truly enjoyed and I was thinking also about my New Year's resolutions. Between sips of coffee, I read an article that caught my attention, "72% of people will quit their New Year's resolutions just 17 days after they started" This made me think, why?, and I wanted to share with you the steps I do to keep myself focus on my goals. A few years ago I decided to study to get a certification in Project Management (PMP) and it was on my list of purposes for several years, but for different reasons, as the year moves on I was always quitting. The first year that resolution did not last in the list even the 17 days the article mentioned !!
I bought several books, databases of test questions, visiting websites to simulate tests and inter acting in various forums.....But I always felt the same, just overwhelming, so much content!, it looked like something unattainable, too much information.
Fortunately I got a present, a book about the Kaizen method, and that changed my way of dealing with objectives! Kaizen (改善) concept was born in Japan and it is based on continuous improvement, it focuses on small steps in the right order, so you can be closer to your goal. The example of a drop gradually hammering a stone it is fairly representative. Thanks to the Kaizen method, I learned that an important task is to make something every day to take you closer to the goal. Even in the worse cases just doing 5-10 minutes will be better than nothing. So I decided to come up with a plan, and I will be studying one hour (5 days a week) and do simulation tests to obtain a minimum of 85% of correct answers in the tests simulated. This "smart" approach has helped me to achieve the goals that I intend, SMART is an acronym(Specific, Measurable, Achievable, Realistic, Timeline).
I used a mix of Kaizen and SMART to work towards my goal of getting a PMP certification
• I want to get the PMP certification (S) • I will study every day 1 hour (M) • Study every day 1 hour is something I can do (A) • I will get a result of 85% in the simulations (R) • I'm going to do this five days a week (T)
I think many times we set purposes but very generic, we always have the typical purposes of "I have to lose X kilos" "I have to learn a language" etc etc ... these are good intentions, but how we are going to check if we are in the right direction? The problem is that these purposes are very generic. In my own experience SMART has helped me to stay focus by detailing what I have to do
It took me a while to be consistent and build this habit. But eventually I got this habit and everything went well. Good luck with your New Year! and remember the joke...., how do you eat an elephant? one bite at a time! Use the Kaizen method and put SMART goals and you will get what you want, humans are unstoppable when it is clear what you want!
Thanks for reading!, you can follow me @yolocalizo or contact me in my LinkedIn Profile
Before jumping on the AI bandwagon: What localization problem are you trying to solve? AI is everywhere right now, including in localization.
But before jumping on the bandwagon, we need to stop and ask:
Are we solving the right problem?