AI时代生成式搜索对情报检索范式的影响与对策OACHSSCD

[Purpose/Significance]The rapid development of generative AI technology poses fundamental challenges to traditional competitive intelligence retrieval paradigms.This study aims to explore the impact mechanisms of generative search technology on competitive intelligence retrieval paradigms.[Method/Process]Using a combination of theoretical analysis and case study methods,with Perplexity Deep Research as a typical case,this study analyzed the impact mecha-nisms of generative search from three dimensions:information discovery mechanisms,cognitive processing processes,and workflow patterns.[Result/Conclusion]Generative search achieves a paradigm shift from"information discovery"to"knowledge generation":the information discovery mechanism shifts from keyword matching to semantic understanding and reasoning generation;the cognitive processing process shifts from manual analysis to human-machine collaborative intelli-gent analysis;the workflow shifts from linear to iterative dynamic adjustment.Generative search technology reconstructs the theoretical foundation and practical methods of information retrieval,driving the transformation of intelligence analysts from information processing experts to problem design experts.A new working paradigm centered on human-machine colla-boration should be established.