How Data Became the Most Indispensable Resource for AI | Or Lenchner, Bright Data | RAISE 2026

Operational Scaling & Infrastructure:

• Bright Data re-architected its entire technology stack twice in the last 12 months to support the unexpected scale of data demand driven by the AI industry.
• The company is transitioning its data infrastructure from primarily textual formats to massive visual data requirements necessitated by physical AI and robotics.
• Bright Data is launching human-in-the-loop platforms to generate niche, ad-hoc visual data that does not exist on the open web (e.g., specific phone models, unique manual tasks).

Physical AI & Robotics Trends:

• Industry demand for visual data has "exploded" over the past year due to the emergence of humanoid robots and industrial automation requiring robots to "see and understand" the physical world.
• Data collection is evolving from egocentric views (robot's perspective) to capturing third-party interactions (e.g., two humans conversing, robot-to-robot interaction).
• Industrial robotics adoption is accelerating faster than consumer applications due to well-defined use cases and lower barriers regarding public trust and safety.
• Consumer humanoids in private homes are predicted to be limited to simple tasks initially, with widespread trust and capability expected to take several years to mature.
• Early adopters, particularly in China, may see humanoids in homes within the next 12 months, whereas Western adoption will likely be slower.

Legal Strategy & Litigation:

• Bright Data successfully won all major legal conflicts initiated against it (including cases involving Meta and X).
• The company views litigation as a strategic business instrument essential to securing the data rights necessary for the global AI ecosystem.
• Success in these legal battles prevents the potential collapse of the web data infrastructure upon which modern AI training and search capabilities rely.

Geopolitical Market Dynamics:

• Chinese AI companies are primarily focused on building their own data infrastructure stacks and sourcing data through novel methods, such as large-scale citizen filming initiatives (e.g., GoPro straps).
• Western AI companies are predominantly outsourcing non-core functions like data sourcing to focus exclusively on model development and application logic.
• Bright Data observes Chinese customers utilizing "bare metal" products to build internal capabilities, contrasting with Western customers who prefer outsourced data solutions.

Financial Performance & Corporate Structure:

• Bright Data ended the previous year with a revenue run rate of $300 million and achieved growth significantly faster than the mid-year projection of $400 million.
• The company remains private with plans for an IPO "not on the horizon," prioritizing hyper-growth and high profit margins without external capital injection.
• Bright Data has never raised external funding, maintaining profitability since its founding 11 years ago.

Market Outlook & Valuations:

• While acknowledging that some AI valuations are exaggerated, the speaker asserts the long-term value of AI is real and that a total retreat from AI technology is impossible.
• The speaker predicts potential stock market corrections regarding high valuations, warning that inflated startup valuations may ultimately be detrimental to employee upside.
• The consensus view is that despite market volatility, the industry will continue building infrastructure and products regardless of short-term financial corrections.