At a New Year’s Eve dinner with my family, I saw a familiar situation play out: someone speaking with strong confidence about something they only partly understood. In Spain, we call this el efecto cuñado. What I didn’t realize for a long time is that this behavior has a name in psychology too. It’s the Dunning–Kruger effect, and it shows up just as often in localization and AI conversations as it does at Christmas dinner tables.
This feels like a pivotal moment. Localization teams are being asked to support more markets, move faster, use AI responsibly, and show impact, not just output. Expectations are higher than ever, but many teams are still trained mainly for execution. We are strong at delivering localization work, yet we often struggle to move from output to outcome and to clearly explain the impact of what we do.
AI isn’t just changing tools, it’s changing expectations
Three years into working with AI in localization, I’ve seen the pressure build: automate faster, scale more, do it now.
But the real challenge isn’t the tech itself. It’s the gap between hype and reality , and what happens when teams are expected to act like everything’s already working.
In this post, I break down five common challenges that keep showing up, and what we can actually do about them.
Words have the power to shape perceptions and influence actions, which is why reframing is such a powerful tool. In localization, we can reframe our role from simply translating to driving alignment across the company. By ensuring content is consistent, culturally relevant, and strategically aligned with business goals, localization professionals play a key role in helping businesses grow globally. This post explores how we create that alignment and why our work is much more than just translation.
Choosing between a single-vendor or multi-vendor localization model is not only about price. The real difference shows up in the day-to-day metrics: turnaround time, quality stability, cost control, and how much coordination your teams need to do. In this post, I walk through the core metrics that tend to improve with a single-vendor setup, and how they can help you understand which model fits your localization strategy right now
Even when localization teams aren’t directly affected by a company reorg, everything around them can change fast sponsors move, teams merge, budgets shift.
That’s when weak governance shows its cracks.
This post explores how strong localization governance keeps programs stable, visible, and credible no matter how often the org chart moves.
Over the years, I’ve noticed that localization buyers, like the emotions in Inside Out, are often driven by one dominant need. Some are in survival mode, juggling too much. Others are just getting started and need guidance. Some care about speed, others about cost, and some are laser-focused on how things feel in-market.
Most localization discussions stop at per-word rates. However, what appears inexpensive on paper can often turn into costly delays, rework, and frustrated teams.
Total Cost of Ownership (TCO) provides a more comprehensive view, one that encompasses engineering fixes, QA cycles, support tickets, and brand impact.
When procurement and leadership focus only on price, localization becomes a cost center. When they consider TCO, it becomes a key driver of quality and efficiency. And this post explains how to approach that
Many teams treat localization vendors as interchangeable compare rates, sign the contract, move on. But every switch comes with invisible costs: lost context, quality dips, and team fatigue. In this latest post, I unpack what really happens behind a vendor change ( and how to prepare for it like a continuity project, not a quick fix)
“Welcome to my blog. The space where I document my passion about Localization, Project Management and Leadership”
We’ve all heard the saying that “change is always good,” right? Wrong. We don't like change; we don't like to step out of our comfort, but still, change must happen. I've been studying "Change management and resistance to change" in the last weeks because change is the norm in our #localization industry. In this post, I summarized my learnings so far! I hope you find it useful ☺️
There are many articles about best practices on how to prepare an RFP, but information about how to evaluate them is scarce. This blog post gives a client-side perspective on what areas are important.
Understanding in which areas AI is really powerful, and the ones that a human professional is superior is critical nowadays to maximize our impact and possibilities to stay relevant in the generative content world we are living in nowadays
Consistently posting about our accomplishments on platforms like LinkedIn can quickly become tiresome for others. At the same time, not giving visibility to what we do or achieve can cause our work to go unnoticed, causing us to miss out on certain professional opportunities to advance our careers further.
Several factors affect the duration of localization for a digital product, including translators' availability and the technology setup level. This blog post explores the various elements that impact the amount of time needed for product localization.
I'm passionate about Localization metrics, but it can be frustrating. We live in a data-rich world, allowing us to measure our impact better. However, this data abundance brings challenges when building a Localization metrics system.
In my experience, two main pitfalls emerge (but they are not the only ones 😅). One is overemphasizing Localization ROI, which can lead to unproductive discussions. The other is tracking effort-related KPIs without translating their impact on company success into terms that matter to leadership and product owners.
