中科闻歌CEO罗引：AI 走向企业核心，绕不开“决策”

Core Insights - The rapid evolution of generative AI over the past two years has profoundly impacted the global technology industry [2] - The industry is forming a new consensus that the value of AI is shifting from content generation to higher-value enterprise decision-making [3] - By 2027, Gartner predicts that 50% of business decisions will be assisted or automated by decision intelligence AI agents [3] Group 1: Decision Intelligence - The key challenge for enterprises is how to integrate AI into core decision-making processes [4] - Zhongke Wenge, founded by the Chinese Academy of Sciences, is focusing on decision intelligence rather than general large model development [5] - The CEO of Zhongke Wenge emphasizes that the core of enterprise AI lies in systematic reasoning and judgment capabilities, rather than just model parameter size [5][7] Group 2: AI's Role in Decision-Making - Current generative AI primarily operates at the "System 1" level, providing quick answers based on probabilities but often lacking logical coherence [5] - For AI to participate in critical decision-making, it must be safe, controllable, and truly understand industry logic [10] - Zhongke Wenge has developed its own large model, "Yayi," to address these needs while ensuring a clear methodology [10] Group 3: DOMA Framework - The DOMA (Data–Ontology–Models–Agents) framework has been proposed to systematically address how enterprises can use AI for decision-making [12] - The four layers of the DOMA framework include: - Data layer: Captures the current operational state through multi-source data governance [12] - Ontology layer: Structures decision logic by formalizing industry rules and causal relationships [12] - Models layer: Conducts reasoning within defined rules and logical boundaries [12] - Agents layer: Facilitates the execution of decisions through multi-agent collaboration [12] Group 4: Long-Term Strategy - Decision intelligence is a "heavy engineering" task that requires long-term industry engagement and iterative refinement of business logic [15] - Zhongke Wenge's decision intelligence systems have been successfully implemented in complex scenarios across finance, energy, media, and government [15] - The true value of AI lies in becoming an integral part of the organizational decision-making system, helping organizations form stable, explainable, and reviewable judgments in uncertain environments [15]