A hybrid cloud approach enables businesses to deploy workloads across both public and private cloud environments based on specific workload characteristics. This flexibility is particularly critical as AI and generative AI (GenAI) models mature, allowing organizations to make strategic decisions about where to run their applications and data in the most optimized and secure manner.
“A hybrid cloud strategy will become essential for running GenAI/AI-related workloadsas the market matures around the value realization, scaling requirements and security concepts,” says Rampal Singh, Global Head, Hybrid Cloud Business Unit at HCLTech.
The growing trend of multi-cloud adoption is a significant enabler of hybrid cloud strategies. In fact, according to HCLTech’s latest cloud research, Cloud Evolution: Mandate to Modernize, 85% of organizations will definitely or probably be partnering with more cloud providers than they currently work with, diversifying their cloud infrastructure across key players like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), Oracle and others. This diversification helps avoid vendor lock-in, allowing businesses to select the best options and tools tailored to their needs and optimize costs through competitive pricing and appropriate workload placements.
This shift in how cloud resources are deployed is a pivotal factor in ensuring AI and GenAI initiatives run effectively across different environments.
Transforming productivity and efficiency with GenAI
The adoption of AI technologies within hybrid cloud frameworks is transforming how organizations approach productivity and efficiency.
As Singh highlights, “When it comes to productivity and efficiency…AIOps has been delivering significant value…GenAI is now poised to take it to a very different level.”
The integration of GenAI brings cognitive capabilities to the forefront, enabling AI to manage a substantial portion of operational tasks autonomously. 20% to 30% of routine tasks in hybrid cloud management could be easily handled and executed much more efficiently by GenAI, according to Singh. As models continue to mature, the technology will take on even more complex tasks.
As the focus shifts from traditional IT management to cloud-based operations, organizations are also increasingly moving workloads to cloud.
In fact, HCLTech’s latest cloud research found that 87% of respondents agreed that many workloads currently run on-prem would benefit from being migrated to the cloud. This transition is not just about lifting and shifting data but involves optimizing operations to leverage AI-driven insights, improving business agility and enabling faster decision-making. With AI’s continued evolution, this transition promises to further augment the capabilities of cloud infrastructures, enhancing both productivity and operational efficiency.
Hybrid cloud strategies driving future business outcomes
Looking ahead, hybrid cloud strategies are increasingly seen as essential for realizing AI-driven business outcomes. The flexibility of hybrid cloud models supports companies in deploying AI wherever it provides the most value, adapting dynamically to changes in demand or operational needs. “Hybrid cloud would become an essential component in terms of driving AI for large enterprises…[it’s] critical for business to differentiate themselves in the marketplace,” explains Singh. Companies have limited options: to stay competitive, they must embrace AI or perish, and hybrid cloud is a critical enabler of this transformation.
This trend is supported by the broader multi-cloud shift. By leveraging multiple cloud providers and models, businesses can optimize performance, reduce risk and enhance resilience — key factors required for a successful AI deployment.
The importance of partnerships
To leverage hybrid cloud and AI solutions, many enterprises are turning to integrated offerings, such as HCLTech’s AI Force, which is enabled by our AI Labs and Cognitive Infrastructure Services as part of the AI Foundry suite can streamline AI deployment and maximize returns. This enables companies to not only adopt AI but also to ensure these investments provide continuous value. “We are providing end-to-end value propositions to the customers to harness value out of AI investments,” says Singh.
This approach also positions businesses to manage operational costs effectively, particularly as more IT budgets transition from capital expenditures to operational expenses. The need for expertise in financial operations (FinOps) becomes critical as organizations seek to forecast and optimize cloud resource utilization. Hybrid cloud solutions offer the agility required for this transition while enabling organizations to maintain flexibility across diverse cloud platforms.
Embrace a hybrid cloud strategy for a resilient AI future
Increasingly, a hybrid cloud approach is proving to be an essential component in scaling AI initiatives effectively, with a key role in sustaining innovation as AI technologies mature. With increasing cloud diversification and a shift toward more cloud-reliant operations, organizations must embrace hybrid cloud strategies to fully leverage the potential of AI.
