01341nas a2200229   4500008004100000022001400041245004200055210004100097260004200138300000900180490000700189520069700196653002300893653001600916653001900932653003400951653003300985653001301018653002401031100002601055856003001081       2020                        eng d  a1927-032100aAI-Driven Digital Platform Innovation0 aAIDriven Digital Platform Innovation  aOttawabTalent First Networkc10/2020  a4-150 v103 aArtificial Intelligence (AI) innovation becomes useful today when it enriches decision-making that is enhanced by applications of big data (BD), advanced analytics (AA), and some element of human interaction using digital platforms. This research aims to investigate the potential combination of AI, BD and AA for digital business platforms. In doing so, it develops a multi-dimensional AI-driven platform innovation framework with AI/BD/AA innovation value chain and related levels of AI maturity improvement. The framework can be used with a focus on the data-driven human-machine relationship and the application of AI at different levels of an AI-driven digital platform technology stack.10aAdvanced Analytics10aAI maturity10aAI value chain10aAI-driven platform innovation10aArtificial Intelligence (AI)10abig data10aenterprise platform1 aYablonsky, Sergey, A.  utimreview.ca/article/139201711nas a2200229   4500008004100000022001400041245006800055210006700123260004200190300001000232490000600242520103400248653002301282653001601305653001901321653003301340653001301373653002401386653001501410100002601425856003001451       2019                        eng d  a1927-032100aMultidimensional Data-Driven Artificial Intelligence Innovation0 aMultidimensional DataDriven Artificial Intelligence Innovation  aOttawabTalent First Networkc12/2019  a16-280 v93 aThis is a critical time for the development and adoption of Artificial Intelligence (AI). The field has existed since the 1950s and is only now emerging as viable for commercial markets. Many enterprises are placing bets on AI that will determine their future. Today AI innovation becomes useful when it enriches decision-making that is enhanced by applying Big Data (BD) and Advanced Analytics (AA), with some element of human interaction using digital platforms. This research investigates an opportunity for cross-fertilization between AI, BD, and AA with related disciplines. The paper aims to investigate the potential relationship of AI, BD, and AA with digital business platforms. In doing so, it develops a multidimensional BD-driven AI innovation taxonomy framework with an AA/BD/AA innovation value chain, related levels of BD, and analytics maturity improvement. This framework can be used with a focus on data-driven human-machine relationships, and applying AI at different levels of data driven automation maturity.10aAdvanced Analytics10aAI maturity10aAI value chain10aArtificial Intelligence (AI)10abig data10aenterprise platform10ainnovation1 aYablonsky, Sergey, A.  utimreview.ca/article/1288