The massive volumes of data from diverse sources needed to train GenAI require a revamp of cloud and data infrastructure. Trust is key to such a modern infrastructure.
Generative AI (GenAI) promises a future brimming with possibilities, with McKinsey estimating it could contribute an annual value ranging from US$2.6 trillion to US$4.4 trillion across various industries worldwide.
But amid the excitement lies a crucial question: how do we separate hype from reality? The answer, according to Cloudera, lies in two key ingredients: trusted data and a robust cloud infrastructure.
DigiconAsia finds out more from Remus Lim, Senior Vice President, Asia Pacific and Japan, Cloudera.
What elements of digital technology are making GenAI a reality for businesses today? Why?
Remus Lim (RL): Implementing a modern data architecture and ensuring data is trusted and reliable are some of the most important elements necessary to turn generative AI (GenAI) into tangible business results.
As massive volumes of diverse data are crucial to train GenAI models effectively, a modern data architecture is necessary. Such infrastructure facilitates real-time data processing and secure storage across hybrid and multi-cloud environments, giving businesses access to all of their data so that this can be organized, stored, and analyzed in a structured, secure, and governed manner. This creates a foundation for powerful analytics, machine learning, and ultimately, GenAI applications across the organization.
Beyond data volume, data quality and trust are also crucial for GenAI adoption. Privacy, compliance, and ethical considerations are essential to ensuring reliable and unbiased results. By prioritizing data governance and security, businesses can leverage GenAI with confidence, extracting valuable and reliable insights for better data-driven decision-making.
How should organizations in Asia Pacific navigate the challenges and opportunities GenAI adoption poses in the cloud, especially from a data governance and security perspective?
RL: Globally, companies are struggling with the challenge of how to use all of their data to help them run their businesses better, and APAC organizations are no exception. With more data than ever before and new data sources emerging, significant amounts of critical information are dispersed and siloed, resulting in data that businesses cannot trust or derive meaningful insights from in a timely manner.
Today, we find GenAI mostly in generic applications that can run on general purpose data available in the cloud. While valuable, the real high impact use cases for GenAI require us to trust our most secure, sensitive, and valuable data to these AI models.
Embracing a hybrid cloud approach is therefore a strategic and cost-effective solution to overcome potential data sprawl and leverage any deployment. Organizations can harness the flexibility and scalability of the public cloud as well as the security and control from on-premise data centers to manage their data. Ensuring openness and interoperability are also crucial elements needed to bridge the gap between on-premises and cloud data sources. This paves the way for seamless integration across all data to accelerate GenAI adoption across the enterprise.
However, infrastructure alone is the tip of the iceberg. Building a robust data culture is paramount, and this should start from the top. A study by Bain & Company discovered that 60% of companies see Gen AI as a top three priority over the next 2 years, but only 35% have a clearly defined vision for how they create business value from Gen AI.
Company leadership needs to set the tone in fostering a culture where data is valued and consistently used to inform business decisions. This ensures data becomes a strategic asset and encourages employees at all levels to readily access and utilize data effectively.
Please share some real-world examples of how trusted data and cloud infrastructure are fueling GenAI innovation in the region.
RL: Since trusted data and secure data infrastructure are the cornerstones of the GenAI revolution, leveraging this technology can lead to streamlined operations, enhanced risk management, and greater customer satisfaction — giving organizations a more competitive edge.
This is exemplified in Cloudera’s partnership with three leading banks across Singapore and Indonesia: OCBC Bank, PT Bank OCBC NISP, and Bank Negara Indonesia.
- OCBC also sought Cloudera to leverage GenAI for a more personalized banking experience. They created a hybrid cloud solution that seamlessly integrated with existing data sources and empowered data scientists to work independently. OCBC’s customers received personalized recommendations and insights through the mobile banking app (“Next Best Conversation”). This led to improved financial management and time-saving features like chatbots handling customer interactions. The bank itself achieved increased customer engagement, improved operational efficiency, and mitigated the risk of data loss.
- PT Bank OCBC NISP worked with Cloudera to achieve their vision of becoming a digital-first bank. Our solution provided a platform for stronger collaboration between data scientists and business users, allowing them to develop AI models and deliver real-time, personalized recommendations to customers. By establishing a strong foundation for AI integration, PT Bank OCBC NISP is now better equipped to enhance customer experience, improve efficiency, and strengthen regulatory reporting.
- Bank Negara Indonesia (BNI), Indonesia’s largest state-owned bank, is on a similar journey. To unlock the potential of GenAI for enhanced services, BNI is among the first to trial Cloudera’s AI Inference service, enabling efficient deployment and management of large-scale AI models. This collaboration is expected to lead to a more personalized and efficient banking experience for customers, potentially including features like knowledge-based co-pilots for BNI employees. The bank itself anticipates increased operational efficiency, improved credit mechanisms, and a stronger market presence through innovative GenAI-powered services.
These examples demonstrate GenAI’s ability to improve internal operations and deliver better customer experiences.
How do you see the future of GenAI developing in the region, and how will it transform data-driven organizations leveraging the cloud?
RL: There are high levels of GenAI enthusiasm across various industries in APAC, with companies moving beyond hype to focus on data-driven value creation. Our whitepaper shows 57% of surveyed APAC organizations are already early AI adopters, highlighting a strong foundation for future GenAI growth.
This enthusiasm translates to real-world applications, like the way companies leverage GenAI for tasks like chatbots and code generation. These are areas where Cloudera’s GenAI-focused Advanced Machine Learning Packages (AMPs) that integrate Large Language Models (LLMs) enable one click deployment of customizable AI projects to decrease time to value and transform models into unique assets for the organization.
Furthermore, GenAI is set to democratize AI usage across organizations, benefiting every employee whether they are data scientists or business analysts. To boost the accessibility of GenAI, Cloudera recently launched three new AI Assistants, each used to simplify complex tasks.
Looking ahead, we believe AI will move from conversation to consultation, acting as a professional consultant to iteratively refine answers and results until they are a perfect fit for each unique interaction. GenAI will also transition to a “concierge experience,” tailoring content and offerings to each customer.
To turn this prediction into reality, organizations need a secure and trusted data foundation. Here’s where Cloudera comes in – we’re committed to providing secure, data governance tools that empower organizations to harness the full potential of GenAI.
