Lowering Adoption Barriers to AI

“Organizations do understand that they are going to benefit more by bringing in more useful data across their business lines for deeper insights. But that doesn’t mean that they cannot get started with the amount of data they currently have.”

Although AI as a concept has been there for a very long time, it is only now that the businesses are exploring the technology to see how it helps in their transformation objectives. Artificial Intelligence(AI) and Machine Learning(ML) technologies are now being used extensively to recognize patterns across data, user interactions to draw insights and do away with the mundane tasks, so on and so forth. Premalakshmi R, Head – Cloud Platform, Oracle India talks about how the traditional businesses and applications are able to improve their user experience and productivity by infusing AI/ML into the business processes and customer interactions.  

Excerpt:

What are the low-hanging fruits for AI in terms of adoption? How technology decision makers in organizations embracing it? 

When we look at some of the Indian Businesses who are embracing AI and ML technologies, the advantages become very evident from the business standpoint – customer engagement, enhancing employee experience, self-help, etc. AI-enabled chatbots, analytics for real-time decision making are some of the key areas where Indian CIOs or Indian businesses are extensively deploying AI and ML. Organizations are certainly understanding the value of AI and ML and putting them to use in the areas where they can be more data-driven to enhance experiences, take away mundane activities which otherwise is required to be done manually. 

To give you some of our use cases across Indian organizations, Bajaj Electricals has used the AI and ML technology in the form of a chatbot named ‘Bajaj Paddy’. The bot addresses the customer queries in a much faster and efficient way. Now Bajaj Electricals is also thinking to expand the same for their employee experience, internal purposes, etc. Another leading polymer company has started using similar bot technology to enhance its internal employee engagement and digital experience. A leading petroleum company has also started using AI and ML-enabled technology for end-to-end vendor management. 

Could you tell us how do you help organizations embrace AI? 

Most of the organizations are still at a nascent stage of AI adoption and they are trying to have a grip on the technology to understand what are the best ways to put AI into use. Once the customer identifies their current business challenges and what they want to achieve – some form of AI and ML technology will invariably come in handy as a solution. Rather than building just AI cloud services, we are infusing AI capabilities across our SaaS, PaaS, and IaaS offerings. This enables our customers to leverage AI across any of their business plans or any of the cloud applications or services they adopt. We are also able to offer better automation and price-performance ratio vis-a-vis any other cloud vendor today and that is certainly encouraging a lot of customers to take advantage of the new-age technologies and speeding up adoptions in turn. 

Another important advancement that we made around AI and ML is ‘Autonomous’. It helps organizations to free up their critical resources from mundane activities and help them focus on more important tasks. Our Autonomous Cloud offering comes with three game-changing capabilities: self-driving, self-securing, and self-repairing. Through self-driving, the database automatically backs up itself, it is able to fix and recover the issues on its own. This improves your efficiency, brings down the cost and eliminates all human labour and human errors. And when we say it is self-securing, we mean that the system automatically applies patches, helping to protect itself from malicious external attacks. And lastly, when we say it is self-repairing, we are providing an alternative protection feature for all the planned and unplanned downtime. We have quite a few customers who have already started moving in many of their workloads into our Autonomous service.

Data is the lifeblood of AI. But is it a prohibiting factor for organizations who don’t necessarily have large data sets to work with? 

Yes, AI becomes better when more data is available, and organizations do understand that they are going to benefit more by bringing in more useful data across their business lines for deeper insights. But that doesn’t mean that they cannot get started with the amount of data they currently have. Hence, I don’t think that is currently a limitation for them to start. We have already a few customers who have adopted AI technologies and started seeing the results.  While the businesses understand that AI and ML technology is going to be extremely important, they are also aware of the fact that they have to have a clear view of their objectives in the long term and make sure that the teams are also nimble enough to adapt themselves to these technologies. 

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