“Cloud is not inherently vulnerable”

Data gravity, the ability of data to attract additional data, applications and services as the data sets grow, requires the flexibility of Cloud.

Shubhendu Parth
New Update
Siki Giunta

A seasoned executive with over 20 years of experience in international operations, marketing and sales, Siki Giunta leads CloudSMART Business, Industry Cloud and the Google Ecosystem Business at HCL Tech. In an interaction with Shubhendu Parth, she talks about the technologies driving Cloud, challenges of Network Cloudification, security issues, and the impact of Cloud operating models and data engineering on generative AI. Excerpts:


How is the industry Cloud evolving and what are the key technologies driving the trend?

Cloud is evolving to become the optimal business platform for companies that are transforming to grow at scale. Each industry, be it life sciences, retail, manufacturing, financial services, or media, has its drivers but the one thing that every industry has in common is the need for speed. Accelerated response to compelling events, whether they are global like a pandemic or unique to a business like a competitive threat, is a requirement for businesses to act quickly.

"More agile, cost-effective and adaptable networks are fundamental to successful Cloud initiatives."


To succeed, to achieve desirable business outcomes, organisations are prioritising the ability to analyse the volumes of collected data, use analytics to discover insights and then apply these constantly changing insights to innovate and drive profits – we say to supercharge progress by making innovation a habit.

We live in a “5-star culture” – the impact of social media and the ever-present opportunity for customers, patients, and partners to rate a company or a product creates pressure to improve services and products. Success requires innovative technology that is dependent on using the Cloud as a business platform.

What are the top workload requirements that are driving the adoption of the Cloud by businesses beyond the hygiene remote working and integrated communication needs?


Each industry is unique, but the drivers are consistent: increase the productivity of knowledge workers, improve price-performance ratios, deepen customer engagement, and streamline processes. From a technology perspective, 5G is estimated to be a USD 12 trillion market. 5G smartphone subscriptions are likely to reach 3 billion in 2026. 5G brings innovation and dramatic transformation to how we live and work having 10-20 times higher data speeds with greater device connectivity. It is also essential to realise smart cities, smart hospitals, smart manufacturing and more.

Another trend is Generative AI (GenAI). Even school children are aware of ChatGPT and similar technology for the consumer market. Our clients are interested in the enterprise adoption of GenAI. We are engaged in many projects from consumer safety to clinical trials to investor portfolio management. Our clients and HCL Tech are concerned with ethical use and related security and compliance issues.

Taming the tsunami of data is a powerful trend for every business. Here we see data gravity propelling successful GenAI initiatives. Many companies and service providers are improving skills in developing large language models (LLMs) but data gravity is the necessary ingredient in the GenAI recipe for success.


What are the primary obstacles stopping faster adoption and utilization of Cloud technology and what can businesses do to overcome it?

Cloud adoption is happening very quickly in many industries in most regions of the world. We are partners with all the hyperscalers, and they are seeing an increase in the number of new customers and continued subscriptions from existing customers. But I think there are situations where businesses hit a wall. First, IT may lose sight of the strategic intent driving the move to the Cloud. Second, technology adoption requires an experienced team and while their workforce may have the technical training, they may not have the experience. Third, ever-changing business requirements create the need for continuous modernisation and previous decisions have sometimes left businesses with technical debt – depressing the appetite for innovation.

If organisations neglect to tie Cloud deployments to business outcomes, migrations can fail to return measurable value and workloads may end up back on-prem.


Our research indicates that the collaboration between IT and the business is not happening consistently which makes it difficult for leadership to stay the course. Businesses may sometimes also have to deal with unexpected costs of Cloud and organisations may not always have experienced financial operations – Finops – to optimise their Cloud spend.

My advice to these companies will be to find a trusted partner who can help them stay on the course and engage business and IT leadership together to extract all the value from the move to the Cloud.

Recent digitalization efforts have seen organizations shifting network functions from traditional hardware-based systems to software-based ones. What challenges does Network Cloudification bring with it?


Network cloudification, also referred to as network function virtualization is the process of transforming traditional network infrastructure into more agile, Cloud-based solutions. This represents a shift in how network services are designed, deployed, and managed.

The CloudSMART SMART Ways, Connected Cloud and Secure Cloud, focus on security and compliance and provides guidance and services to protect users, consumers and partners when doing business in the Cloud. The goal of network cloudification aligns with the modernisation of applications and data. More agile, cost-effective and adaptable networks are fundamental to successful Cloud initiatives.

What about the security challenges that the Cloud environment brings in?


