By Veda Iyer
The rapid and remarkable progression of cloud technology in a relatively short timeframe has empowered enterprises to match its pace of innovation. A recent survey conducted by McKinsey revealed that cloud adoption accelerated during the COVID-19 pandemic. Another survey by Gartner predicts that by 2026, 75% of organizations will look to adopt a digital transformation model with cloud as the underlying platform. This serves as compelling evidence for Indian enterprises transitioning from experimental stages to the formal implementation of hybrid and multi-cloud solutions.
Notably, startups and fintech firms are spearheading this expeditious adoption, recognizing the technology’s potential to confer a competitive advantage and enable seamless integration within the global cloud ecosystem. According to the latest Future of Cloud survey by Deloitte, 90% of companies see cloud technology as essential for growth, digital transformation and competitiveness in the marketplace.
Today, as the banking sector consistently attempts to adapt to new technologies, the emergence of another groundbreaking innovation, Generative AI, has opened up a substantial opportunity to redefine the approaches connected to cloud migration strategies and customer experience transformation. The introduction of this technology has incited a competitive atmosphere among enterprises, each aspiring for innovation. Amidst this enthusiasm, businesses must approach the adoption of generative AI with due consideration, steering clear of impulsive participation in the prevalent trend of widespread utilization. Consequently, enterprises need to evaluate the specific needs and potential applications of generative AI within their distinct workflows, thereby ensuring the optimal utilization of the evolving capabilities inherent in this technology.
With that in mind, let us delve into how these two revolutionary technologies are mutually enhancing each other, spearheading the journey into the next era of innovation and legacy creation.
Enhancing Generative AI through Cloud Integration:
The partnership between Generative AI (Gen AI) and cloud computing is expected to be a fundamental factor in facilitating a seamless transition, while simultaneously enabling organizations to strengthen their abilities in important areas like fraud detection, data security, and robust disaster recovery, especially in sectors such as BFSI. In addition to this, cloud services offer readily available pre-trained Application Programming Interfaces (APIs) and foundational models, allowing organizations to work with greater efficiency without the need to initiate projects from scratch. This advantage gives enterprises an upper hand when incorporating generative AI into their applications, streamlining the development process.
Take, for instance, the case of ‘OmniAI,’ an AI and cloud-powered platform developed by a multinational financial services firm in 2019. This project, which is operational even today, is dedicated to speeding up the use of AI in their operations by expanding AI and machine learning applications using their in-house innovations. What makes OmniAI remarkable is its strong reliance on cloud technology, mainly due to the cloud’s inherent flexibility and capability to manage vast and complex datasets. This enables them to use AI on a large scale while maintaining the necessary security and controls for handling highly sensitive data.
Optimizing Cloud Resource Usage with Generative AI:
To re-iterate, the connection between these two technologies is not one-sided. Gen AI offers a range of advantages to the cloud environment, including optimizing cloud operations, data mining, cost reduction, and security automation. Furthermore, it can forecast future infrastructure needs and autonomously allocate or deallocate resources accordingly.
Consider the notable example of India’s largest private sector bank, which, earlier this year, unveiled a strategic partnership with Microsoft Azure’s cloud platform. This collaboration aims to leverage services such as Microsoft Power Platform and Microsoft 365 as integral components of its ongoing digital transformation initiatives. The primary objective is to enhance the bank’s information management capabilities significantly, employing advanced artificial intelligence (AI) for robust analytics. This partnership extends beyond the goal of constructing a bank for the future; it aspires to deliver a neo-banking experience, aligning with the evolving expectations and preferences of the customers.
Generative AI additionally can forecast variations in demand for distinct banking services like mobile and online banking. Using these forecasts, banks can intelligently adjust their cloud resources to match the expected demand, thus preventing excessive or insufficient resource allocation. This strategic management of resources not only optimizes operational efficiency but also leads to cost savings in the realm of cloud computing expenditures for banks.
Democratization of innovative technologies:
As we discussed the synergistic relationship between Generative AI and cloud technology, it becomes evident that this alliance is ushering in a significant shift in how the banking industry approaches innovation and efficiency. It is worth highlighting the role AI plays in making advanced cloud computing more accessible. The emergence of cloud-based AI services has greatly simplified the process of acquiring and utilizing AI technologies.
In simpler terms, AI is no longer an exclusive domain limited to a select few; it has become readily available across various sectors, requiring only minimal technical expertise for implementation. This democratization of AI serves as a vital catalyst for digital transformation, fueling innovation, efficiency, and growth within enterprises.
Even as the growing accessibility of AI empowers cloud-computing environments, one must also be cautious of over-reliance and limitations of machine learning systems. Despite extensive development in AI, and data-driven decision-making creating faster processing, there is still a need for human-discernment in certain situations. Data security is another area where the two technologies can enhance their productivity but enterprises need to ensure strong data protection given the significant amounts of information that is used across cloud networks and ML tools.
With these transformative technologies seamlessly converging, businesses are set to embark on a transformational journey with boundless possibilities. We are on the verge of a new era where the collaboration between cloud and AI is set to create innovative legacies that redefine the industry.
The author is global chief marketing officer, head hyperscalers and strategic partnerships, head sales– APAC,Mphasis
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