AI data solutions aren’t from the future anymore; they’re what your business needs to succeed now. Companies across all verticals are using AI data collection and AI annotation for a variety of functions, including:

• Data collection and annotation for AI and Large Language Model (LLM) training.

• Data cleaning and preprocessing to ensure high-quality input and analytics for AI models

• Predictive analytics to use historical training data for predicting future trends in the market and customer behavioral patterns.

• Natural language processing to perform sentiment analysis, translation, train chatbots, and summarize text.

• Computer recognition to aid in object and facial detection, as well as image classification in security, healthcare, or retail.

• Recommendation systems that eCommerce and streaming services over to users and customers seeking their next product, movie, music, book, etc.

• Fraud detection systems that use data to identify possible fraudulent activity.

• Customer insights via analyzing customer data to implement targeted marketing and personalize customer journeys.

• Automating routine tasks and workflows — without human error.

• Healthcare tasks, including diagnostics, personalizing medicine, and managing patient records.

• Supply chain optimization to help forecast demand, streamline logistics, and optimize inventory.

Achieving this requires a high-performing AI model, which begins with high-quality labeled data. Here are five reasons your competitors are using (and benefitting from) AI data collection services.

Reason 1: Data Collection Services Help You Scale with External Data

Many companies rely solely on internally procured datasets to train their AI models. These data sets may include:

• Customer behavior
• Locations
• Buying patterns
• Other materials hand-picked by internal employees
• Etc.

To procure data internally, companies often create synthetic data, scrape the Internet for publicly available data, or fail to adequately clean and curate internally procured data. Unfortunately, this often isn’t enough to help an AI model perform accurately, sensitively, and eliminate bias from its output. AI models require data that encompass a diverse range of people, perspectives, languages, topics, and locations. Without a vast set of training data, some of which must be external, AI models risk generating insensitive, intolerant, inaccurate, or harmful output.

AI data collection services can help organizations procure and manage the massive amounts of data they need to train their AI systems properly. To support our data services, Lionbridge’s Aurora AI Studio platform utilizes AI to provide sentiment analysis and AI summaries of the data captured from our global community of half a million experienced linguists, testers, and reviewers.

It also provides visibility into rich, on-demand analytics. With so many participants, we can collect and annotate the huge amounts of data that our customers need — quickly and within budget.

Reason 2: Faster LLM /AI Training

With the right data collection services, companies can rapidly scale their data curation and labeling. These quick timelines can help companies train their AI models at record paces, allowing them to start serving and connecting with customers worldwide faster. Lionbridge uses our innovative AI technology to automate and expedite repetitive data tasks. We can also use it to analyze data sets and share insights for stronger marketing strategy, operational strategy, and more.

Reason 3: Crowdsourced Data Collection Builds a Strong, Diverse Foundation

Your AI model is much more likely to perform well if it’s trained on a strong foundation of data. This means high-quality, diverse data sets that reflect the real-world, lived experiences of your target audience. Curating and AI data labeling for this kind of varied data can be a complex process that requires AI expertise and extensive labor from individuals with global perspectives. Lionbridge’s team uses our extensive, diverse, and international crowd of participants via Aurora AI Studio. This platform lets us access a deep network of global and diverse participants who provide human-in-the-loop annotation solutions that have helped many of our customers build robust data sets for training their AI models. We’ve also offered custom dataset creation to help train AI models over time because, like humans, AI systems need to continue learning about cultural touchstones as they evolve.

Reason 4: Data Collection Services Fill Data Gaps for Special Use Cases

Brands may not be able to access or procure data sets for every language, location, or topic that matters to their customer base. Finding this data might require special skills or the ability to speak specific languages or dialects. Companies like Lionbridge have the international, expert resources and crowd members to assist with these challenges. We assist customers with the data collection and annotation they need for complex or niche areas. These services are crucial in helping our customers utilize their AI models to reach new markets via reliable, sensitive, and accurate content.

For example, companies in the legal and healthcare spaces need annotation for domain-specific data and documents. Lionbridge offers experts who can assist with these highly technical and regulated tasks so data is accurate, clean, and reliable.

Reason 5: Data Collection Services Help Achieve Compliance

Obtaining the right training data for an AI model isn’t just about its performance. It’s also about maintaining compliance now and in the future. AI regulations are still a work in progress, but responsible AI is already a crucial topic across all verticals. Additionally, there are existing laws that cover the usage and procurement of data, including these laws and regulations.

AI data collection services can help companies ensure their data usage supports responsible AI initiatives and complies with the aforementioned regulations (and potential future regulations and laws). They can also help with data documentation, which may be needed for compliance or potential audits. Lastly, data collection services can offer advanced security measures, helping to protect data from cyberattacks and leaks, and meeting industry standards and regulations.

Get in touch

Ready to discover how AI data collection services can help your team get the most out of its AI system? Your AI model is likely one of the most significant investments your company is making right now, so let’s see how we can help optimize output and ensure current and future compliance with responsible AI usage. Let’s get in touch.