Episode Transcript
[00:00:15] Speaker A: Welcome to K beyond the go. And today I'm on the go in Singapore with Oracle reporting on the ground here at the Shangri La for the Oracle Cloud World tour. Cloud World is an event across the globe where participants can learn about Oracle solutions, connect with experts, experts and peers, and discover insights to solve business challenges. So for this interview, I've got a few executive interviews up my sleeve, so please stay tuned. Joining me now in person is Ashish Ray, vice president of product management from Oracle. Ashish, thanks for joining.
[00:00:43] Speaker B: Thanks Carissa. It's always my pleasure to be here.
[00:00:46] Speaker A: So let's start with how are you making Oracle's database more accessible and appealing within the JPack region? And what are you sort of doing to compete with other open source databases, for example?
[00:00:58] Speaker B: Yes, so you can look at it in multiple dimensions. So number one is when we are looking at the core database functionality, that's number one. Number two, how we are making it easily deployable across multiple platforms, that's number two. And number three, how we are bringing in new innovations within the data management of the database space. So let's go through one, two, three at a time, right? So number one is the core database functionality. Today in modern data management, the needs, the needs are very complex. You know, it is not just rows and columns. If you look at financial financial services company, they are not only doing financial transactions, complex financial transactions from party a to party b. They also have to do at the same time in real time fraud detection to make sure that party a when it transfers to party b, if they are going through bunch of intermediaries, whether they should be mapped to the existing fraud detection checks, they also have to do very complex transactions in case there are cybersecurity threats. So which means the nature of transactions, whether it is telecom, whether financial services, healthcare, these have become insanely complex. One way to address this complexity is like, okay, let's make sure that there are separate data solutions in place to tackle each of these problem areas or what we are doing with regards to Oracle database. Oracle data management is built up this functionality right inside the kernel in a very seamless manner. So that means when customers adopt our technologies, we are not necessarily integrating through bunch of APIs which build up business latencies. They are all part of the same kernel. So which means from a product development standpoint, which I represent, everything is all built in native integration, there are no latencies. And number two, when we built a new feature, these are all part of the one single codebase which we call converged database. So that has been our principle or philosophy to build up complex functionalities to address modern data management needs. So that's number one. Number two, then I mentioned deployment. Deployment means how do customers consume these modern functionalities that we are building the traditional way to consume this. Okay, look into your existing data centers and figure out the servers, the storage and the network and build up like this massive footprint, which of course has an impact on power, space and cooling. On the contrast, customers say like, okay, let's go into the cloud. If you go into the cloud, some of our competitive offerings, they say like, okay, ignore everything that you have done for the last 2025 years. Instead look into new data models, new data models, new databases, application changes that are a big shift which causes it disruption. And the customers are like, wait a minute, I don't want to do it disruption. I want to do everything seamlessly. And last 2025 years we have built up enough intellectual property on the way we do stuff, so we should be able to carry on doing it but still get the benefits of cloud agility. So what we have done in that regard, of course, we have made our databases available in our public cloud offerings. That's OCI. And we have done it in such a way, it's still the same database, which means there are no application changes, no new data models. It's very easy if you want to transition to cloud, but at the same time some customers may say, wait, like, I don't, I'm not really ready to transition to public cloud yet because maybe of data sovereignty reasons, data residency reasons, increasingly my applications could be all intermingled, intertwined with the database and I cannot just move one single piece of database. I have to move the entire application stuff. Oh my God, this is so complex. Can you oracle build this cloud portfolio right inside my data center behind my firewall so that I can still take advantage of the cloud agility but without the disruption. And we said, yes, absolutely, you can still use Oracle database in a cloud at customer model such that we bring slices of cloud to you behind your firewall. You can still use the database as a service without the it disruption. So public cloud, hybrid cloud through cloud or customer. And now with multi cloud, we are partnering with Azure where Azure customers can deck the benefits of the Oracle database, but in Azure regions, so that's deployment. And finally, I talked about one, two, three. The number three aspect is innovation, how you're looking at the modern innovation. And this is where modern topics like Jnai comes in. And I would be happy to get dive into details on this, but really what we are looking at, if I am an enterprise customer and figuring out this whole GenAI space, is there any way for me to leverage my existing data set, my private data set, and integrate that with gene AI models such as LLMs in a very application transparent manner, in a database native manner? And that's what we are looking at with new functionalities such as AI vector search that is coming as part of the upcoming Oracle database, which is Oracle.
