I was preparing a presentation to share my GenAI experiences with my team and found out this Gartner Hype Cycle concept, describing my adoption process of GenAI quite precisely.
import numpy as npimport matplotlib.pyplot as plt# Create figure and axisplt.figure(figsize=(10, 6))# Define the points for the hype cycle curvex = np.array([0, 1, 2, 4, 6, 8, 10])y = np.array([0.1, 3, 4.5, 1, 3, 3.5, 3.5])# Create smooth curve through pointsx_smooth = np.linspace(0, 10, 100)y_smooth = np.interp(x_smooth, x, y)# Plot the curveplt.plot(x_smooth, y_smooth, linewidth=3, color='blue')# Add labels for each phaselabels = [ (1, 2.5, "Technology\nTrigger"), (2, 4.8, "Peak of Inflated\nExpectations"), (4, 0.5, "Trough of\nDisillusionment"), (6, 2.5, "Slope of\nEnlightenment"), (9, 3.8, "Plateau of\nProductivity")]for x, y, label in labels: plt.annotate(label, (x, y), fontsize=12, ha='center')# Add title and labelsplt.title("The Gartner Hype Cycle for MGA Adoption", fontsize=16)plt.xlabel("Time →", fontsize=12)plt.ylabel("Expectations / Visibility", fontsize=12)# Remove ticks for cleaner lookplt.xticks([])plt.yticks([])# Add gridplt.grid(True, linestyle='--', alpha=0.3)# Save the figure## plt.savefig('mga_hype_cycle.png', dpi=300, bbox_inches='tight')# Display the plotplt.show()
