Cxo of the week: Sandeep Bhargava, SVP, Global Services and Solutions, Public Cloud Business Unit, Rackspace Technology

Rackspace Technology is an end-to-end, hybrid multi-cloud technology services company. We can design, build, and operate our customers’ cloud environments across all major technology platforms, irrespective of technology stack or deployment model. At every phase of their cloud journey, they collaborate closely with their customers, empowering them to modernize applications, develop new products, and embrace cutting-edge technologies.

Sandeep Bhargava, SVP, Global Services and Solutions, Public Cloud Business Unit, Rackspace Technology, Based in Singapore, Sandeep is responsible for business growth across the region and establishing strong local teams that deliver Fanatical Experience.

Passionate about customer success, he joined Rackspace Technology with over two decades of experience delivering financial and operational results throughout the region. Before joining the company, Sandeep was responsible for the graphic print operation across APJ for Hewlett-Packard. He has also served in various leadership roles with Hewlett Packard Enterprise, Dell EMC, and Procter & Gamble.

In an exclusive interview with Ciol, Sandeep Bhargava, Senior Vice President of Global Services and Solutions at Rackspace Technology's Public Cloud Business Unit, delves into the significant transformations observed in India's tech landscape throughout 2023. Additionally, he outlines the company's strategic plans for the upcoming year, 2024.

What notable transformations have we witnessed in the tech landscape in India in 2023, and what do you anticipate 2024 will bring?

Breakthroughs in cloud computing, artificial intelligence (AI), machine learning, and blockchain in the past year have enabled businesses to achieve greater efficiency, and agility, and be more data-driven. This has significantly offset economic headwinds, providing organisations with opportunities to create new avenues for growth, improve customer experiences, and enhance productivity.

In 2024, businesses need to continue down this path, particularly to minimise potentially acute supply chain and sustainability challenges. The latter will grow in importance next year, particularly with the growing urgency of the climate crisis.

2024 will also see generative AI carry over the momentum from the past year or so. Specifically, a perhaps overlooked aspect of this is how generative AI will transform robotics and automation. For example, generative AI can help robots learn from data and experience instead of purely on human instructions. This would allow robots to learn from how objects interact with each other through simulation, rather than just solely relying on pre-programmed instructions. As a result, robots can handle objects more quickly.

Meanwhile, generative AI's growth can be leveraged to help robots reproduce realistic images of their surroundings, thereby improving robot perception and navigation. These are just some examples of how generative AI could help realise immense productivity boosts, significant cost savings, and just enhance overall operational efficiency.

Generative AI will also play a major role in the continued rise in the importance of edge computing. With the exponential growth in data and the increasing need for real-time data processing, organisations will turn to edge computing for more applications. The convergence of the Internet of Things (IoT) and generative AI will empower organisations to gather, analyse, and act upon data at the edge for more and more use cases.

Lastly, generative AI will play an increasingly important role in cybersecurity in a continually evolving threat landscape. The technology will be vital to address cybersecurity concerns effectively through advanced threat detection systems and encryption technologies.

Could you elaborate on the growing emphasis on GenAI and how you foresee its application in future industries?

Many discussions on generative AI focus on content creation, such as text, visuals, audio, and even entire lines of code. However, generative AI has applications that extend beyond content generation. 

For example, the healthcare sector would greatly benefit from generative AI-powered chatbots that can comprehend patient inquiries in natural language and make accurate, relevant responses. However, the ability of generative AI to identify patterns in massive amounts of data and make inferences would have its most dramatic impact on applications such as the diagnosis of existing and future diseases. 

The telecommunications industry can also benefit from generative AI by integrating it into network management, enabling customer service teams to provide better technical support and simplify billing and account management processes.

Generative AI can also transform the automotive sector by assisting with complex maintenance and repair tasks in modern vehicles. By meticulously analysing blueprints of individual vehicles, generative AI can offer detailed insights, enabling enhanced vehicle management and streamlining automotive services.

Similarly, generative AI can handle the exponentially growing amounts of data in the financial services sector to generate better insights, improve financial analysis processes, and enhance investment decision-making. Financial institutions can also deliver hyper-personalised investment recommendations to customers, engendering better financial outcomes while improving customer satisfaction.

What measures and strategies do you think will be crucial for ensuring robust cybersecurity in the coming year?

First, it is imperative to thoroughly understand your current cloud security posture to effectively address potential gaps and reduce threat risks. Managed services providers can be leveraged to provide expert design and implementation recommendations that give insight into the strengths and weaknesses of an enterprise's security operation. By identifying these gaps, organisations can then take proactive steps to strengthen their defences and mitigate potential threats.

