Why businesses must embrace hybrid multicloud to supercharge GenAI

The incorporation of Generative Artificial Intelligence (GenAI) in the business realm is transforming workflows and unveiling numerous opportunities for rapid innovation and substantial growth. Numerous use cases are emerging, particularly in customer service, document search and analysis, fraud detection, and co-piloting, significantly boosting productivity levels. According to International Data Corporation (IDC), AI and GenAI adoption in India significantly increased, with spending projected to reach $6 billion by 2027 and a compound annual growth rate (CAGR) of 33.7% for the period 2022-2027.

While recognising the advantages of AI, businesses are also conscious of the associated risks and the significant upfront costs for training the models. Therefore, businesses need to meticulously evaluate various aspects, including the financial viability of incorporating GenAI into their workflows, to ensure it fits within their budget and meets their goals.   

The scarcity of AI talent also poses a significant hurdle, requiring companies to invest in training, educational collaborations, and to create a culture of continuous learning to meet the demand for skilled professionals. Addressing these challenges is paramount for businesses aiming to harness the full potential of GenAI.

But there is a solution to address these challenges.

Why a hybrid, multicloud approach matters for GenAI

In the evolving and dynamic technological landscape, the implementation of GenAI is being characterised by vast data and intricate solutions with dependencies on multiple clouds and architectures that enable an organisation's ability to be agile while also being efficient in how they innovate.

A hybrid multicloud architecture that includes the edge, private, and public clouds can significantly mitigate risk, enhance performance, and drive innovation for enterprises seeking to leverage GenAI. Businesses are increasingly opting for hybrid cloud solutions as a balanced approach, combining the advantages of both public and private clouds. Their primary strength lies in offering the security typical of private clouds while benefiting from the scalability found in public ones. Significantly, a recent EY-FICCI cloud report, titled "India's Cloud and Data Revolution: From Adoption to Enabling Innovation, states that as much as 78% of organisations have actively adopted cloud strategies to modernise tech stacks and infuse intelligence into their apps and that two out of every five organisations have opted for a hybrid approach. 

Recent statistics show that a hybrid cloud strategy yields 2.5 times more commercial value, underscoring its effectiveness. Larger firms are notably attracted to this model, with 56% having embraced it. Additionally, 70% of IT leaders deem a strong hybrid cloud strategy essential for achieving full digital transformation. 

A hybrid multicloud approach can also enhance cost-effectiveness for GenAI deployments by allowing companies to select services from different public cloud providers based on specific requirements. This flexibility optimises costs, mitigates vendor lock-in, and enables more favorable pricing negotiations. According to a study, businesses that adopt a hybrid multicloud strategy can achieve up to a 30% reduction in overall cloud expenditure due to the ability to leverage competitive pricing and avoid over-provisioning resources.

In the face of the scarcity of AI talent, elevating the skills of current employees is paramount for the successful implementation of GenAI. A hybrid multicloud platform, predicated on a standardised and non-specialised infrastructure, can provide access to a diverse talent pool across various disciplines. Effective collaboration that focuses on every facet of where applications and data are deployed not only enhances technology implementation but also ensures continual support, training, and alignment with business objectives.

Data from recent studies indicate that organisations adopting a hybrid multicloud strategy experience an increase in system reliability and a reduction in operational costs. The integration of edge computing and advanced analytics into this framework further bolsters performance and scalability.

Understanding business priorities

As businesses prioritise GenAI, they will look for solutions that simplify adoption and deployment. One thing is clear — businesses are more likely to purchase existing AI GPT models (large language models, LLMs) or leverage existing open-source AI models rather than train their own proprietary AI models. 

More than cost, what is imperative to businesses running GenAI is data security and governance, including data quality and data protection. This means most businesses will prefer to use existing foundational generative AI models and adapt and fine-tune these to their own needs, such that their private, proprietary data stays within their control regardless of where their GenAI applications run. 

Making the right choice

Businesses opting for a hybrid multicloud approach should craft it as a deliberate, strategic service where every feature contributes value based on the company’s needs. The cloud era isn't on its way; it has already arrived, transforming the landscape of business, technology, and innovation. As companies prioritise developing cloud-native applications and strategies, it’s imperative to adapt, evolve, and thrive in this boundless digital realm. 

Faiz Shakir

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Faiz Shakir is VP & Managing Director - Sales, Southern Asia at Nutanix.