Accelerating AI innovation through application modernization

However, realizing measurable business value from AI-powered applications requires a new game plan. Legacy application architectures are simply not capable of meeting the high demands of AI-enhanced applications. Instead, now is the time for organizations to modernize their infrastructure, processes and application architectures using cloud-native technologies to remain competitive.

Now is the time to modernize

Today’s organizations exist in an era of geopolitical change, growing competition, supply chain disruptions, and evolving consumer preferences. AI applications can help support innovation, but only if they have the flexibility to scale when 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 for AMD, says companies “really want to make sure they can migrate their current [environment] and take advantage of all the hardware changes as much as possible.” The result is not only a reduction in the overall life cycle of new application development, but also a quick response to changes in global circumstances.

In addition to rapidly building and deploying intelligent applications, modernizing applications, data and infrastructure can significantly improve user experience. Take Coles, for examplean Australian supermarket that has invested in modernization and uses data and artificial intelligence to deliver a dynamic e-commerce experience to its customers online and in-store. With Azure DevOps, Coles went from monthly to weekly application deployments while, at the same time, reducing build times by hours. Moreover, by collecting customer views across multiple channels, Coles has been able to provide more personalized customer experiences. In fact, according to a CMSWire Insights Report 2024there is a significant increase in the use of AI across the digital customer experience toolkit, with 55% of organizations now using it to some extent and more just getting started.

But even the most carefully designed applications are vulnerable to cyber attacks. Given the opportunity, bad actors can extract sensitive information from machine learning models or maliciously inject corrupted data into AI systems. “AI applications are now interacting with your core organizational data,” says Surendran. “It’s important to have the right guardrails in place to make sure that data is secure and built on a platform that allows you to do that.” The good news is that modern cloud-based architectures can provide robust security, data governance, and AI guardrails like content security to protect AI applications from security threats and ensure compliance with industry standards.

The answer to AI innovation

New challenges, from demanding customers to malicious hackers, require a new approach to application modernization. “You need to have the right underlying application architecture to keep pace with the market and bring applications to market faster,” says Surendran. “Not having that foundation can slow you down.”

Enter cloud native architecture. As organizations increasingly adopt artificial intelligence to accelerate innovation and stay competitive, it is increasingly urgent to rethink the way applications are built and deployed in the cloud. By adopting a cloud-native architecture, Linux, and open source software, organizations can better facilitate AI adoption and create a flexible platform built for AI and optimized for the cloud. Harmon explains that open source software creates opportunities, “And the overall open source ecosystem just thrives on that. It allows new technologies to come into play.”

Application modernization also ensures optimal performance, scale and security for AI applications. That’s because modernization goes beyond simply lifting and offloading applications to virtual machines in the cloud. On the contrary, cloud native architecture is inherently designed to provide developers with the following features:

• Flexibility to scale to meet growing needs
• Better access to the data needed to run intelligent applications
• Access to the right tools and services to easily build and deploy intelligent applications
• Security built into the application to protect sensitive data

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 safety,” says Harmon. Cloud is no exception.