The technology sector needs no introduction to AI. The market for machine learning is growing by the day, driven by some of the world’s brightest minds and most innovative companies. It’s obvious that an AI project backed by custom data is a potentially invaluable business asset.

However, even as it transforms the world, the tech industry is also being affected by its creations. Outside of the development of their core product, a variety of AI applications are changing the way these companies operate. Whether through virtual assistants that simplify online payment processes or search relevance algorithms that ensure the best products are given the limelight, AI’s strengths in analyzing big data can be brought to bear on a vast number of use cases. It’s worth considering the diverse range of ways you can use AI to improve not just your product, but your entire business – and how different types of data can help you to achieve that goal.

Machine learning applications for the technology industry


If there’s one thing machine learning is good at, it’s improving efficiency. From the highest to the lowest levels of business operations, this specialism is being put to use in a variety of unexpected ways. In tech support, for example, virtual assistants and chatbots are helping to handle calls so that only previously unanswered questions are rerouted to support staff. With the ability to integrate and learn from third party applications, it’s well worth considering some of the endless ways that these algorithms can improve ROI.

Personalized service

The rapid development of virtual assistants and chatbots has revolutionized consumer expectations. Personalized experience has become the norm, usually achieved through algorithms that ask and answer the customer’s questions, as well as providing recommendations based on customer data. However, the challenge to completely satisfy this demand remains, with new developments exploring the possibility of personalized newsfeeds and automated emails generated by AI. Approached correctly, algorithms that ensure exemplary customer service could provide your business with a significant market advantage.

Accurate predictions

There are a plethora of ways to use AI’s strengths in analyzing data outside of strengthening your core product. Significant progress has been made in sentiment analysis, turning oceans of unwieldy customer data into a force that can accurately predict the market’s reaction or lift your customer engagement to the next level. AI assistants are also improving software development, analyzing the impact of changes on the user, the developer and the market. In every facet of your business, AI provides an opportunity to build better and grow faster.

Why Lionbridge?

You don’t need to tell us twice that data quality is critical. We understand that to build a game-changing algorithm, you need datasets that are up to the task. In fact, at Lionbridge we’re obsessed with ensuring your gold standard through richly annotated data. As fellow tech fanatics, we’re been improving our system for the last decade to ensure that your data will scale across 300 languages. Whether you need a hundred annotations for sentiment analysis or a million data points for chatbot training, we’re committed to providing you with the custom data that will push your algorithm forward.

How We Can Help

Data annotation

We’re itching to fulfil your desire for detailed and thorough annotations across a variety of use cases and global languages. LEARN MORE


With 500,000 certified language specialists in our crowd, Lionbridge is the obvious choice when it comes to native-level datasets for chatbot training. LEARN MORE

Sentiment analysis

Whatever your use case, we’ll work with you to ensure that your algorithm can identify the precise blend of emotions you’re looking for in 300 languages. LEARN MORE