The future of AI isn’t just about bigger models or faster chips—it’s about better data. The Data for AI 2025 report, independently conducted and commissioned by Bright Data, digs into insights from 500 senior decision-makers whose organizations leverage public web data to train, fine-tune, and power their AI systems. The report offers a comprehensive look at the role of web data strategies across startups, SMBs, and enterprises .
Here are some of the most compelling insights from the report—and what they mean for the future of AI.
Web Data Is a Core AI Asset
One of the most striking findings is that 65% of organizations use public web data as their primary source for AI training. This marks a significant shift from traditional, static datasets to dynamic, real-time data streams that are continuously updated and customized.
Public web data is no longer just a supplement—it’s the foundation. It supports the entire AI lifecycle, from pre-training and fine-tuning to inference and real-time decision-making. This is especially important for applications like generative AI, AI agents, and real-time analytics, where context and freshness of data are critical.
Startups Are Leading the Charge in Innovation
Startups, known for their agility and innovation, are making bold moves in the AI space, and web data is a key part of their strategy.
- 69% of startups use public web data as a main source for collecting real-time, connected data
- 52% are already seeing positive ROI from web data infrastruct
Startups’ focus on speed and flexibility creates a necessity for a scalable, reliable data infrastructure. A trusted data partner can streamline collection and ensure compliance.
Enterprises Are Scaling with Precision
While startups move fast, enterprises scale big and focus on quality and compliance.
- 69% of enterprises rely on public web data for real-time AI
- 54% report positive financial impact from web scraping
Enterprises use web data to improve AI model accuracy, relevance, and real-time decision-making. At scale, challenges like regulatory compliance and data integration become more complex.
Real-Time Data Is Powering AI Agents
A major trend highlighted in the report is the rise of real-time data usage during inference. 96% of organizations collect real-time web data for inference, enabling AI agents to interact with the web, ground their responses, and reason more effectively.
Use cases like search, navigation, and information extraction require up-to-date, context-rich data. Bright Data’s unblockable infrastructure is designed to support these needs at scale, ensuring that AI agents can operate with the most current and relevant information.
Data Quality Is the New Competitive Edge
As AI adoption matures, organizations realize that data quality, not just quantity, is the key to performance. 71% of respondents say data quality will be the top competitive differentiator in AI over the next two years. High-quality, diverse, and well-labeled data leads to better predictions, fewer errors, and more trustworthy AI systems.
The Data Economy Is Booming
The report also reveals that the demand for public web data is growing rapidly.
- 38% of companies already consume over 1 petabyte of public web data annually
- Data needs are expected to grow by 33% in the next year
- Budgets for data acquisition are projected to increase by 85%
This surge reflects the rising importance of data in AI strategies and the need for scalable, cost-effective solutions to meet that demand.
Overcoming Challenges with the Right Partner
Despite the enthusiasm, 98% of organizations face challenges scaling data acquisition. From regulatory hurdles to integration, the road to high-quality AI data isn’t always smooth.
That’s where data partners come in to execute on speed of data collection, cost efficiency, and completeness of data.
The “Data for AI 2025” report makes one thing clear: AI success depends on data success. Download the full report to explore all the insights and see how your organization can stay ahead in the AI race.