[00:05:56] Speaker A: Database 23 c. What about open source databases though?
[00:05:59] Speaker B: With regards to open source databases, they are very interesting, they have very interesting use cases. But the way we look at open source databases, we have a deep respect for them. At the same time, at the end of the day, it's a customer choice. Customer choice primarily route what level of functionality are they seeking? And number two, once they deploy this functionality, what level of technical support are they getting for this? And this is not technical support for a small like two or three developer shop. This is technical support, enterprise level support for a complex enterprise, maybe with branches around the world. Right? We believe that with regards to both of them, with regards to both the technical functionality that customers seek with the modern data management challenges and then the support services that we have built up as part of a customer success program, many of our enterprise customers, because of these reasons, have continued to deploy and expand their oracle database footprint.
[00:07:03] Speaker A: So why would you say customers have flocked historically or recent times to more open source databases?
[00:07:10] Speaker B: In certain cases, some customers may see them as, as good solutions for in a point solution approach like, okay, we have a specific problem and here is an open source that they can download and start using to address that specific problem. So that's one case where we have seen some customers have adopted some open source technology, but when they try to integrate these technologies in the broader context, in the broader context, like the example that I said, when you're doing a financial transaction, it is not just, hey, debit from an account and credit to another account. It is a complex series of microtransactions that also have to happen in a very transactionally consistent state. We believe that in those cases, customers have still continued and will continue to stay and expand with Oracle database.
[00:07:54] Speaker A: So just going back to the open source database for a moment, would you say that they've just probably, yes, the technical side of it, but maybe just done a better job at marketing and branding, they're somewhat newer to the market, perhaps a little bit more hip in terms of what different generations think, would you say?
[00:08:11] Speaker B: Yeah, I cannot comment on that. I cannot comment on how open source approach their marketing or their go to market. But I can tell you that me being responsible for this product portfolio across Oracle database, across cloud systems, I can tell you that I have never been this busy. Which means we from an oracle side, especially as we see in cloud world Singapore, the momentum that we see is enormous. So while I cannot comment on how open source technologies approach their market or their branding, we believe that the awareness that we are seeing with Oracle database, especially with some of the innovation that we are planning, is literally going through the roof.
[00:08:49] Speaker A: What about the DB licensing model? So the charge per cpu core, how are you or Oracle addressing this commercial model other than advising customers to move to OCI for example?
[00:09:00] Speaker B: This is quite interesting. The database licensing on a per core model has been the traditional model and it is a well accepted model by many of our customers.
[00:09:11] Speaker A: What do you mean by well accepted?
[00:09:13] Speaker B: Well accepted in a customers understand this, that, okay, if I am using the database for certain number, of course we will pay just for the course for us, the transition from that model to and OCI model has been quite seamless in that regard. In fact, what we have done. So one of the products that I am responsible for is Oracle decider and Oracle accelerator is an engineer system where you deploy Oracle database. In this engineer system which is a hardware and network and servers optimized for the Oracle database. It's a very powerful machine and today it comes with a lot of cores. Because of our work with some of our partners such as AMD, Oracle Accedator comes with the flexibility such that even though it comes with a lot of cores, customers can just do what this licensing term, what we call capacity on demand, capacity on demand will say, okay, you don't have to license all the cores, you license only the cores that you need. And then if you want to expand the number of cores based on your expanded business, yeah, sure, you can activate more number of cores depending on your business needs. So while this has been a well accepted model over the years, along with cloud, along with things like capacity and demand, we have introduced a bunch of flexibilities in our licensing consumption that is of interest and that has been really been applauded by our customer base.
[00:10:33] Speaker A: So you said before traditional licensing models, are you saying now that that's starting to change?
