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business ontology

7 articles · Page 1 of 1
Digital Deification
Digital Deification
Oct 18, 2026 · Industry Insights

AI Adoption Gap: Why 88% Pilot But Only 14% Realize Value — Three Pillars to Scale

Accenture and MIT data reveal 88% of Chinese enterprises have moved past AI pilots but only 14% achieve significant value; the gap stems from missing business ontology, data quality, and organizational readiness — not model capability — and success requires evaluating AI against existing business KPIs, not new metrics.

AI adoptionData GovernanceDigital transformation
0 likes · 22 min read
AI Adoption Gap: Why 88% Pilot But Only 14% Realize Value — Three Pillars to Scale
Data Bricklaying Diary
Data Bricklaying Diary
Sep 24, 2026 · Artificial Intelligence

Why Your Knowledge Graph Fails to Explain Business: The Missing Ontology Layer

This article uses an order management example to explain why a knowledge graph alone cannot capture business meaning, defines ontology as explicit computer-processable descriptions of concepts and constraints, distinguishes ontology from knowledge graphs and graph databases, compares OWL and OPM modeling approaches, and provides six validation questions for ontology-driven data governance.

Data GovernanceGraph DatabaseKnowledge Graph
0 likes · 21 min read
Why Your Knowledge Graph Fails to Explain Business: The Missing Ontology Layer
Data Bricklaying Diary
Data Bricklaying Diary
Sep 17, 2026 · Artificial Intelligence

Why Enterprises Need Business Ontologies Despite LLMs' World Knowledge

This article explains why large language models' general world knowledge cannot replace enterprise business ontologies, which provide versioned, traceable semantic models for object identity, institutional definitions, state validity, and responsibility boundaries within a specific organization.

Data GovernanceEnterprise Knowledge ManagementGraph Database
0 likes · 19 min read
Why Enterprises Need Business Ontologies Despite LLMs' World Knowledge
DataFunSummit
DataFunSummit
Jul 30, 2026 · Industry Insights

Why Business Ontology Beats Large AI Models for Real-World Productivity

The article analyzes how industrial AI must first build a unified business ontology—mapping fragmented data about engines, parts, orders, and maintenance into coherent business objects—before large models can reliably turn insights into actionable decisions, using GE's J85 engine program as a concrete case study.

AI-driven operationsEnterprise AIJ85 engine
0 likes · 13 min read
Why Business Ontology Beats Large AI Models for Real-World Productivity
DataFunSummit
DataFunSummit
May 27, 2026 · Artificial Intelligence

How Baidu’s “Sheng Suan” Turns Agents from Outsiders into Business‑Savvy Assistants

The article explains that most AI agents achieve only 80‑90% accuracy in read‑only tasks and cannot handle core production decisions, then details Baidu’s “Sheng Suan” platform which uses a three‑layer business ontology and system‑engineered sandbox, audit, and simulation features to enable agents to execute write operations, citing three real‑world cases where decision latency dropped from months to minutes and accuracy exceeded 95%.

AI AgentsCase StudiesContext Engineering
0 likes · 8 min read
How Baidu’s “Sheng Suan” Turns Agents from Outsiders into Business‑Savvy Assistants