▌ Introduction

Earlier this summer, Meta made a $14.3 billion bet on a company most people had never heard of: Scale AI. This investment sent Meta’s competitors scrambling to exit their contracts with Scale AI, fearing it might give Meta insight into how they train and fine-tune their AI models.

▌ What is Data Labeling?

Data labeling is the process by which experts manually evaluate and classify data used to train AI models. In the era of large language models (LLMs) like ChatGPT, this process has become crucial for improving the quality and accuracy of models.

▌ Why Did Meta Invest Billions?

Meta’s investment in Scale AI is linked to the growing interest in agentic AI—models capable of performing complex multistep tasks that require interaction with various tools and systems. Agentic AI requires high-quality data for training, and this is where data labeling comes into play.

▌ The Role of Synthetic Data

Synthetic data is data artificially created using other AI models. It is used to train new models, speeding up the process and reducing dependence on human labor. However, as Sajjad Abdoli from Perle notes, synthetic data cannot always replace human expertise, especially in complex fields like medicine.

▌ The Future of Data Labeling

Meta’s investment in Scale AI highlights the importance of data labeling for the future of AI. Companies specializing in this process will play a key role in the development of agentic AI and other advanced technologies. The question of how best to combine human labor and synthetic data remains open, but one thing is certain: the future of AI depends on the quality of the data it is trained on.

The Future: Who Trains Whom?

By 2026, 40% of data labeling will be AI-performed (Gartner), but:

✅ Full automation is impossible - we'll need "human anchors"

✅ A new market will emerge: AI-labeler auditing

✅ Hybrid professions will appear (AI assistant trainers)

The Irony of Our Era: We're creating intelligence meant to free us from routine, while first forcing thousands of humans to nurture its «childhood».