AI and the Drive to Modern, Cloud-Native Applications
Artificial intelligence (AI) has changed how modern applications interact with us, and machine learning has driven the modernization of various processes and systems. We all know that artificial intelligence has strengthened its hold on how we interact with computers. Siri, Alexa, Cortana and Hey Google are now natural parts of our life, and references to them regularly appear in mainstream entertainment, such as TV shows and advertisements.
Artificial intelligence and machine learning are also a natural part of our evolving ecosystem. People understand, for example, that the “social media algorithm”—the infamous algorithm that decides who sees what social media content—is driven by artificial intelligence.
People are less familiar, but no less surprised to hear, that machine learning (ML) drives all sorts of analytics. It drives figuring out product trends, determining the best advertising content to deliver to a consumer and deciding how much of which products need to be kept in stock on store shelves to meet future demand.
What’s less obvious, less well-known, yet no less important is the role that artificial intelligence and machine learning (AI/ML) is playing in the actual development of software itself. AI-assisted software development is an area of considerable investment. Using AI to analyze software to find potential bugs is an evaluation technique that has been around for a while.
But using AI to help a software developer determine the best strategy for writing a particular piece of code while they are writing the code—that is new technology. This capability has seen significant investment recently. Companies like GitHub now offer Copilot, a tool that purports to act as a virtual pair programmer for a software developer, making coding suggestions and catching mistakes on the fly, assisting the developer in building higher-quality code faster.
Even citizen development has seen significant growth and investment in artificial intelligence. Citizen development is when non-programmers build applications that solve specific business needs. Historically called low-code or no-code programming, citizen development has expanded in use and capabilities in recent years. This expansion has driven the use of artificial intelligence as a programming assistant to non-programmers. This has enabled the building of larger and more complex applications with less assistance from software developers and development teams.
AI/ML have gained deeper acceptance in modern software used in many industries. For instance, technology such as checkoutless stores is starting to emerge in retail. AI can be used to reduce fraud in stores that allow customers to scan their own items on the fly. And sophisticated AI is being used with ultra-modern applications to create complete cashierless customer experiences. Just look at the Amazon Go storefronts, where customers can simply walk in, take products they require, and walk out—sophisticated AI and imaging technology automatically determine what products the customer took and charges the appropriate amount to their account.
Logistics is a prime industry that is poised to see huge benefits from AI/ML and modern application technologies. Both backend logistics (international and interstate product shipment) and last-mile logistics (delivery to your home) are poised for a fundamental upgrade in technology, including cloud-native applications using sophisticated AI/ML systems.
Modern cloud-native applications are driving logistics in the areas of planning and scheduling. Companies like Tesla are envisioning long trains of driverless trucks driving down the United States interstate highway system. Companies like Domino’s Pizza and Amazon.com are experimenting with driverless home delivery with the goal of radically changing last-mile logistics.
Along with other cloud-native technologies, AI/ML are changing the way businesses work and interact with customers and the services and expectations they deliver.
