PurposeWith　the　intensification　of　market　competition,　there　is　a　growing　demand　for　weak　signal　identification　and　evolutionary　analysis　for　enterprise　foresight.　For　decades,　many　scholars　have　conducted　relevant　research.　However,　the　existing　research　only　cuts　in　from　a　single　angle　and　lacks　a　systematic　and　comprehensive　overview.　In　this　paper,　the　authors　summarize　the　articles　related　to　weak　signal　recognition　and　evolutionary　analysis,　in　an　attempt　to　make　contributions　to　relevant　research.Design/methodology/approachThe　authors　develop　a　systematic　overview　framework　based　on　the　most　classical　three-dimensional　space　model　of　weak　signals.　Framework　comprehensively　summarizes　the　current　research　insights　and　knowledge　from　three　dimensions　of　research　field,　identification　methods　and　interpretation　methods.FindingsThe　research　results　show　that　it　is　necessary　to　improve　the　automation　level　in　the　process　of　weak　signal　recognition　and　analysis　and　transfer　valuable　human　resources　to　the　decision-making　stage.　In　addition,　it　is　necessary　to　coordinate　multiple　types　of　data　sources,　expand　research　subfields　and　optimize　weak　signal　recognition　and　interpretation　methods,　with　a　view　to　expanding　weak　signal　future　research,　making　theoretical　and　practical　contributions　to　enterprise　foresight,　and　providing　reference　for　the　government　to　establish　weak　signal　technology　monitoring,　evaluation　and　early　warning　mechanisms.Originality/valueThe　authors　develop　a　systematic　overview　framework　based　on　the　most　classical　three-dimensional　space　model　of　weak　signals.　It　comprehensively　summarizes　the　current　research　insights　and　knowledge　from　three　dimensions　of　research　field,　identification　methods　and　interpretation　methods.