[00:10:39] Speaker B: It's starting to change in that because it's in terms of cloud, it is much more flexible and much more agile. So I will give you one simple example. Like one of the core database functionalities is autonomous database, right? In autonomous database, as a cloud service, as a cloud database service, you are just subscribing to a steady state number, of course. Okay, you want your business to run with this minimum number, of course. You subscribe to just that minimum number, of course. And now what happens at the end of the month, at the end of the quarter if you need to run a report, right? Or if suddenly there is a business spike or autonomous database based on the intelligence built inside the database, it can automatically scale up and scale down depending on your business needs. Which means you as a customer, you are paying for this extra course only for the extra duration that you are using the course for. So this brings in a lot of licensing flexibility, in tune with your business demands, with your business dynamics, and that is huge. And the other aspect of this is while you're doing this, the way we have implemented and engineered this, there is no application downtime.
[00:11:49] Speaker A: So would you say because of this change of commercial model, starting to change, this gives OCI more that competitive edge now? Absolutely, because you guys were later in the market, in the cloud game, as I have been hearing throughout the last two days. So would you say that gives an advantage then to customers?
[00:12:07] Speaker B: Absolutely, and it is just one of the many advantages.
[00:12:09] Speaker A: Do you think customers know about that though, in terms of that licensing model?
[00:12:14] Speaker B: The customers that we talk about definitely know and I'm sure that there is no limit to how good we can be. So I'm sure there is scope for improvement on how we can spread this awareness within our customer base.
[00:12:26] Speaker A: So with your role as vp of product management, what can people start to sort of see on the horizon? Now I ask this question because again, one of the points that I've been and observations I've had is Oracle is known for its historical Oracle version of 47 years ago. Now you guys are modernizing, you're moving, you're changing.
How are you going to ensure that there's that competitive landscape against the other cloud providers now, especially in the product side of things?
[00:12:57] Speaker B: Yes, yes. Yeah, that's a very, very good question. Very interesting question. So if you look at our existing customer base, the existing customer base tends to rely on Oracle for business critical, to mission critical data. So there are various ways or there are various attributes that are very pertinent to this data set. Scalability, reliability, security, high availability, performance. I invent, like I use an acronym to myself, I call that acronym Sharp. Scalability, high availability, reliability, performance and security. So there are two aspects to it. Number one is, do we have a path towards innovation so that we can continue these attributes, providing assurances on these attributes as their data management needs explode and become more complex. And this path towards innovation continues for us with some of the technologies that we are bringing to market, such that core exadata cloud services and core database processing. So that way they are well invested with us because they have the assurance that, okay, Oracle is on this innovation trail for their existing data set, they can continue to get the same innovation trail. And then number two is as their business needs change, as their business dynamics change, to what extent we are also part of this change. So for example, when they are looking at complex, if it is a healthcare company, if you are looking at a complex healthcare environment, how we can bring in Gen AI advantages so that that in turn introduces automation and brings in healthcare in a very seamless manner, affordable to customers, to end users worldwide. So there are two aspects. One is continue with the existing path of innovation. Second thing, look out in the horizon, see how the technology and the business changes and see what innovations we can provide so that customers have the assurance that as their business directions change rapidly, they have a trusting technology partner with us.
[00:14:59] Speaker A: So what innovations can Oracle provide moving forward?
