DETROIT – Southeast Michigan’s Connected and Automated Vehicles network is burgeoning, with 351 organizations identified, including automotive, software, legal, construction, government and manufacturing.

The report also found nearly 1,400 relationships already developed between these organizations, a significant sign that a healthy, collaborative climate is being fostered in the region – a dynamic vital to long-term leadership in the region and state, according to Connected and Automated Vehicles Social Network Analysis.

The Analysis, which identifies key organizations that provide critical thinking or serve as a point of intersection across important initiatives in Michigan’s CAV sector, was developed by the Workforce Intelligence Network for Southeast Michigan (WIN), on behalf of the Advance Michigan Defense Collaborative (AMDC).  

The report provides data and analysis of core influencers, highly connected organizations that serve as gateways to collaboration, and stakeholders that can help integrate other organizations shown as disconnected from the vast CAV network.

The top five most influential organizations in Southeast Michigan’s connected and automated vehicles ecosystem are: 

1. General Motors

2. Ford Motor Company

3. University of Michigan

4. American Center for Mobility 

5. Michigan Economic Development Corporation

“Identifying key players within the CAV space not only allows us to see who is already working together, but also who should be working together to leverage Southeast Michigan as a competitive mobility leader,” said Lisa Katz, executive director, WIN. “As regulations are still being determined within the sector, we are seeing more involvement from insurance companies and law firms. As such, “connectors” are taking many forms as the CAV network continues to organically expand.” 

The full Connected and Automated Vehicle Social Network Analysis as well as social network maps showing the top organizations in various capacities in the region can be viewed at:

For more research and data from WIN, or a custom analysis, please visit: