I was reading about Jio AI cloud this morning. Honestly, I did not know that Jio had a cloud service as well. Upon doing some superficial research, I interpreted that Jio Cloud is primarily consumer-focused, though there is an enterprise version as well. For both of these offerings the service focus currently is primarily storage. The most recent initiative, labeled Jio AI Cloud, powered by Jio AI brain, intends to float a cloud-based AI services platform. I did a little bit of reading on what Reliance intends to offer through this service. My interpretation was that while the opportunity is huge, some large gaps exist that need to be covered at a breakneck speed to make the offering commercially attractive.

As mentioned previously, the services that are being offered are currently primarily focused on storage. The current capabilities have both advantages as well as disadvantages when you compare them with some of the leading cloud players today. A big advantage is the access to massive data, specifically consumer data, that Jio currently has thanks to one of the largest cellular subscriber bases in the world (almost half a billion).

If you are thinking about becoming a formidable player in the cloud space, irrespective of the market you are in, you have to think beyond infrastructure. I have written numerous articles and reports on this topic. The fact is that when it comes to large enterprises, from a pure infrastructure perspective and from a pure cost perspective, the cloud is not as attractive as it used to be. The value-add obviously is in the additional capabilities that cloud services can provide.

There are a few different ways Jio can harness the access that it has to consumer data. I did not get a chance to do deep research into India’s data protection and privacy laws before writing this article. But assuming that Jio can access data pertaining to subscriber usage across key apps, it sits on one of the largest gold mines in the world when it comes to consumer data in one of the largest markets in the world.

There are a few different ways that this data can help Jio in boosting its cloud offering. Let us explore two of them. First, it can tap into this data to train the various AI algorithms it plans to leverage in its portfolio of AI services. I assume that the portfolio of AI services will be offered in two broad categories. One will be focused on the end consumer, whereas the other will be focused on enterprises. The good news is that Jio can extrapolate the capabilities from one category into the other.

When it comes to consumer-focused AI services, the data that it has can allow it to develop a portfolio of services with a high level of accuracy because of the training data available. This data will start helping Jio much before a single line of code is written. The first key step for Jio is to understand what type of portfolio it needs to offer. This is the step that will need significant time and resources, including data that Jio currently has access to.

Jio will have to strategize, based on the data, on what type of portfolio it can create for the consumer segment and enterprise, what can be the different features and functionalities of the products within the portfolios, and how they will relate to consumer and enterprise preferences. Only after this initial blueprint, the work on the development of algorithms can start. Since Jio already has years and years of data on the behavior across various apps, it can help Jio develop portfolios that are very nicely aligned with the kind of services the consumer segment may want.

Then comes the enterprise segment. Keep in mind that when organizations are looking to deploy solutions in the cloud, in addition to some of the obvious advantages like flexibility and scalability etc, they want to deploy solutions that they cannot generally deploy on their own. So they rely on AI services that these cloud providers offer. But if you take a step back and try to understand the purpose of these solutions, you can categorize them into two broad categories again. These enterprises want to deploy solutions either focused internally to digitalize their internal processes or to enhance customer experience and gain more insights into their customers.

You can see how Jio’s expertise in tapping their customer data can provide confidence to enterprise customers when it comes to deploying solutions pertaining to end customers. But the benefits actually spill towards internal digitalization as well. After all, any algorithm can be used for many different purposes. A deep learning algorithm can help customers manage their portfolio of picture albums better, but it can also help an enterprise manage their contract documentation in an advanced way. The more data Jio has to perfect these algorithms on the consumer side, the easier it will be to extrapolate these categories to the enterprise side

The key commercial success will come on the enterprise side. So the question then arises: Will large enterprises across the globe be willing to take a chance when they have options like Azure and GCP? The competition is unavoidable since these are the leading enterprise cloud players in Asian markets as well.

This is where Jio will have to leverage some technology marketing chops.

When it comes to AI technology management and execution, I believe only US and China surpass India’s capabilities. With India’s technology capabilities already recognized globally, this is one less headache that Jio needs to address. Still, there are a few aspects Jio needs to aggressively push on through marketing to establish their AI brain-enabled cloud services within the enterprise segment.

The future can be exciting, provided the starting path is strategized prudently.