Eight Emerging Technology Trends for 2019 Identified by JD Technology Management Center

Technology 1: Autonomous Objects – By applying artificial‑intelligence techniques, objects gain limited intelligence to perform tasks; they are currently semi‑automatic or conditionally automatic and are expected to evolve toward networked, collaborative clusters.

Technology 2: Augmented Analytics – Combines AI with data analysis to produce intelligent data, enabling users without statistical or algorithmic expertise to conduct advanced analysis, discover problems, and identify business opportunities; future enhancements will automate data preparation, cleaning, management, and modern analytics.

*Data analysis development stages

Future augmented analytics will become the primary analysis method, reducing data‑processing time and increasing efficiency across data preparation, cleaning, management, modern analytics, BPM, process mining, and data‑science platforms.

*Key features of augmented analytics

Technology 3: AI‑Driven Development – Divided into two directions: embedding AI into software to provide vision, speech, language, and conversational capabilities, and using AI to automatically generate code, enabling non‑experts to create solutions without manual programming.

Embedding AI: visual analysis, video analysis, facial recognition; speech‑text conversion and speaker identification; text analysis, translation, content moderation; natural‑language processing, Q&A, chatbots.

AI‑generated development: automated development environments that let users build applications without writing code.

Technology 4: Digital Twin – Creates virtual replicas of physical entities by integrating models, metadata, scenes, temporal data, and analytics; enables observation, analysis, control, and optimization of assets such as data‑center servers, improving efficiency and reducing manual inspection costs.

Technology 5: Autonomous Edge – Enhances edge computing devices with AI chips and stronger processing, storage, and functions, creating a complementary relationship with cloud computing; 5G advances reduce latency and increase bandwidth, supporting the growth of autonomous edge workloads.

*Structure of autonomous edge

Technology 6: Immersive Experience – Encompasses AR/VR technologies and human‑machine interaction; AR overlays information on the real world, while VR provides fully virtual environments, primarily used in gaming today; future interaction will expand to voice, gestures, eye‑tracking, and positional tracking.

Technology 7: Blockchain – Offers broad application potential but still faces challenges such as lack of industry standards, absence of dominant vendors, and limited transaction throughput (e.g., Bitcoin ~1.6 tps).

*Blockchain types, trends, and characteristics

Technology 8: Smart Space – Refers to physical or digital environments enriched with connectivity, intelligence, and autonomy (e.g., smart cities, factories, parks); integrates devices, IT management, and business applications to provide information dissemination, decision support, collaboration, and transaction capabilities.

*Evolution stages and characteristics of smart spaces

(Note: Source information is from the internet)