Impact of GenAI Technology on Data Management Frameworks

Ashish engaged in a conversation with the Asia Business Outlook magazine in order to answer queries on how GenAI technologies are bringing about a transformation in the data management sector. He elaborated how the combination of cloud solutions and GenAI are making data management easier for organizations across the world. Currently he is working as VP products for Oracle and his responsibilities include defining and driving product strategies, corralling requirements and framing roadmap based on market/business demands, articulating product positioning and value proposition, launching and evangelizing products and cloud services that solve complex enterprise problems, building and managing cross-functional teams and strategic partnerships.

What is your advice on how businesses can optimize their architectures to mitigate data governance complexities when integrating Generative AI and Cloud computing into data management workflows?

When one looks at data governance, harmonization is required across multiple systems through a very collaborative process. It should involve the latest business friction and the lowest latency. This is the reason why we cannot have data alliance or multiple compute frameworks. One will not be able to extract value from business data by following this process especially with modern GenAI initiatives. What is generally advised to customers is to streamline all the segments like data inject, data access, data processing, data storing and one of the best ways to do that is converge data management that eliminates the complexities of data fragmentation. It can also be done by increased automation in cloud deployment which eliminates all kinds of complexities associated with manual tasks.

While integrating Generative AI with cloud-based systems, companies also need to make adjustments to ensure the data is AI-ready. How are solution providers supporting customers in navigating this?

How to mitigate the threats arising in the segment of cybersecurity is one of the top concerns for CIOs today. At the end of the day, what these threats are targeting are essentially the data sets that are utterly crucial for any modern enterprise. One essential criterion for providing these solutions is that the data sets needs to be completely encrypted. But there are other architecture frameworks that are associated with the data encryption. All of these aspects are part of something that is called the maximum security architecture that is part and parcel of the data solutions portfolio of any given provider. 

How Generative AI systems and technologies are helping customers modernize their data and incorporate the perfect framework for data management?

In the last few years, there have been a lot of IT innovations which have made the industry more productive. This productivity can be demonstrated through various business applications. These productivity gains flows from the solution providers to the end users. However, adapting every innovation cannot be disruptive and the same thing is applicable for GenAI. In other words, the embracing GenAI needs to be as minimally disruptive as possible. If an user needs to face a downtime of services because of GenAI integration, the productivity will not be that obvious. Integrating GenAI capabilities directly to the database portfolio can be a smart solution to this problem. This enables clients to build AI powered applications with great degree efficiency and accuracy. This enables customers to combine AI vector processing with their already established sets of private business data without the need to duplicate it elsewhere. This is an excellent way through which customers are bale to embrace this innovation without going through severe and costly IT disruptions. 

How are GenAI powered database management solutions helping customers address regulatory requirements?

Everybody is interested in IT modernization and data modernization. Companies are thinking on ideas to extract actionable data from years of accumulated data sets. It is not just about the data but the business and IT framework that revolves around this data. We are looking at this from a basis of holistic framework. It combines several innovative capabilities. We have garnered enough knowledge around industry best practices on data can be accessed and processed. We now have the next generation cloud infrastructure deployed in a distributed manner and this can be used to train and serve AI models at scale using low cost GPUs. This creates an array of use to use cloud services for developers and scientists. With regards to IT and data modernization, Oracle's uniqueness lies in data management capabilities powered by GenAI and cloud capabilities that has the capability to eliminate all kinds of hurdles related to digital transformation and new technology adoption. Customer's around the world are understanding and accepting this framework.