By Jacob Clemente

Senior reporter, AI & work

Last week, we wrote about the various ways organizations are using generative AI in their everyday work. While some of those examples came from individual experimentation, others came from larger-scale projects driven by teams and departments.

How should you select which projects to prioritize? Cisco serves as an interesting case study.

Earlier this year, I heard Francine Katsoudas, EVP and chief people, policy, and purpose officer at the tech company, mention a hackathon within her organization during a virtual panel at Davos. The approach struck me as a good way to get employee buy-in and crowdsource ideas for AI projects. We recently spoke with Katsoudas to learn more about that hackathon, and the AI use cases that resulted from it. Here are highlights from that conversation, edited for length and clarity:

Can you talk about the AI hackathon you recently held in Cisco’s People, Policy, and Purpose organization?

We started off with a little bit of education, so our teams could get deeper in understanding [the technology]. From there, we had our teams ideate. [The hackathon preparation] started back in November. We captured all of these ideas—at one point there were 248—and then we kept engaging people to look at some of the top projects that we could potentially execute, [given] what we have. We involved some of the solutions teams that were most closely connected to the suggestions. Then we opened it up and had people vote on what was most interesting, and had a hackathon based on the top six ideas over a few months. The team is really proud of the ideas that came forward. The six tech proposals are all at different points of being either assessed or executed against.