Event Title
Visualizing the Evolution of the AI Ecosystem
Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
4-1-2021 12:00 AM
End Date
9-1-2021 12:00 AM
Description
This study examines the evolution of the complex, emerging artificial intelligence (AI) ecosystem. Grounded in multiple theories, we introduce a conceptual framework that maps emerging ecosystem dynamics in terms of firm funding and exits. Using a curated dataset of nearly 10,000 ventures and 31,000+ funding/exit activities, we visualize the trajectory of 15 core technology segments of the AI ecosystem as connected scatterplots and compute several salient path measures for each, including path length, velocity, number of loops, and L-shapes. Our visual analysis reveals several path patterns across the four quadrants of our framework and highlights the evolutionary growth and consolidation across segments. We discuss our findings in terms of initial conditions (market size, funding, technology hype), platformication, and geographic concentration. Our study contributes to our data-driven understanding of ecosystem dynamics.
Visualizing the Evolution of the AI Ecosystem
Online
This study examines the evolution of the complex, emerging artificial intelligence (AI) ecosystem. Grounded in multiple theories, we introduce a conceptual framework that maps emerging ecosystem dynamics in terms of firm funding and exits. Using a curated dataset of nearly 10,000 ventures and 31,000+ funding/exit activities, we visualize the trajectory of 15 core technology segments of the AI ecosystem as connected scatterplots and compute several salient path measures for each, including path length, velocity, number of loops, and L-shapes. Our visual analysis reveals several path patterns across the four quadrants of our framework and highlights the evolutionary growth and consolidation across segments. We discuss our findings in terms of initial conditions (market size, funding, technology hype), platformication, and geographic concentration. Our study contributes to our data-driven understanding of ecosystem dynamics.
https://aisel.aisnet.org/hicss-54/os/managing_ecosystems/10