AI Is Helping Make Cloud Management Smarter
Analytics India Magazine (Ankush Das)
In the fast-evolving landscape of enterprise technology, the hybrid cloud has become the backbone of digital transformation. It combines the agility of the cloud with the management control of on-premises infrastructure. But as systems grow more complex, AI is becoming the driving force that enables organisations to move faster and make smarter decisions.
“AI is emerging as the strongest driving force for change, especially in hybrid cloud environments,” said Abhishek Agarwal, president, Judge India & Global Delivery, The Judge Group, a business consulting and services firm.
He said, “We are witnessing firsthand how AI is transforming the way organisations manage, optimise, and secure their hybrid cloud environments.”
Predictive Power and Automation
Across industries, companies are leveraging AI to automate repetitive work and predict problems before they occur.
Agarwal noted, “Firms are adopting AI-powered predictive analytics and automation in their mix of cloud and on-premises computing environments.”
He explained that AI-powered predictive analytics anticipates potential failures, performance issues, and security threats before they impact operations. This capability is crucial in sectors like banking and retail, where it can prevent costly downtime during peak periods.
Furthermore, AI automates routine management tasks such as provisioning, patching, and compliance scans. This frees up IT personnel to focus their expertise on innovation, rather than being consumed by repetitive maintenance tasks.
Smarter Workload Decisions
For years, deciding which workloads to move to the cloud and which to keep on-premises has been a balancing act for enterprises, Agarwal said.
“AI is making that decision easier by evaluating a variety of factors, including how sensitive the data is, latency needs, and cost considerations, in order to determine the best approach for that workload.”
He added that AI’s ability to evaluate workload stability can help organisations optimise performance, security, and cost savings. For instance, AI can recommend keeping sensitive financial data on-premise for security, while moving less sensitive or mission-critical applications and services to the public cloud to reduce costs.
Towards Self-Optimising Systems
Enterprises are steadily moving away from static cloud management and towards intelligent, adaptive systems.
Agarwal said that, “Previously, IT teams manually configured workloads and collected performance data by hand, and AI orchestration tools can now manage, migrate, and load-balance workloads across environments in real time.”
He added that these systems leverage continuous learning to adapt to evolving business needs, thereby enhancing agility and optimising resource utilisation.
Agarwal described this evolution as paving the way “for the advent of smart cloud management, a new era of navigation, where better operational flexibility, cost savings, and uptime can all be realised with fewer points of intervention.”
AI for Security and Compliance
In an era of constant cyber threats, the security dimension of hybrid cloud cannot be overlooked. “Given the increasing prevalence of cyber threats, AI is critical for real-time risk detection and improved compliance in hybrid cloud environments,” Agarwal said.
“AI-enabled security systems can analyse massive amounts of network traffic to detect anomalies or potential threats in advance,” he explained.
AI can assist organisations in fulfilling regulatory requirements and data privacy obligations by proactively identifying potential compliance deficiencies. For instance, AI can track the whereabouts of sensitive data, monitor access methods, and ensure adherence to specific security protocols, Agarwal said.
Industry Leaders and the Road Ahead
Some industries are moving faster than others in this transformation. “Healthcare, retail, banking, and insurance (BFSI) are the industries where AI-enabled hybrid cloud solutions are emerging the fastest,” Agarwal said.
“In BFSI, AI is well-suited to help in fraud detection and prevention, risk management, and transaction monitoring by benefiting from the secure and scalable nature of the hybrid cloud model,” he explained.
“Healthcare providers, in compliance with strict data regulations, use AI for medical imaging analysis, patient health record management, and predictive diagnostics.”
Retailers, for instance, are leveraging AI to gain deeper insights into consumer behaviour, optimise inventory management, and create tailored shopping experiences both online and in physical stores.
Agarwal anticipates that the upcoming phase of AI-driven hybrid cloud transformation will be defined by several key trends. These include a shift towards fully autonomous cloud operations, where machine learning and predictive analytics enable the cloud system to self-manage.
“Edge computing will take center stage,” he added, “as AI will process data near the edge quickly and with low latency to allow for real-time decision making.”
He also pointed out that sustainable cloud behaviours leveraged via AI will also help businesses track and reduce their carbon footprint, thereby supporting international green IT initiatives.
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