But achieving measurable business value from AI-powered applications requires a new plan. Traditional application architectures cannot meet the high demands of AI-enhanced applications. Rather, it’s time for organizations to modernize their infrastructure, processes, and application architectures using cloud-native technologies to stay competitive.
Now is the time for modernization
Today’s organizations exist in an era of geopolitical change, increased competition, supply chain disruption, and evolving consumer preferences. AI applications can help by supporting innovation, but only if they have the flexibility to scale as needed. Fortunately, by modernizing applications, organizations can achieve the agile development, scalability, and fast computing performance needed to support rapid innovation and accelerate the delivery of AI applications. David Harmon, director of software development at AMD, said companies “really want to make sure they can migrate their current (environment) and take advantage of all the hardware changes as much as possible.” states. The result is not only a shorter overall development lifecycle for new applications, but also a faster response to changing global conditions.
In addition to rapidly building and deploying intelligent apps, you can modernize your applications, data, and infrastructure to dramatically improve the customer experience. Take, for example, Coles, an Australian supermarket that has invested in modernization and uses data and AI to offer customers a dynamic e-commerce experience both online and in-store. By using Azure DevOps, Coles moved from monthly to weekly application deployments, while saving hours of build time. Additionally, Kohl’s can now deliver a more personalized customer experience by aggregating customer feedback across multiple channels. In fact, according to the 2024 CMSWire Insights report, the use of AI is increasing significantly across digital customer experience toolsets, with 55% of organizations currently using AI to some extent and many more looking to adopt it. It’s starting.
However, even the most carefully designed applications are vulnerable to cybersecurity attacks. Given the opportunity, bad actors could extract sensitive information from machine learning models or maliciously inject corrupted data into AI systems. “AI applications are now interacting with an organization’s core data,” says Surendran. “It’s important to have the right guardrails in place to ensure your data is secure and built on a platform that enables it.” Fortunately, modern cloud-based architectures You can provide AI guardrails such as robust security, data governance, and content safety to protect your AI applications from security threats and ensure compliance with industry standards.
The answer to AI innovation
From demanding customers to malicious hackers, new challenges require new approaches to modernizing applications. “To keep up with the market and bring applications to market faster, you need the right underlying application architecture,” says Surendran. “If you don’t have that foundation, it can slow you down.”
Enter cloud native architecture. As organizations increasingly embrace AI to accelerate innovation and stay competitive, there is a growing urgency to rethink how applications are built and deployed in the cloud. By adopting cloud-native architectures, Linux, and open source software, organizations can accelerate AI adoption and create flexible platforms built for AI and optimized for the cloud. Harmon explains that open source software creates options. “And the whole open source ecosystem thrives on that. It allows us to take advantage of new technologies.”
Application modernization also ensures optimal performance, scale, and security for your AI applications. Because modernization is more than just lifting and shifting application workloads to cloud virtual machines. Rather, cloud-native architectures are inherently designed to provide developers with the ability to:
Flexibility to scale with your evolving needs Better access to the data you need to power intelligent apps Access to the right tools and services to easily build and deploy intelligent apps Applications to protect sensitive data security built into
Together, these cloud capabilities ensure that organizations get the most value from their AI applications. “At the end of the day, it’s all about performance and security,” Harmon says. Cloud is no exception.