In this blog post, we explore 3 ideas on how to assess the quality of your localization content with the help of ChatGPT
A major challenge in Localization is defining quality. There's confusion around perceived quality, linguistic/grammatical quality, and clients' tolerance for low-quality translations. Some clients accept minor errors, while others are horrified by poor translations on product labels.
Models like J2450, LISA, and TAUS measure quality but often don't convince product owners or teams to support localization programs. Localization teams focus on quality, while product teams focus on revenue and user engagement.
User feedback can align both teams. Poor feedback can jeopardize a product's future, but explaining how poor linguistic quality impacts long-term growth is challenging. Gathering feedback from international users is crucial for aligning goals.
Analyzing feedback is often overwhelming due to the volume and qualitative nature of the data. Feedback comes from various channels, requiring careful reading and interpretation.
ChatGPT can help by automating and streamlining feedback analysis. It handles large volumes of feedback, interprets qualitative data, filters noise, and bridges language barriers, leading to actionable insights and better decisions.
Ever found yourself juggling the complexities of localization solo?
What happens when the need for expansion knocks on your door? It's time to build your tribe!
This blog post covers the phases of transitioning from a one-person localization department to a functional localization team. From pitching the need for expansion to laying the foundations for continuous improvement,
Chain of Thought (CoT) Prompting is a method in AI models like ChatGPT that breaks down questions into smaller, logically ordered sub-prompts. This step-by-step approach helps the AI generate more accurate and coherent responses, making its reasoning transparent and easier to trust. Among the different CoT techniques, the Zero-Shot Chain of Thought is my favorite.
Every decision a team makes affects not only a digital product's accessibility but also how easily it can be adapted to different markets. Therefore, everyone involved in creating software can help improve both accessibility and localizability. Accessibility is a core consideration in software development and must be integrated into the entire process. The same applies to localization. The best time to consider localization is during the product's ideation phase. The sooner we start thinking about adapting experiences for different markets and making the product usable for as many people as possible, the better. Taking advantage of this week's Accessibility Awareness Day, this post explores how accessibility and localization can join forces to remove barriers.
The power of positive and negative together: The science of mental contrastingThe sweet spot for achieving something is when there is tension between the positive and the negative. And that's a model we can use in this moment where AI is in the spotlight
We move between three approaches when considering how to reach a desired outcome.
1.- INDULGING
2.- DWELLING
3. -ACTIVE CONTRASTING
Localization is all about adapting content from one culture to another, from one market to the next. The tricky part is the thin line separating appropriation and appreciation. The challenge is to adapt content respectfully and give proper credit. It's easy to blur the line between appreciation and appropriation. My post this week reflects on that.
Much is said about AI's threat to professionals in the localization industry. But the truth is that the AI + human combo has a lot of potential. In this blog post, you can learn about the role of an internal Localization team in the AI era.
Creating quality online content adapted to different markets is more important than ever. Our world revolves around content. These days, buying decisions are often based not only on experiences with products, but with information about products. Naturally, with the growing importance of content, a lot of attention is being paid to content strategy. This is a good thing. Companies need to stop throwing content out to the world without a good reason. They need to manage content strategically.
But what about global content? What about all the content that your company produces for people in other parts of the world?
What areas should a localization team consider when collaborating efficiently with a game publisher operating on a GaaS model?
This blog post covers the main elements you cannot ignore when considering implementing a Localization strategy to support developers operating under the GaaS framework.
We all live our particular Groundhog Day; regardless of what we do, some things come back again and again.
Translators and AI: A PartnershipIn this post you can find a list of ideas, areas in which a translator can rely to be more efficient in their day-to-day tasks.
The basic principle of strategic decision-making is based on understanding the impact of our decisions on the future in the decisions we make today.
But, of course, that's more complex than it seems because of cognitive biases. The topic of cognitive biases is fascinating; we all have cognitive biases, and to make matters worse, we don't know we have them. Identifying them is vital since overcoming cognitive biases helps us think more critically and objectively, and we end up making better decisions as a result.
But how can we identify a bias if we don't know we have it? chatGPT to the rescue!"
ChatGPT is a fantastic tool, and in this post, I explain things I have discovered after a year of use
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.