In two words: exciting times. As an industry, we invested heavily over the past few decades to produce ever-increasing amounts of content in more languages. Faster. Cheaper. But the existing language technologies, processes, and to a large extent, our mindsets, have been reaching the limits of what’s possible. AI is changing the game. It’s a massive opportunity. It is a great technology that will allow us to do even more. And even better. And it’s still early days, with a lot more to come. As such, we recognize the necessity of integrating AI into our processes to expand our market reach, enhance efficiency, and maintain high standards of quality.

While AI transforms our workflows, human expertise remains irreplaceable. Our role evolves to more consultative, strategic involvement, guiding clients through technological advancements and ensuring quality control. This human-AI synergy is crucial for maintaining cultural relevance and mitigating the risks of AI.

Our industry must adapt to the rapid pace of AI innovation. This includes developing new service offerings, such as AI-enhanced content generation and advanced quality evaluation tools. It is our mission to educate clients on the effective use of AI, aligning their expectations with realistic outcomes and maintaining the integrity of their brands.

It is also the responsibility of the leaders in our industry to support our supply chain, particularly the linguists who are integral to this process. As AI reshapes workflows and introduces new efficiencies, we must ensure that our linguists are not left behind. This means investing in their continuous education, providing them with the tools and training to work effectively alongside AI, and recognizing the value they bring to our services.

By building a collaborative environment where technology enhances human expertise rather than replaces it, we can navigate this transformation responsibly and ensure sustainable growth for all stakeholders involved.

Reflecting on 2024, it's clear that the localization industry is undergoing a transformation, one driven by the rapid adoption of AI and large language models. These technologies have fundamentally reshaped workflows and content channels, expanded scalability options, and challenged traditional views of quality, efficiency, and creativity.

A major success this year has been the industry's ability to integrate AI and LLM tools into production pipelines without compromising the human expertise that ensures cultural relevance and linguistic nuance. Many organizations have leveraged these tools to manage the exponential growth of content, boost productivity, and reduce time to market.

2024 has also highlighted areas requiring adjustment. We've seen examples where the rush to adopt AI solutions has sometimes outpaced the development of robust quality frameworks and ethical standards. Balancing the efficiency gains of automation with the trust and accuracy demanded by end users is a key aspect of this transformation.

Looking ahead, the localization industry must focus on refining its integration of AI and LLMs, fostering transparency, and investing in upskilling talent. 2024 has proven that while technology can amplify our capabilities, the human element remains irremplaçable in building trust and delivering impactful global experiences.

AI in localization has moved past the hype stage. We’re no longer discussing what could happen; we’re seeing real deployments driving measurable productivity gains in translation automation and post-editing. But let’s be clear: the goal isn’t replacing linguists. It’s augmenting them. By taking repetitive tasks off their plates, AI frees linguists to focus on what protects brand integrity, ensuring the voice, nuance, and cultural alignment that machines alone cannot deliver.

At the same time, the entire language infrastructure is shifting. We’re moving from slow, sequential, segment-based processes to real-time, multimodal, agentic workflows where AI orchestrates each step dynamically. Language is no longer the centerpiece of the process but one component within a broader content supply chain designed to deliver value faster.

This isn’t just a technology shift; it’s a business model shift. Clients care about turnaround times, consistency, value and the cost of managing multilingual content, not about how many words you translated. Operationalizing AI effectively means aligning your workflows with those client outcomes while preserving human expertise where it matters most.