I froze for a minute; watching with bated breath, as the scenes from the TV showed a second plane hit one of the New York twin towers. The screams, plumes of thick smoke and images of people plunging to their deaths was just too devastating for me (a fourteen year old at that time) to bear. I was overwhelmed with grief after having just witnessed in real time; albeit remotely; a catastrophe that would change the course of events forever.
My brief moment of shock was cut short abruptly when my friend yelled my name from a distance summoning me to come play football. Suddenly, I was back to my familiar version of reality.
Unsurprisingly, about two decades later; my “familiar reality” has been greatly altered. It is one that includes Computer Automation, Machine Learning, Big Data, “Killer Robots” and all the technobabble associated with Artificial Intelligence (AI). Irrespective of the merits of AI; the possibility of a re-occurrence of that unfortunate event in these present times is terrifying.
Although AI applications are undoubtedly diverse, it is usually portrayed through the narrow lenses of core Information Technology establishments and advanced robotics.
However, Geospatial Technology; which includes Geographic Information System (GIS) and Location Intelligence (LI) is a sector that has witnessed its own fair share of AI-induced technological disruptions. Geospatial Technology encompasses all the tools used in capturing, storing, analyzing and displaying geographic data. It can be used to link seemingly unrelated data for better understanding of spatial patterns and relationships.
The potency of LI lies with the availability and accessibility of high quality Big Data. Since 80% of all data has a location component, actionable insights can be derived from questions beginning with a “where”. The corresponding answers to these questions are best visualized using maps. My personal interaction with the concept of AI is primarily from its fusion with LI and the origin of this experience was with maps.
What I find amazing about this technology is its powerful capabilities in answering questions and addressing business and global developmental challenges. Due to its potency, I am constantly enthused by any possibility of utilizing its application for problem solving and as a decision support tool.
As laudable as Geospatial technology may sound, the availability, accessibility and quality of data is critical to its success. Predictive algorithms rely on large volumes of high quality data essential for actionable intelligence. The integration of AI with GIS is invaluable in several ways including the automation of tasks and processes.
Over the past couple of years, I have advised current and prospective stakeholders in the Financial Services, Insurance, Agriculture, Utility and Telecommunications industries on the possibility of determining patterns and trends which unbeknownst to them; is critical for effective decision making. With LI, we are now able to answer location-based questions such as:
- Where do the customers most likely to patronize your products live?
- Where is the most suitable (profitable) location to site my store or business?
- Where do customers of a certain demographic live?
- Which areas are more prone to risks associated with flooding?
- Where are the most suitable areas for agricultural crops to thrive?
These questions are not exhaustive and cut across all industries. One remarkable thing of note is that their corresponding answers are all tied to location.
True business intelligence for a decision maker is derived from the ability to identify patterns, clusters and trends critical for resource and asset optimization.
In addition, the causal relationship between business and geospatial data within a defined territory or geography will reveal critical insights which were hitherto unseen.
There lies the power of “where”.