Geospatial AI in the Public Sector: A Conversation with Dilip Krishna (Deloitte)

How is Geospatial AI solving real-world challenges in the public sector? In this conversation, Dilip Krishna from Deloitte discusses the latest trends in the analytics ecosystem, from real-time streaming data to the growth of infrastructure. Discover how the partnership between Deloitte and CARTO is leveraging AI to deliver real solutions for complex use cases like permitting, public safety, and more. Learn more about CARTO: https://carto.com/ #geospatialai #publicsector #dataanalytics #Deloitte #CARTO Transcript 00:02 What trends have you seen in the analytics ecosystem for the public sector? What we are seeing generally is with the enhancement of computer technology, cloud, and other technologies, analytics is becoming more and more powerful. It's becoming more real-time. There's a lot more streaming analytics, and people are able to get information a lot faster with huge amounts of data as well. And that's leading to many more possibilities in terms of use cases and use of data, use of analytics to do things for the public good that we are just scratching the surface on. 00:40 How is AI impacting geospatial solutions for the public sector? AI is one of the most exciting things that is happening at this point. The confluence of the ability of AI to derive fantastic insights very rapidly but now do it in a geospatial manner, is where there's a huge amount of opportunity. Also, the ability for AI to then be distributed into very specific areas, specific use cases, and individuals can affect the ability for governments, for example, for people to do very specific, beneficial things to the populations that they serve. 01:27 What geospatial use-cases are you most excited about? One of the key trends in our time is the growth of infrastructure, whether it be building infrastructure that's going to get built out significantly in manufacturing, or it is electrical infrastructure or other kinds of energy infrastructure, and all this requires something to do with land and location. And so those are the big types, big use cases that I'm excited about. One example is permitting, which depends on which parcels of land, who owns those parcels of land, and how do we negotiate through that. So using geospatial, a lot of that can be sped up increasingly through this process. 02:19: How does Deloitte work with federal, state, and local municipalities? In the example of permitting, there are permits that go across from federal, state, and in many cases, they overlap. So it's very important for companies or individuals to know what their permitting regime is. So being able to understand which permits apply to what in terms of land and location becomes very important. So that's an example of what we do with federal and local. But there are many others. And I would add that in addition to federal and local, there's also the commercial side of the equation, where you get a lot of situations. For example, companies that are putting up data centers are commercial entities, but they also need to be part of the same process. Companies that are implementing nuclear reactors, for example. So there's a lot of different use cases where many of these actors come together and need to work in concert. 03:22 How are CARTO and Deloitte working together to help public sector customers? We value our relationship with our partners like CARTO, companies that are innovative and move fast and generate new technology. Deloitte's benefit and the value proposition that we bring to our clients is we are very good at integrating and delivering solutions and delivering results. We work very collaboratively with companies like CARTO to deliver these sorts of outcomes. For example, understanding flood plain characteristics in certain areas or understanding how to limit pedestrian injuries on busy city roads are good examples of what we do together. 04:20 Can you share an example of a solution CARTO & Deloitte have worked on together and the strenghts of each partner? One example I might go back to is the pedestrian injuries example, where we integrated the solution, but the solution crucially depended on partners like Kado and other partners that came together in one solution to deliver, using GenAI, the ability for business users to quickly query, understand patterns at any given point in the day, and be able to also recommend solutions given the information that we've provided to the business user. And to be able to do this over and over again in a very rapid fashion.