[00:15:03] Speaker B: Yes. So one big area that as I mentioned, that we are looking at is this whole Genai space. And if you look deeper into the Genei model, there are two aspects of Genai. One is you look at the public domain knowledge, which is the LLMs. You have to train the LLMs, the large language models. But then that's not enough for an enterprise database. Why? Or an enterprise customer, because how do you integrate this public domain knowledge to your existing data set, which could be hundreds of terabytes or it could be petabytes. That's where we come in. Some of the newer technologies that we are building as part of the upcoming database, which is database 23 c, is called AI vector search. Vector database or vector processing. In this whole new area where you're looking at data but not looking at data, and a superficial, just metadata level, you're looking at data at a deep semantic level. So for example, if I am a product catalog company, I may sell, say, for example like handbags, you can look at a handbag and you can say, oh, okay, this handbag is this price, it's made by this manufacturer and it has these certain attributes. So those are like metadata attributes which are very well trusted model. But now when you look at such a product information, you look at deep semantic analysis of this data or any image. Now you see like, okay, this is a handbag of this certain style, of this certain color. And this could be multiple variations of that color, which means you can have a different representation of this product catalog within your data set. And that's essentially called what we call as a vector. It could be handbag, it could be a complex financial document, it could be a legal document, it could be any other image, it could be an transaction, could be an entity. So the possibilities of these vector data sets are enormous. Now, within Oracle, if we have a model such that customers can use open source libraries to embed incoming data sets to vectors and stored that natively inside the database in a high performant manner, do the computations around vectors and do the search, all of them using the familiar Oracle APIs, then that's huge. That means they can bring in all the jnai innovations right within the database, within the data set, without causing massive disruptions in the applications. And when we talk to some customers about this, the light bulbs literally go up because they see that, okay, our administrators, our traditional database administration now can be data scientists because now they are looking at the semantic value of data, hence leading to the possibilities of unlocking productivity of these terabytes and terabytes of data they already have.
[00:17:56] Speaker A: So in terms of moving forward, what's sort of on your roadmap for the year, what can people expect and how from a product perspective, do you see OCI becoming leading when at least when.
[00:18:08] Speaker B: I personally talk to customers and the feedback that I get from customers, how they see OCI different or Oracle's cloud entrance to be different is they feel that we have brought in our, our enterprise value to the cloud. Oracle has been a trusted enterprise customer or enterprise partner over the last 20, 25, 30 years. When I talk to customers, say in the database space, when I say, hey, this database is available in OCI, they know that when we bring in the database deployment now, customers can say like, okay, let's deploy this database in OCI. They know that when we provision and deploy the database, even the nitty gritty initialization parameters, the default values that we set in these parameters as the database is brought up, we choose this very carefully based on our 2025 years of enterprise knowledge and best practices. So that way the inherent enterprise trust that everything that Oracle has done on premises, it's reflected through the set of cloud best practices. That trust remains. And increasingly, that's what enterprises see. Our customers see that when they are trusting OCI, the same level of best practices, the same security standards, reliability, high availability, scalability, all of them transition over without any disruption, without any downtime, without any application changes. So those are the big differentiators compared to if they were to go through any other competitive cloud offering.
[00:19:47] Speaker A: Do you think customers know that? That know that in terms of differentiators.
[00:19:51] Speaker B: Customers increasingly know this and I'm sure we can do a better job in making sure that this awareness is within the customer set.
[00:20:02] Speaker A: Join me now in person is Sunil Wahi, vice president, Fusion cloud applications from Oracle. So Sunil, thanks for joining. So Sunil, I was reading your bio before today's event and you are heading up the strategy and execution of large deal programs. So what is a large deal program?
[00:20:22] Speaker C: So thanks for having me through this podcast. I'll just give you a context of what I do at Oracle and what my team runs with large deals is essentially part of the solution engineering portfolio which I lead with. And this is for fusion applications. Fusion applications are essentially our set of core business applications which we have been developing and driving in the market for more than a decade now. It's our true cloud natively built SaaS set of applications around core ERP HR, which is from a human employee experience standpoint, customer experience solutions, and then a very strong set of supply chain applications also. So these solutions form part of what we call fusion applications. And me and my team essentially drive the entire solution strategy solutions execution working with clients in the region, for example Air Asia and Malaysia, Macquarie, which is again a very large customer we have in Australia, they have successfully deployed their entire back office. Finance on core ERP large deals is a segment which we lead to work way more closely with some of our strategic customers to help them be successful as they run through a fusion cloud SaaS journey. That's essentially what we do.
[00:21:49] Speaker A: So before we jumped on the interview, we're just talking about my last version of Oracle. Would you agree that people in the market still have an older version of Oracle? And then if so, how is Oracle going about sort of modernizing that sort of brand and leading it back to maybe the large deals program because you are working with large customers, how does that sort of look?