Second, the ever-evolving cybersecurity landscape demands the proper management of risks and compliance. This involves assessing one's compliance posture and identifying any deviations from recognised regulations and industry standards. By building a plan to achieve and maintain compliance, organisations can then establish a robust framework that shields them from the potential consequences of non-compliance.

Third, incorporating security and privacy into an organisation's architecture is critical in reducing the likelihood of vulnerabilities being exploited. Many organisations do not have the resources to staff senior security executives and technical roles, making it essential to provide technical support and guidance to these teams. This ensures that security considerations are infused into all stages of development and implementation, providing a strong foundation for cybersecurity.

Lastly, enhancing cyber defences requires a proactive approach. Offensive security measures involve actively searching for vulnerabilities, assessing the potential impact of a cyberattack, and providing assurance for your digital estate. Regular assessments and penetration testing can uncover vulnerabilities, allowing businesses to take mitigating actions to protect their systems and sensitive data.

Which industry verticals do you see as early adopters of Generative AI powered by the Public Cloud?

Healthcare organisations have traditionally lagged when it comes to adopting new technologies, leading to challenges such as data silos, interoperability issues, and manual processes. But more and more organisations have been leveraging AI, and with each successful use case, more are emboldened to either start their own AI journeys or embrace the next step by adopting generative AI. 

However, it is important to recognise that the applicability of emerging technologies like AI can vary depending on the context. For academic medical institutions, certain priorities may differ from those of large health systems focused on revenue management and cash flow cycles. Each organisation should carefully assess the specific advantages generative AI can offer and how it aligns with its goals and needs.

Manufacturers, on the other hand, already have opportunities to experiment with generative AI and develop use cases for their industry. The functionality of generative AI can be explored in various areas within a manufacturing environment.

For example, generative AI can be used to analyse unstructured data, such as documentation or standard operating procedures (SOPs) that have been in place in factories for years. When faced with a specific situation in the factory, AI can quickly access and analyse relevant documents to provide an accurate answer or recommendation. This functionality is already available and presents an exciting opportunity for manufacturers to explore the potential of generative AI.

Are there best practices or examples you can share regarding successful AI integration without significant disruption?

When it comes to successfully integrating AI without significant disruption, organisations must first ask themselves what problems they are aiming to solve. This allows them to identify specific areas in which artificial intelligence can be effectively utilised. After identifying these areas, organisations should then evaluate their existing decision-making processes and gather all the necessary data required to meet their objectives.

A crucial step in AI integration is the creation of a proof-of-concept (POC). By focusing on a single use case, organisations can develop a deep understanding of the applicability of AI and machine learning to their specific business. Defining the requirements and desired outcomes before proceeding with the POC allows for a clear direction and aids in highlighting the potential benefits of the solution. Implementing the POC model and showcasing its business value provides tangible evidence of the benefits that AI integration can bring, ultimately garnering support and buy-in from stakeholders.

For organisations that are just beginning their journey in AI and machine learning, leveraging ready-made tools and managed services providers can significantly expedite the adoption process. These tools and services are specifically designed to streamline the integration of AI and machine learning, making it more accessible for organisations of varying sizes and levels of technical expertise.

What emerging trends and strategies do you foresee in the realms of data and cloud for businesses in 2024? 

This year will see a continued focus on democratisation and sustainability, as well as significant advancements as industry-specific cloud platforms emerge. The latter will combine the capabilities of cloud computing and package them in a way that makes it easier for industries to consume solutions within specific regulatory and other constraints, enabling industries to fully leverage the benefits of cloud computing while addressing their unique requirements.

Sustainability will be another key focus in the data and cloud landscape as soaring demand for computing and storage power is expected to affect carbon emissions levels. Various initiatives across the industry are already underway and we can expect more in years to come. This is also inspiring many cloud services providers to develop digital solutions that enable Environmental, Social, and Governance (ESG) outcomes for companies. 

The rise of industry-specific platforms and digital solutions for ESG outcomes will create greater pressure for enterprises to migrate to the cloud for fear of being left behind by the competition. But at the same time, the challenging economic situation of 2024 will also bring pressure on decision-makers and business leaders to justify greater spending on IT.

This will translate to more organisations leveraging managed cloud services to effectively migrate to the cloud while demonstrating cost efficiency. By utilising the infrastructure and expertise of managed service providers, businesses can become cloud-ready in a fraction of the usual time while avoiding the huge expense of setting up their own infrastructure and recruiting talent.