Look Ahead: AI, Location Intelligence and Efficiency

January 3, 2024

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The biggest business news of the past 12 months didn’t involve the Federal Reserve or Wall Street. It was the coming-out party for AI. When ChatGPT was launched at the end of last year, it had one million users within five days. The number of users reached 100 million by January and it may hit one billion by the end of 2023.

There has been no shortage of “think piece” articles from experts about the impact of AI. They range from glowing commentaries about how nearly every aspect of human life will be positively transformed by AI to dystopian commentaries predicting that AI will be the downfall of our species.

 I have a different perspective on AI – a much more practical one. I see it as a very useful tool that becomes exponentially more useful when you combine it with other technologies like location intelligence. Directions Magazine echoed that belief in its recent article titled, “How AI and Geospatial Technologies Can Make a Difference.” In that article, the editorial staff framed their discussion of the impact of the of AI and geospatial technologies in this way:

 “By integrating spatial data and geographic context into AI systems, location intelligence provides valuable insights and enhances the accuracy, efficiency, and effectiveness of AI algorithms and applications.”

I agree with that view, and I will take it a step further. I believe generative AI, natural language interfaces like ChatGPT, and machine learning (ML) technologies will combine with location intelligence to create powerful tools that will dramatically magnify the impact of geospatial technology. And these tools will be indispensable not only for professionals who already work with location data and insights (such as readers of Directions Magazine), but for people across organizations who may never have heard the words “geospatial” and “photogrammetry.” Using natural language prompts like ChatGPT, people who do not have expertise in geospatial data analysis will be able to harness the power of those insights to be far more productive. And power users who do have experience with location intelligence will be able to be even more productive extracting insights from location data and applying that to their work.

 Many of the dystopian commentaries about AI talk about how the technology will render humans irrelevant, but I strongly believe that AI and location intelligence will make employees even more valuable. When you combine location data, location intelligence, and AI/ML technology, it is possible for employees to automate the most tedious parts of important business processes in ways that allow vital projects to move forward faster, more efficiently, more successfully and more cost-effectively. It frees people up to focus on more important work that has an even bigger impact on the success of projects and on the success of the organization.

 To illustrate that, let’s look at a way that AI/ML and location intelligence will bring far greater efficiency to an industry like utilities. Assessing, maintaining, and upgrading infrastructure like electrical poles is a critical responsibility for electrical utilities, but today it is a tedious, time-consuming process for crews: today, a crew is sent to a neighborhood to visually inspect poles, conduct triage, add that information to a GIS system, and coordinate work orders for the maintenance that needs to be done. If a neighborhood like mine has 3,000 poles in it and one crew member can inspect an average of 10 poles per day, that process will take almost an entire calendar year. That’s for just one neighborhood. Now think about how much labor that is for a utility’s entire geography, which might have hundreds of thousands or even millions of utility poles. This is a vital job that must be done, but what if you could make that inspection process far more efficient so that the crews can make progress on other urgent infrastructure management tasks?

 That is exactly what is possible when AI/ML is combined with location intelligence. Rather than sending work crews to inspect every pole in a given neighborhood, the utility can conduct automated analysis of satellite and aerial photos to determine which poles show signs of degradation. Using AI/ML, a process that previously required almost a year of labor can be accomplished in minutes. The crews can then focus on rolling their trucks to the small subset of poles that warrant in-person inspection, accelerating the process of conducting maintenance, repairs, and replacements. This increased efficiency enables the utility to then devote more time and resources to forward-looking infrastructure projects that too often end up on the back burner because of the enormous backlog of basic tasks that take priority.

 The efficiency gains don’t stop there. The combination of AI and location intelligence can also automate other labor-intensive processes that utilities professionals to do higher-value work.

AI-driven location intelligence apps can automate the process of updating electrical, gas, and water utilities’ GIS system with information gathered from work crews – a process that is currently highly-manual and tedious for most organizations. This would release work crews and the GIS department from tedious tasks to work on more strategic projects.

Insights from AI analysis of location data can bring far greater efficiency to vegetation management for electrical utilities, a notoriously labor-intensive process whose importance has grown significantly over the last two decades due to the rising danger of wildfires and the increasing intensity of storms. Utilities can use perennially-shorthanded vegetation management teams far more effectively, deploying them to address issues that have been pre-flagged by AI-driven apps as the most urgent.

 AI-driven analysis can dramatically accelerate the process of mapping natural gas lines from mains to residential and commercial buildings – a process recently mandated by the federal government in the U.S. to avoid safety issues like those that led to a gas main failure and explosion in California. Traditional approached to mapping these decades-old lines is labor-intensive and often highly-inaccurate. AI can make this process far more efficient and accurate, enabling engineers and crews at gas utilities to focus on much-needed infrastructure upgrades.

These are just a few examples of how AI/ML and location intelligence combine to bring far greater efficiency in the utilities industry. The impact will be similar in a long list of other industries, and none of the applications I have addressed result in workers being replaced. The result is that workers become more valuable by skipping over their most tedious, time-consuming basic tasks in order to devote far more time to the higher-value tasks that they and their bosses would love them to have time for.

The most exciting thing to me – as someone who has committed my career to geospatial technology – is that AI helps make that a reality across the organization so that location-based insights benefit not only GIS professionals but also people who have limited or no experience with digital maps and GIS apps. We are entering a golden age for the impact of location intelligence, and AI/ML and natural language interfaces are a powerful catalyst for putting these tools in the hands of far more people around the world. 


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