Unlocking AI Value: Data Quality, Privacy, and Blockchain in the Smart Era

Industry Data Value and AI

Data is the essential foundation for artificial‑intelligence development and scenario application, and it has become a key element in comprehensive digital‑intelligent transformation. At the 2023 World AI Conference in Shanghai, beyond large‑model discussions, “industrial data value‑creation” was a hot topic.

Data serves as the raw material for AI machine learning and large‑model training, while privacy protection and efficient circulation are seen as critical steps toward data value‑creation. As the UN Industrial Development Organization’s Deputy Director‑General Zou Ciyong noted, protecting data privacy is necessary to build trust in AI technology.

Market Forecasts

Recent forecasts show that China’s big‑data market IT investment reached about USD 170 billion in 2022 and is expected to grow to USD 364.9 billion by 2026, effectively doubling in size. Within the five‑year horizon, China’s share of the global market is projected to rise, potentially surpassing the combined Asia‑Pacific (excluding China and Japan) market by 2024 and approaching 8 % of the global total by 2026.

Why Data Quality Matters

In the current era led by large models, data quality largely determines the breadth of model applications and performance, especially for vertical large‑model training. Acquiring and governing industrial data and knowledge is a crucial foundation, making high‑quality dataset construction and governance especially important.

Case Studies

Smart‑car sector : Zhiji Auto’s co‑CTO Liu Tao explained that a vehicle generates massive data daily; the company’s data throughput exceeds 14 million kilometers per day. By deploying efficient edge‑side filters, only data beneficial for iterating autonomous‑driving algorithms is uploaded to the cloud‑based data factory.

Fintech example : Ant Group Digital Technology’s Vice President Yu Hu described a data‑quality and value‑assessment technology that can evaluate data quality both online and offline through model performance feedback. Ant also collaborates with universities to develop blockchain‑based large‑scale distributed data trustworthy‑governance technology, ensuring data security and trust throughout the process.

Automated laboratory : JingTai Technology co‑founder Ma Jian introduced an autonomous laboratory that uses high‑efficiency parallel robots to generate large‑scale, high‑quality real‑world data, accelerating drug‑candidate prediction and creating a closed loop between intelligent algorithms and robotic experiments.

Strengthening Data Privacy and Standards

Digital resources are vital production factors, yet data‑leak incidents are frequent. The complexity, breadth, dispersion, and diversity of data amplify challenges such as asset discovery, classification, access control, compliance analysis, and AI predictive analytics.

Yu Hu emphasized that the core issue of data circulation is the lack of security and trust guarantees. Without a trusted collaboration mechanism among data owners, holders, developers, and operators, public data sharing and flow are hindered. He proposed that blockchain and privacy‑computing can form a trusted infrastructure to promote industrial data flow.

Blockchain enables authorized use, traceability, and protection of data, while privacy‑computing allows verification of data utility without exposing its content. The fusion of these technologies can accelerate data circulation and unlock data value.

Ant Group’s FAIR Platform

Ant Group’s FAIR (Privacy Collaboration Platform) deeply integrates privacy‑computing and blockchain. Smart contracts drive the collaboration workflow, a privacy‑computing engine handles data flow, and blockchain ensures rights registration and consensus. The platform has been applied in the Hangzhou International Digital Trading Center, Sichuan Port Investment Group, and the National Industrial Information Security Development Research Center.

In December of the previous year, the Hangzhou International Digital Trading Center was inaugurated. By December 2022, it had partnered with 215 enterprises, listed 428 products, completed 457 data‑business transactions, and achieved a cumulative transaction amount exceeding CNY 1.3 billion, all supported by Ant’s data‑element circulation technology.

Industry Outlook

IDC’s “Privacy Computing Panorama 2022” report predicts that over the next 5‑10 years, technologies like blockchain will become indispensable for the data‑element market. The “blockchain+” solution has become an industry consensus and is viewed as the standard for data‑element circulation.

Traditional enterprises are also standardizing data production. Shanghai Steel Union, with 23 years in commodity data services and IOSCO certification, has built a massive professional data collection system and launched three product series—Commodity Prices, Commodity Industry Big Data, and Commodity Data Application Services—on the Shanghai Digital Exchange.

Chairman Zhu Junhong stated that to improve data circulation efficiency, Shanghai Steel Union has established a complete set of standards covering data collection, inspection, and governance, enabling standardized flow of commodity data.