And yet, in some quarters of computing and finance, there is a noticeable reverse cloud migration – companies deciding they want to move parts of their data, applications and workloads from public cloud back to on-premises or local private cloud infrastructure.
As AI adoption accelerates, enterprises must rethink their data storage, management, and processing strategies to support performance-intensive workloads like generative AI.
Matthew Hardman, APAC chief technology officer for Hitachi Vantara, sees a parallel between today’s AI hype and the initial cloud rush. He posits that many organisations are eager to adopt AI, often overestimating their readiness.
He goes on to suggest that while this drive for innovation is positive, companies are now evaluating what truly benefits them, what he refers to as "innovation on their terms."
At the same time, cybersecurity concerns, including ransomware, are now global priorities, even in markets where such issues were previously less emphasized. He believes this focus on both innovation and resilience is shaping the data infrastructure landscape, requiring a balanced approach.
Streamlining data management processes
Statista forecasts that by 2025, data volumes will have reached 180 zettabytes. Hardman says to also expect more complicated data management challenges to flow from this.
Hardman reminds us that the issue is more than just an element in storage. “Data is now a critical business asset necessitating storage, protection, archival, and utilisation,” he cautions. He raises the term "data gravity" which draws more applications, and which, in turn, produces more data, and the cycle repeats.
“The key challenge is understanding what data is valuable. We must sift through the "mud" to find the valuable "gold" in our data,” he continues. “This requires sophisticated data management strategies, tailored to data criticality and usage. This, in turn, helps to optimise financial outcomes and IT budget allocations.”
The right mix of on-prem and cloud
Asked if there is such a thing as the right balance of on-premise, collocation infrastructure and public cloud, Hardman says optimal infrastructure solution always depends on specific circumstances. Key considerations include performance requirements, cost, regulatory compliance, and risk profile.
He suggests a detailed evaluation of risk tolerance and investment is helpful as cybersecurity resilience varies across environments. “For instance, on-premise solutions may involve building robust data centres that ensure 100% data availability,” he continues. “In comparison, attaining a comparable level of reliability in the cloud may incur higher costs due to the need for additional services. Colocation may be most ideal for maintaining control over edge-generated data.”
He notes a significant trend towards hybrid cloud architectures in Asia Pacific, as businesses seek flexible, compliant, and efficient infrastructure solutions.
Meeting data security and compliance requirements
Hardman raises the topic of "data effect" and highlights two major challenges: the exponential growth of data and its questionable value.
Matthew Hardman
“Not all data is valuable, yet organisations tend to capture everything, leading to complexity in managing and securing it. With 90% of data expected to be outside the cloud by 2025, regulatory and skill challenges amplify the issue.”
Matthew Hardman
He believes that CIOs now need to navigate not only infrastructure but also legal and security concerns. “Effective data management starts with discovery, prioritising critical systems, and employing immutable storage to protect against ransomware. Regular testing of disaster recovery plans is essential to mitigate risks and ensure resilience,” he continues.
The sustainability conundrum
One of the value propositions of the cloud is scalability and availability. But more recently, there has been growing interest in the issue of sustainability. What data strategies can organisations adopt that allow them to balance the need for scalability (as far as businesses are concerned) and, at the same time support sustainability goals, particularly as we start using new applications such as AI and cloud initiatives?
Hardman acknowledges that sustainability, particularly environmental sustainability, is a critical challenge. He points out that modern infrastructure can offer significant environmental benefits, such as reduced power consumption and the ability to run in warmer conditions, thereby lowering cooling needs.
“Enterprises can tap on innovations like power-efficient storage units and intelligent software that adjusts resource use according to demand,” he adds. “Organisations can also opt for “greener” storage arrays that adhere to globally recognised standards and certifications.”
He clarifies that it is also important to recognise that moving to the cloud doesn't eliminate environmental impact; it merely shifts it. “True progress in environmental sustainability requires a holistic approach, considering all aspects of our technological ecosystem,” he adds.
Food for thought
Hardman says CIOs encounter multifaceted challenges in growth, profitability, resilience, and sustainability. They need to juggle the demands of innovation with cyber-resiliency and environmental requirements.
“CIOs must act as the voice of reason, balancing innovation with the risks and technical debt it may incur. They need to guide the organisation in making tough decisions, like retiring outdated systems, and align with CFOs to rationalise these choices,” he continues.
He also contends that IT departments should embrace diversity by introducing fresh hires with skills and perspectives divergent from that of the old guard. “This can drive meaningful innovation tailored to business needs, rather than simply following industry trends,” he concludes.
Click on the PodChats player and hear Hardman elaborate on his perspective on data strategies for the AI-native enterprise.
Where are Asian enterprises today around data management?
How can we streamline data management processes to handle the increasing volume and complexity of data?
How are enterprises addressing the need to minimise operational latency while improving data movement in hybrid cloud environments?
What’s the right balance between on-premises infrastructure and cloud services?
How can CIOs ensure data security and compliance across different cloud environments?
What data strategies can we adopt to balance the need for scalability with environmental sustainability goals in our AI and cloud initiatives?
Given all the unpredictability that lies ahead, any suggestion for CIOs (not just to keep their jobs but more importantly to lead and support the business’ need for growth, profitability, resilience and sustainability?
Allan is Group Editor-in-Chief for CXOCIETY writing for FutureIoT, FutureCIO and FutureCFO. He supports content marketing engagements for CXOCIETY clients, as well as moderates senior-level discussions and speaks at events.
Previous Roles
He served as Group Editor-in-Chief for Questex Asia concurrent to the Regional Content and Strategy Director role.
He was the Director of Technology Practice at Hill+Knowlton in Hong Kong and Director of Client Services at EBA Communications.
He also served as Marketing Director for Asia at Hitachi Data Systems and served as Country Sales Manager for HDS’ Philippines. Other sales roles include Encore Computer and First International Computer.
He was a Senior Industry Analyst at Dataquest (Gartner Group) covering IT Professional Services for Asia-Pacific.
He moved to Hong Kong as a Network Specialist and later MIS Manager at Imagineering/Tech Pacific.
He holds a Bachelor of Science in Electronics and Communications Engineering degree and is a certified PICK programmer.
