To derive tangible value from AI-driven capabilities, businesses must develop a novel strategic approach. Legacy utility architectures struggle to accommodate the escalating demands of AI-infused functionalities. As the pace of innovation accelerates, organizations must evolve by modernizing their infrastructure, processes, and utility architectures using cloud-native technologies to maintain a competitive edge?
Organizations currently operate amidst a backdrop of rapid geopolitical transformations, intensifying competition, supply chain volatility, and shifting customer expectations. AI functions may support innovation by providing flexibility to scale when needed. By modernising their functions, organisations can harness the benefits of agility, scalability, and rapid computational efficiency, thereby facilitating swift innovation and accelerating the delivery of AI capabilities. According to David Harmon, AMD’s director of software program improvement, corporations must prioritize migrating their existing environments and leveraging new hardware advancements to minimize the total improvement lifecycle of future applications, ultimately enabling a swift response to evolving global conditions?
Constructing and deploying innovative applications at speed, while modernizing functions, data, and infrastructure, can significantly elevate the customer experience. Australian supermarket chain leveraging cutting-edge technology to deliver seamless e-commerce experiences for customers across both online and offline platforms. Using Azure DevOps, Coles has successfully transitioned from monthly to weekly deployments of functions, concurrently reducing build instances by several hours. By consolidating consumer perspectives across multiple channels, Coles is able to deliver more bespoke customer experiences. As evidence suggests, a significant surge has occurred in leveraging AI across digital customer experience toolsets, with 55% of companies currently adopting it to some extent, and more embarking on this path.
Despite rigorous design, even the most robust functions remain vulnerable to sophisticated cyber attacks? If granted access, unscrupulous actors could potentially extract sensitive data from machine learning models or deliberately inject AI systems with tainted information. “A new era of organizational efficiency has emerged as AI functions seamlessly integrate with your existing core data,” remarks Surendran. “Protecting sensitive information demands robust guardrails. Fortunately, modern cloud-based architectures can deliver robust security, data governance, and artificial intelligence-powered safeguards, ensuring the integrity of AI applications by shielding them from potential threats and complying with industry regulations.”
Unprecedented threats, emanating from formidable adversaries and malicious cyber-attackers, necessitate the development of a cutting-edge approach to revitalizing operational capabilities. “To thrive in today’s fast-paced market, a robust underlying infrastructure is crucial for sustaining growth and delivering products to customers quickly.” “Not having a solid foundation can slow you down.”
Enter cloud native structure. As organizations increasingly leverage AI to accelerate innovation and stay competitive, a growing imperative exists to reexamine how functions are designed and deployed within the cloud infrastructure. Organizations can accelerate AI adoption by embracing cloud-native architectures, leveraging Linux, and tapping into the flexibility of open-source software to build an agile platform purpose-built for AI and optimized for the cloud. The open-source software community flourishes due to the inherent freedom to choose, Harmon notes, with the ecosystem thriving as a direct result. As emerging technologies come into being.
The utility modernization effort prioritizes optimal efficiency, scalability, and safety to effectively support the integration of artificial intelligence applications. As a natural consequence of modernization, it transcends mere migration of utility workloads to cloud-based infrastructure. Somewhat, a cloud-native architecture is inherently designed to provide builders with several options that
- The ability to adapt and grow in response to shifting demands?
- What startups are creating innovative mobile apps?
- Accessing top-tier tools and services to seamlessly craft and implement innovative applications?
- Security seamlessly integrated within a utility to safeguard sensitive data.
By leveraging these cloud capabilities, organizations can maximize the value they derive from their AI initiatives. “On the end of the day, everything is about efficiency and safety,” Harmon remarks. Cloud isn’t any exception.
