GIS Industry Predictions 2024 – Korem

By Jonathan Houde , CTO, Korem

Jonathan Houde

Navigating Geospatial Trends, Cloud, Data, and AI Innovations

As we delve into the intricate landscape of geospatial technology in 2024, it’s essential to reflect on the dynamic shifts that unfolded throughout 2023. Many of Korem’s 2023 predictions have come to fruition, while others are still unfolding, shaping the trajectory of the industry. This article will focus on 5 key trends on the evolution of geospatial within the enterprise ecosystem.

Data Privacy and Mobility Data, Still in Evolving Canvas

In the realm of data privacy, the landscape remains in constant evolution. New federal and provincial regulations are still emerging, in the US, Canada, and various other countries. This has contributed to maintaining volatility in the mobility-derived data market landscape. As a result, many vendors have started to shift from offering raw mobility trace data, to anonymized and pre-aggregated data. For customers, using these types of pre-aggregated mobility data allows transferring both the complexity of dealing with mobility data quality, the challenge of dealing with privacy compliance, and ultimately a faster time to value.

While the market hasn’t yet reached expected potential, as a data advisor, we are starting to see a surge in demand for both vehicular and phone mobility-derived data. This can be explained by businesses turning to data-driven decisions to navigate their disrupted or competitive markets. These companies increasingly rely on external insights and data contextualization to fuel their analytics and AI processes.

Cloud Data Warehouse as the New Geospatial Data Repository

In 2023, Snowflake has stated that over 70% of its 8500+ customers leverage Snowflake’s geospatial storage or processing capabilities. This is a clear indication of the growing significance of cloud data warehousing in housing geospatial data. The rapid evolution of Snowflake’s geospatial capabilities has been supported by a combination of built-in geospatial capabilities and extension from geospatial vendors like Carto, Precisely, and Mapbox. Even advanced features such as raster processing that used to require GIS platforms are now becoming possible in platforms such as Snowflake. All of these combined with an increasingly rich data enrichment ecosystem are key to positioning cloud data warehousing as the nucleus of analytics and AI/ML.

Expanding Horizons for Geo AI

2023 was dominated by Gen AI, Large Language Models (LLM), with not only the widespread launch of OpenAI’s Chat GPT, but other similar technologies in both commercial and open-source landscapes. These technologies have also brought applications on the geospatial ecosystem, ranging from conversational GIS, code generation, advanced feature labeling, automated documentation, to automated data analysis.

GeoAI capabilities have also expanded. For instance, advanced spatial modeling is now easier to perform at scale in cloud data warehouse. Even if image recognition and feature extraction have been around for a while, it is finally becoming more accessible for more large-scale use cases in various industries. This due to a combination of several factors including more affordable imagery data, the ability to consume imagery through content-as-a-service, and the evolution of feature extraction models that now integrates into variety of software.

There’s a growing consensus that companies cannot have an AI strategy without a thorough data strategy. It is also commonly recognized that any data strategies should include a geospatial component. Therefore, it is not surprising that geocoding, geo-enrichment, and geospatial relationships, are often critical to achieve AI/ML modeling accuracy.

Increasing Synergy Between Open Source and Commercial

Instead of opposing commercial and open-source technology, the combination of these two in the geospatial ecosystem is now becoming more prevalent.

Similarly, in a context where more open and government data sources are becoming available, the creation of the Overture Maps foundation, demonstrates how commercial and open-source data can mutually benefit.

For companies, broader data availability from commercial, governmental and open sources will translate into the ability to address more business use cases. However, keeping up with the rapidly evolving data landscape and associated terms of use will become increasingly challenging.

Redefining Geospatial in the Era of AI and Cloud

Today’s CEOs are facing many challenges, including labor shortages, high turnover, high inflation or increasingly competitive markets, which induce pressure on their operational efficiency. Combined with external changes and disruptions related to climate, demographics and customer habits, taking the right decisions without a data-driven support is becoming increasingly difficult.

For most companies, AI and cloud technologies are top of mind as primary tools to help deal with these challenges, while geospatial is often overlooked.

In 2024, we expect decision makers to become increasingly aware that geospatial is a key dimension of AI or cloud, and often necessary to get expected value from their cloud and AI investments.

In retrospect, 2023 marked an exciting year of innovation in the geospatial landscape, laying the groundwork for a promising 2024. As we navigate through the evolution of mobility data, cloud data warehousing, GeoAI, the geospatial industry’s transformation and redefinition will be key to the expansion into new industries use cases and technology landscape. Learn more at korem.com.

About the author

Jonathan Houde CTO at Korem Jonathan is responsible for technical leadership and innovation, further developing the company’s technical community, and aligning its software strategy, architecture and partner relationships to solve business challenges and deliver the best customer value. With his extensive experience across many different technologies, Jonathan and his team are able to build technology solutions for complex projects across different industries. He is known for his ability to quickly identify customer requirements and translate them into recommendations and realizations that can range from simple “out of the box” technologies and data integration to very advanced custom developed solutions.

Category: Industry Predictions

This entry was posted on Friday, January 12th, 2024 at 2:43 pm. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.