Moving Beyond Private Vs Public Cloud: The Case for Digital Infrastructure in the AI Era

· 22 May 2024 · 4 minute read

Moving Beyond Private Vs Public Cloud: The Case for Digital Infrastructure in the AI Era

As businesses embrace the potential of generative AI, there’s a stronger case to be made for moving from a traditional cloud set-up to a more holistic digital infrastructure. With distributed application and data architectures that runs across multiple locations, traditional IT infrastructure models need to evolve to meet the ensuing challenges.

These setups such as public cloud, private cloud, and on-premises solutions, can often result in data silos, compliance challenges, and operational inefficiencies that hinder agile AI deployment. An integrated approach, however, can help facilitate seamless data flow and real-time processing capabilities that are essential for effective AI utilisation.

Challenges in Data Management: The Rise of Data Gravity

The proliferation of data poses significant challenges for organisations, leading to the phenomenon known as data gravity. As data accumulates, its gravitational pull increases, making it increasingly difficult to move and manage large datasets. This poses a fundamental challenge for businesses as effective AI relies on high-quality, accessible data. Addressing data gravity requires strategic data management approaches that prioritise data accessibility, quality, and security, while ensuring scalability to accommodate evolving workloads.

Building a Hyperconnected Digital Infrastructure

A unified digital infrastructure brings together different platforms to create a cohesive environment supporting AI. This involves the optimal use of applications, business logic, data lakes, and machine learning algorithms across a broad array of platforms including hyperscalers, private cloud, and edge computing. Such configurations can create a fabric of interconnected data, computing resources and optimise data utilisation for intelligence and insights, regardless of the data’s origin.

Companies’ AI Ambitions Challenged by IT Limitations

A report by MIT Technology Review Insights in partnership with Telstra International highlights a critical gap between aspiration and execution in AI adoption: less than 30% of surveyed executives express confidence in their current IT infrastructure’s ability to support ambitious AI rollouts. These concerns span hardware limitations, data volume management, accuracy, and storage infrastructure, indicating a pressing need for a new approach that integrates data and computing resources across the entire business landscape.

Importance of Connectivity

In the rapidly evolving landscape of AI, hyperconnectivity emerges as a key enabler of innovation and growth. Hyperconnected networks, powered by technologies like 5G, edge computing, and cloud, provide the agility and scalability required to support AI-driven applications across diverse industries. This interconnectedness forms the foundation of what Telstra International refers to as the "digital fabric" — an integrated network infrastructure that seamlessly connects data, devices, and applications.

As the future of AI relies heavily on hyperconnected networks , businesses can invest in robust hyperconnected digital fabrics to accelerate their digital transformation journeys and unlock new opportunities for growth and success.

Insights from Industry Leaders

Discussions from a recent roundtable hosted by Telstra International and Equinix shed light on AI deployment struggles and successes across various sectors:

  • Financial Services: Executives emphasised the need for an infrastructure capable of real-time data analytics to enhance customer interaction and security protocols.
  • Retail: AI's role in inventory management and customer service was highlighted, emphasising the need for a robust infrastructure to process vast amounts of unstructured data.
  • Healthcare: The use of AI in diagnostics and patient management underscored the need for an agile, secure infrastructure to manage sensitive data effectively.

Paradigm Shift in Infrastructure Strategy

The transition to a holistic digital infrastructure represents more than a technological upgrade. It's more akin to a strategic realignment to meet the needs of modern AI systems. As AI evolves, organisations’ supporting infrastructure needs to advance in step to accommodate future innovations. By adopting a holistic approach to digital infrastructure, organisations can unlock the full potential of AI and drive meaningful business outcomes in today's digital age.

Get in touch to learn how to build a cost-effective, hyperconnected digital infrastructure that facilitates seamless and secure data movement across your organisation and extended ecosystem.

Related articles