Dominik Schiener, Co-Founder of IOTA: How DLT Will Make Data Privacy a Reality

— Machine-to-machine transactions will become central to an automated economy where devices directly transact value and data with each other without human intervention.

— IOTA uses Directed Acyclic Graph (DAG) technology instead of blockchain to enable feeless micropayments suitable for IoT devices operating offline or on non-internet protocols.

— Data ownership and monetization will shift from corporate extraction to individual/machine control, allowing cars, sensors, and devices to sell their data and receive payment directly.

— Smart decentralization—where edge devices make local decisions and share insights rather than sending raw data to centralized clouds—preserves privacy while enabling collective intelligence.

— Corporate adoption is accelerating through partnerships with automotive (Jaguar Land Rover), microelectronics, and energy companies seeking to build future business models around machine economies.

— Federated machine learning allows devices to analyze data locally and share only insights, not raw personal information, enabling privacy-preserving AI without centralized data gathering.

— Data will become a tradeable asset; individuals and machines holding valuable datasets (health, location, behavior) can monetize them directly without intermediaries, creating new income streams as automation scales.

— Regulatory frameworks around data protection and permissionless innovation will determine whether machine economies remain open (benefiting all participants) or centralize under dominant firms—watch policy development in California and Europe.

— Early adoption likely in supply chain, vehicle telematics, and smart city infrastructure where machine-to-machine payments and data sales are already economically viable within 2–5 years.