Figure 1
The horizontal axis is labeled “Data” and ranges from 1 to 19 in increments of 2 units. The vertical axis is labeled “Number” and ranges from 30.00 to 100.00 in increments of 10.00 units. The graph contains three solid colored lines and two dotted lines. A legend in the top right identifies the red line as “Observed values”, the blue line as “Model fit”, the upper dotted purple line as “Upper bound confidence interval”, the lower dotted purple line as “Lower bound confidence interval”, and the dark blue line as “Predicted values”. The “Observed values” line starts near (1, 44), gradually rises with fluctuations through points near (5, 55), (7, 58), (10, 67), and peaks near (11, 68), then declines slightly around (13, 64), and ends near (15, 71). The “Model fit” line follows a similar upward trend, starting near (2, 45), fluctuating through points near (5, 49), (7, 58), (10, 65), and ending near (15, 71). The “Upper bound confidence interval” line begins near (2, 53), rises gradually with fluctuations, reaching near (15, 77), and extends upward in the forecast region toward (20, 96). The “Lower bound confidence interval” line begins near (2, 39), and it fluctuates throughout the observed region, showing several rises and declines before ending near (15, 64). In the forecast region, it extends almost flat toward (20, 66).” A vertical black line at data point 16 separates the observed data from the forecast region labeled “Y-Model underscore 1”, shown vertically on the right side of the graph. The dark blue “Predicted values” line begins near (16, 73.5) and rises steadily through the forecast region, ending near (19.89, 81). Note: All numerical data values are approximated.Time series plot of exponential smoothing method for AI satisfaction forecast. Data point 1 represents the year 2009, and data point 19 represents the year 2026. Source: Authors’ own elaboration