Indeed, people and companies in early-stage Cloud adoption often express security concerns. Cloud is not inherently vulnerable. The network considerations for accessing the Cloud have matured and are less reliant on hardware to manage access with user access managed by sophisticated multi-authentication protocols and digital IDs. Today, we secure applications by authenticating user access. In general, security depends on how well systems are implemented, configured, and managed – whether it is a legacy or Cloud implementation. We take security very seriously and find clients appreciate our approach to security and compliance. We believe that properly configured and managed Cloud solutions can be as secure.

A recent HCL Tech report indicates that 24% of organizations are considering repatriation due to a lack of optimization of workload. What steps should businesses take to become Cloud-native?

When organizations neglect to tie Cloud deployments to business outcomes, migrations sometimes fail to return measurable value and workloads may end up back on-prem. Often, organizations think about how to get to the Cloud but overlook the required operational know-how to securely operate in the Cloud. The second reason for repatriation is the expectation that Cloud costs less. The cost of the Cloud is relative to how the applications are implemented, how resources are being used, and the ability of the company to make sense of different pricing scenarios.

Avoiding repatriation requires leadership to define the relationship between the Cloud project and the strategic intent of the business. For example, if the strategic intent is to improve customer service, the decision to repatriate may delay the business outcome and cost the company profits over time. Having a financial plan for the Cloud is important.

How does advancement in Cloud operating model and data engineering underscore the success of generative AI?

The Cloud operating model is essential for many reasons, but fundamentally Cloud provides scalability, accessibility, and elasticity to enable generative AI. GenAI models are computationally intensive and require processing power and memory and Cloud can scale up or down as needed, which is important for training models. The GenAI models are hosted in the Cloud and are accessible with APIs. The accessibility of the Cloud makes it easier for developers to integrate generative AI into applications. Cloud also offers elasticity – the ability to allocate resources dynamically and this is essential for handling spikes in demand as GenAI applications find their way into the mainstream.

GenAI models require massive processing power and memory and Cloud can scale up or down as needed, which is important for training models.

The success of a project that incorporates GenAI is largely dependent on data engineering – the ingestion, storage of the data and data quality and validation. Data gravity, the ability of data to attract additional data, applications and services as the data sets grow, requires the flexibility of Cloud. Language models prompting the data are most effective when the data sets are vibrant and robust.

What is HCL Tech doing in the Cloud space and Generative AI?

As an IT services company, HCL Tech collaborates with clients on a variety of projects. Our job is to advise them and ensure the underlying Cloud platform – the data, governance, and security – is accessible and secure to support GenAI initiatives. For example, we have deep expertise in Integrated Management Systems. GenAI can improve how organisations integrate all current systems in one place within an organisation to prevent unforeseen conflicts between systems and enable them to work as a whole, boosting efficiency and productivity.

Engineering is in the DNA of HCL Tech. We are working on the best ways to use GenAI for code generation. There are already commercial implementations like GitHub CoPilot, Google CodeGen, or Generative AppBuilder. These will generate the scaffolding. We see a different role for HCL Tech. While GenAI will generate a lot of code you still need to validate the code before it is deployed into production. Trusted application development must meet the business requirements and identify bugs. Our engineers are automating the inspection of GenAI-generated code and how to accelerate testing and apply modifications with its help.

What investments is HCL Technologies making in building GenAl capabilities and strengthening Cloud technology?

We have built on our model – the HCLTech Cloud Native Labs – and will be offering a Lab just like it specifically geared to GenAI knowledge transfer and hands-on learning for clients. The Lab experience surrounds the client with our best people and the processes enabling clients to generate LLMs, core to GenAI, and other sessions that underscore the importance and operation of data engineering. Data engineering is critical for successful generative AI projects.

We are investing in our people by working with our global ecosystem of partners to train and certify our engineers on modern generative AI tools and processes. We have many examples of successful GenAI projects today.

Telcos are both users and drivers of the Cloud. What solution does HCL Technologies have to support the TSPs?

Telcos drive Cloud adoption through initiatives such as OSS, BSS modernization, NFV, 5G, MEC and IT-OT convergence, which rely heavily on Cloud infrastructure provided through AWS, Microsoft, and Google as well as traditional technology OEM partners. The CloudSMART SMART Way – Connected Cloud – provides the platform and ideal ecosystem that partners require to operate these technologies. Enabling Cloud-native transformation for the internal IT OSS/BSS transformation services will optimize their operations and improve their abilities. IT services are complemented by business services and services like 5G, Edge and IT/OT converge to leverage Cloud, Edge, and advanced analytic use cases.