Home » Exclusives » GenAI capabilities enhance efficiency and effectiveness throughout the cloud implementation process: Anant Adya, EVP & Service Offering Head, Infosys
Infosys stands as a beacon of innovation and excellence, driving digital transformation for clients across the globe. At the helm of this renowned organisation is Anant Adya, the Executive Vice President and Service Offering Head, whose leadership has been instrumental in steering Infosys towards new heights of success.
In this interview, Adya sheds light on how Infosys Cobalt approaches modernising the data landscape in multi-cloud environments, exemplifying the symbiotic relationship between cloud computing and AI across industries such as healthcare, finance, manufacturing, and retail. He delves into the key benefits of a seamless and agile enterprise infrastructure on the cloud, underscoring its pivotal role in navigating today’s dynamic marketplace.
How does Infosys Cobalt approach the modernisation of the data landscape in the context of multi-cloud environments?
Many companies struggle to manage multi-cloud environments effectively. They often treat each cloud implementation separately instead of integrating them. This means that specific workloads or departments are deployed on specific clouds, making their overall landscape multi-cloud. The same goes for their data landscape. Before modernising the data landscape to enable multi-cloud deployments, it’s important to ask whether it’s necessary for the business to do so. Based on client strategies and requirements, there isn’t a need to do so. However, there’s always a good use case and benefit to making data landscapes multi-cloud. This applies to data landscapes and to all workloads deployed on the cloud.
Can you provide examples of how the intersection of cloud computing and artificial intelligence is being applied across different industries, such as healthcare, finance, manufacturing, and retail?
Cloud computing and artificial intelligence are two transformative technologies rapidly changing the landscape across industries. These technologies, when combined, operate in a symbiotic relationship, unlocking unprecedented possibilities. The cloud’s vast computing resources and data accessibility empower AI algorithms to learn, analyse, and generate insights at a scale once unimaginable. Here are some examples of how these technologies are being used in various industries: in healthcare, cloud-based systems analyse patient data, such as X-rays and scans, using AI algorithms to detect diseases like cancer at early stages, which improves accuracy and enables timely intervention. In finance, AI algorithms on cloud platforms scan large financial transactions in real time, identifying suspicious patterns and flagging potential fraud attempts before losses occur. In manufacturing, cloud-based AI analyses sensor data from machines to predict equipment failures before they happen. This helps in preventing costly downtime and optimising maintenance schedules. In retail, AI on cloud platforms analyses customer purchase history and browsing behaviour to recommend products and promotions, increasing customer satisfaction and sales.
In the current business landscape, what are the key benefits that organisations can derive from having a seamless and agile enterprise infrastructure on the cloud?
In today’s business landscape, marked by rising inflation, geopolitical tensions, and a dynamic economic environment, organisations of all sizes face unique challenges that demand a strategic approach emphasising adaptability and resilience. In this regard, a seamless and agile cloud enterprise infrastructure can provide immense value. The cloud’s flexibility allows organisations to optimise IT spending, scaling resources up or down based on real-time needs. This is crucial in fluctuating demand and potential economic downturns, enabling businesses to avoid unnecessary costs and maintain financial agility. The cloud’s robust security protocols and disaster recovery solutions also offer improved risk management and continuity, mitigating risks associated with data breaches and unforeseen disruptions. This ensures business continuity despite external challenges, safeguarding valuable assets and enabling uninterrupted operations. Moreover, the cloud empowers organisations to transform data into actionable insights. Powerful analytics platforms reveal hidden trends and patterns, allowing businesses to make informed decisions in the face of economic uncertainty. This data-driven approach can inform strategic planning, resource allocation, and market response strategies.
How is Infosys exploring the use of generative AI to augment and improve cloud capabilities?
Infosys is utilising GenAI capabilities in all stages of cloud implementations, including CloudOps, FinOps, designing and deploying cloud foundations, and creating automation scripts. GenAI capabilities enhance efficiency and effectiveness throughout the cloud implementation process.
How do you believe the adoption of cloud computing and AI impacts the competitiveness of businesses in today’s dynamic marketplace?
The convergence of cloud computing and AI is transforming the competitive landscape, providing businesses with a potent combination of agility, intelligence, and efficiency. The scalability of cloud computing allows enterprises to adjust resources in real-time, responding quickly to market trends and customer needs. AI-driven insights further refine strategies and optimise operations, positioning organisations for success. Cloud accessibility provides smaller businesses access to sophisticated AI tools, fostering a vibrant ecosystem of innovation that promotes healthy competition. AI-powered personalisation on the cloud platform empowers businesses to customise products, services, and interactions to individual customer preferences. This fosters loyalty and deepens engagement with customers. AI automates repetitive tasks and streamlines workflows, freeing up valuable human resources for strategic initiatives. Cloud infrastructure reduces costs and boosts productivity. AI analyses vast datasets on the cloud, revealing hidden patterns and insights that inform smarter decision-making and unlock new business opportunities.
As organisations increasingly adopt cloud and AI solutions, what challenges do they commonly face, and how can these challenges be effectively addressed?
The current business landscape is experiencing a transformational shift due to the convergence of cloud computing and artificial intelligence. This powerful combination of technologies empowers organisations to achieve exceptional agility, intelligence, and efficiency, providing them with a competitive advantage in today’s dynamic marketplace. However, implementing and managing complex cloud and AI solutions requires specialised expertise, and it comes with several challenges, such as data security and privacy, integrating new technologies with legacy infrastructure, cost and return on investment (ROI) concerns, and resistance to change from employees. Organisations can partner with experienced cloud and AI service providers who offer expertise, resources, and best practices to address these challenges. They can also leverage open-source platforms for cost-effective access to advanced capabilities while maintaining flexibility and control. It is recommended to start with small-scale pilot projects to test the waters, identify potential challenges, and refine the approach before full-scale implementation. Ongoing training and updating on the latest advancements in these technologies are essential to ensure successful cloud and AI adoption.
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Sayantan is a Correspondent at Express Computer and CRN India, The Indian Express Group. His interest lies in technology and innovation across all industries. Sayantan holds a Masters degree in Media and International Conflicts from University College Dublin, Dublin, Ireland and a Bachelors degree in Journalism and Mass Communication from Amity University Kolkata, Kolkata, India.