Transformation of Digital Intelligence Enabling Think Tank Service Paradigms,Enabled In-novations and Construction of Collaborative Service Model
[Purpose/significance]The rapid development of technologies such as modern big data and artificial intelligence has had a tremendous impact on hybrid intelligent labor,and is also reshaping the process and mode of think tank service paradigm innovation and value co-creation.[Method/process]From the perspective of transformation and innovation of digital intelligence enabling think tank service paradigm,this paper condenses and elaborates the important transformation and enabling role of think tank service para-digm triggered by big data and artificial intelligence technology,constructs a theoretical model of collaborative service between think tank experts and intelligent support system,and puts forward strategies to promote think tank collaborative service.[Result/conclu-sion]The traditional service paradigm of think tanks has encountered profound challenges in the technological environment of big data and artificial intelligence,which has brought about significant changes in information context,collaborative subjects,resource ele-ments,service processes and other service elements,and has given birth to a new digital service paradigm of think tanks.Based on the new service paradigm of digital intelligence technology,digital intelligence technology enables further innovation in big data behavior insight,group hybrid intelligent labor,collaborative service value co-creation and digital service mode.[Innovation/limitation]This pa-per reviews the transformation of the service paradigm of digital intelligence enabling think tanks,and the enabling innovation pro-moted by the application of digital intelligence fusion technology in think tanks,which provides a theoretical reference for the digital intelligence collaborative service of think tanks;however,the theoretical model of collaborative service of think tank experts and intel-ligent support system constructed in this paper still needs to be gradually improved in practice.
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