In the ever-evolving landscape of enterprise technology, as CTO of EagleView, I’ve witnessed the emergence of Generative Artificial Intelligence (AI) as a transformative force, driving innovation and offering solutions to complex business challenges. It has been imperative that we foster educational opportunities throughout EagleView to understand the importance of this technology revolution and how we should embrace it. As our organization continues to navigate this exciting yet challenging frontier, it’s vital to understand the tools we use and why they are crucial for our growth and resilience.
Overcoming Generative AI Challenges
Integrating Generative AI into enterprise operations is not without its hurdles. Three significant challenges we have seen are:
(a) being informed of the breadth of use-cases and prioritizing effectively,
(b) having a clear alignment of AI capabilities with existing business processes and products, and
(c) measuring the impact to the business in a quantitative manner.
At EagleView, we evaluate AI capabilities across two dimensions; those that improve internal processes (i.e. productivity) and those that improve business development and customer needs (i.e. product). 3rd-party Generative AI solution providers are evolving exponentially and thereby, the need of staying abreast of the latest productivity tools is of upmost importance and this has been supported by staying in close contact with trusted partners and others in our peer group. With this guidance coupled with internal research, conducting pilots amongst a more narrowed set of Generative AI products sharpens the landscape of potential productivity impacts.
However, this will continue to change. As an organization, we set metrics to drive the exploration, fully expecting our toolset to evolve and our business processes to bend to that evolution. Regarding measuring productivity, significant research has focused on this recently with the emergence of Generative AI. We carefully evaluate productivity both quantitatively and qualitatively. Adoption is a crucial metric to monitor and likely the most critical. Just as the first introduction of company chat communication tools (e.g. IBM Chat) has rapidly evolved over time, Generative AI is charting the same course and encouraging adoption and evaluating the use cases is the best way to grow efficiently with these tools.
Are There Lesser-Known Examples of Generative AI Applications for Businesses?
EagleView’s Assess drone inspection solution is capable of accurately detecting hail and wind damage to roofs using machine learning, but getting there wasn’t easy. While we had a large historical library of overhead roof images, the vast majority were captured using airplanes rather than drones. And most of these roof images were examples of healthy roofs without hail and wind damage. What we really needed were good examples of ultra-high resolution drone imagery for damaged roofs, ideally with the individual hail strikes and wind creases accurately labeled.
While EagleView could have sourced and annotated such “ground truth” training data in the field, it would have significantly delayed the product development process and come at a great expense. EagleView’s data scientists employed generative AI methods to create a large base of synthetic training data in the form of damaged roof simulations. While the synthetic training data didn’t immediately produce a highly accurate model, it greatly accelerated the fine-tuning process as more and more drone flights were completed and the model was improved through reinforcement learning through human feedback (RLHF). With its AI-based damage detection, Assess has taken off in the construction world, helping roofers provide accurate, verifiable evidence of roof damage to property insurance claims adjusters and win more roof repair and replacement projects.
EagleView’s Innovative Solar Program with Generative AI
Beyond common applications like content generation and design, Generative AI harbors potential into new frontiers forging innovative techniques to enable enterprise solutions. Our solar program exemplifies this, leveraging Generative AI to improve accuracy and reduce delivery time. Generative Adversarial Networks (GANs) were an early form of Generative AI that helped speed up development of this technology. At a high level, GANs work by creating two neural networks that effectively compete against each other (hence adversarial) and result in these models learning how to better fake outputs and resultantly, detect fake outputs. We’re continuing to explore how additional Generative AI approaches can benefit this product.
Can Generative AI Revolutionize Auditing?
Generative AI offers a compelling use-case in auditing, supplanting and regulating legacy systems. Technology companies with long histories and/or prolific product portfolios are bound to suffer from the crippling effects of dated documentation, unsupported applications and technical obsolescence. EagleView is leveraging Generative AI to counter this, and a few areas that we are seeing opportunities include deconstructing institutional knowledge and upgrading end-of-life (EOL) software. Given many years of growth and acquisitions, it has been an ongoing priority for EagleView to remain efficient in knowledge maintenance and transfer. Now, by integrating Generative AI into our proprietary data, anyone across the company can query this information model to better understand a variety of facets of the business; products, technology, organization, etc.
Additionally, the common time-consuming task of upgrading software to later versions of recently EOLed software can now leverage automated code assistants like GitHub Copilot. This work doesn’t come for free, yet given that these models are familiar with a multitude of languages and versions on those languages, they can quickly provide a solution that can be immediately dropped into testing. Managing legacy technologies is going to look very different at EagleView over the next year with Generative AI.
Is Generative AI the Next Business Revolution?
Generative AI is revolutionizing industries in a manner reminiscent of past technological upheavals, such as the advent of the internet or the rise of mobile computing. Just as these technologies redefined the business landscape, Generative AI is poised to transform how companies operate, create, and compete. Software will be delivered faster. Marketing content will be mostly automated. Customer service will be quicker, more accurate, and (ironically) more personal. There’s an ever-growing demand to do more. Companies that embrace generative AI now are likely to gain a significant competitive advantage, much like early adopters of the web and mobile technology did. Those who delay risk falling irretrievably behind, as the pace of change accelerates and the benefits of AI-driven innovation become increasingly integral to business success.
Ready for Generative AI?
As EagleView continues to integrate Generative AI into its business operations, the benefits become increasingly evident. From enhancing creativity to improving efficiency and bolstering resilience, Generative AI is not just a technological advancement but a strategic asset in today’s competitive landscape. It’s critical that others also embrace a growth mindset and strategy around these advancements. By addressing the challenges and capitalizing on the opportunities it presents, our enterprises can look forward to a future where innovation is not just welcomed but woven into the very fabric of business operations. And this means all business operations. Heck, even this article couldn’t escape from the ever-reaching clutches of Generative AI.
