The presentation will focus on the coalescence of technology that is enabling geospatial AI use cases to take place across the enterprise. It will feature a playbook for pivoting away from the legacy GIS operating model (teams and technology) into a modern AI + Cloud model.

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For modern labor organizing, spatial data is a critical multiplier. At Working America, its true power lies in its ability to driving cultural transformation by dismantling the gatekeeper model of data analytics. By building an ecosystem that equips staff to answer strategic questions directly, we have shifted the paradigm of data access. This talk maps our journey, exploring how we are navigating engineering hurdles, governance, and user adoption while charting our next frontier in spatial analytics.

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Traditional economic forecasting at the city level can mask significant variation in economic outcomes across areas within the same city. Oxford Economics has developed a novel hyperlocal forecasting framework for the US, which disaggregates cities into uniform hexagonal grids and models economic activity using a quantitative spatial model. Using case studies from New York, Los Angeles, and elsewhere, we demonstrate how hyperlocal forecasts reveal within-city divergences that are invisible at the city level. These insights support more targeted decision-making for investment, site selection, and policy at the scale where those decisions are actually made.

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For years, spatial analysts and field operations battled rigid queries, manual updates, and high-maintenance custom applications. It’s time for a shift. In this session, we will explore how combining CARTO with AI Agents completely modernizes this legacy workflow. Discover how we transformed static analytics into dynamic, conversational spatial applications. We will dive into how CARTO can speed up time to delivery, explain how CARTO’s AI agents orchestrate and automate spatial analysis, and share the major leaps that can be achieved in operational efficiency.

Climate events are occurring daily across the globe, and without significant emissions reductions, their intensity and frequency are expected to grow. ICE Climate provides insights into the material impact and financial losses from current events, alongside tools designed to project future climate related risk. These models are built on high resolution, geospatial data and analysis. This presentation shares real-world examples using data and visualization to explore how climate risk is unfolding today and how it can be assessed into the future.

A good audience-movement visualization looks effortless — a smooth glide across the city. Underneath, it’s a high volume of data with unique challenges: signal sparsity, trajectory inference, snapping points to road networks, and reconciling voluminous but rarely cooperative device data. This session looks beneath the waterline at how we turn noisy pings into OOH decisions stakeholders trust, and how to visualize calm waters while the underlying data is far more sophisticated.

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