[00:22:11] Speaker C: So yeah, look, clearly we have had a huge legacy of customers, right? And that's our install base. Let's put them in the bracket of a set of our on premise customers who have been running, who were running our e business solutions, they have been running JDE, and they are also, some of the customers are also on successfully deployed Peoplesoft applications. Now this is our legacy on premise install base, which over the last decade we have been transitioning to fusion cloud. And that's again something which my team actively engages in working with partners working with consulting teams like Oracle consulting partners like KPMG, Accenture, Deloitte and others. So we have been and we have been successfully migrating a lot of these customers to fusion cloud. A few examples are the ones I've given you, AirAsia, Macquarie Pil, which is again a large liner company here in Singapore. They have successfully gone live on the fusion cloud. So the way we are innovating and the way we are moving towards fusion applications is one of the most agile way which customers can deploy. And hence we also have non Oracle install base in our competitive areas who are looking at us to advise them on fusion strategies. So we have done deployments of non Oracle install base as well who have successfully moved to fusion applications. So I would pretty proudly call out that our success rate in moving customers off legacy to fusion cloud is extremely high. Our success rate in customers who have the latest set of our innovations is extremely high. Like no customer on Fusion Cloud lives on a release which is even a step back.
All our Fusion cloud customers are on the latest application version and we release about four versions every year. In contrast to the on premise world where you've done a legacy release and you basically are behind because the upgrades, the technology which you need to move to, the customizations which you have done are all going to take a lot of time for you to move to the next release. All that disappears in the cloud world because cloud comes from a true native agile background. We run the updates every quarter. We advise the customers, we work with them to help them get into new innovations. And as a result of that, every customer of ours today we have about 40,000 plus fusion cloud customers are on the latest and greatest release as of this year.
[00:24:51] Speaker A: So there's a couple of things in there. You said, just going back to the success rate, what does that actually look like though? You said we've got a higher success rate. What does that mean?
[00:24:59] Speaker C: So by success, what I mean is customers who have shifted to cloud have gone live. They haven't had large lengthy times to move to the cloud version. They haven't got held up in implementation challenges or customization scenarios. Because the entire model of cloud is an agile driven model. We have what we call modern best practices within the application. So it comes with a set of pre built requirements around GL, AR, AP. There are business innovations as part of cloud.
I'm sure we'll talk about AI and Gen AI. There's workflow automation which is built into these applications, and there are pre built set of analytics, a whole lot of packaged analytics which are part of cloud. So when you think about it, take an example of any customer, say PSA here in Singapore, the largest ports Singapore authority, they are successfully live on fusion cloud. They went live on ERP, they have gone live on EPM, which is our financial planning, planning and consolidation cloud solutions. They're now looking at establishing a data strategy project as well, leveraging fusion analytics. So a lot of capabilities, Carissa, within what a customer requires is packaged is part of our fusion cloud so that customers do not have to go build their own applications. Yes, there could be some secret sauce applications which they do need. There will always be those kind of applications. Those we then let them leverage our PaaS application. So PaaS is, I'm sure Chris and others would have discussed with you, PaaS is essentially where we allow customers to extend the SaaS footprint. So if someone wants to build an application a which is very unique to their business and something which we cannot deliver, they're going to use the PaaS platform and they're going to build on top of it. As a result of that, anything which happens on SaaS remains standard. Anything which we release on a regular basis can be immediately rolled out. And hence the success rate and the deployment of these applications is way faster than the old on premise world.
[00:27:18] Speaker A: Would you say you're faster than competitors?
[00:27:20] Speaker C: 100%, yeah.
[00:27:22] Speaker A: So before, when you said implementation challenges, delays, etcetera, is that under the assumption that competitors would have implementation challenges and delays, et cetera?
[00:27:32] Speaker C: Well, look, from a SaaS standpoint, we are today, number one, if you look at, you know, multiple different statistics in the market, and the agility at which we can deliver these applications is already proven by the customers who have leveraged it. Right, and they have successfully deployed it. That's what I can tell you at this point of time. And at cloud world, you will hear from a whole lot of customers.
[00:27:57] Speaker A: What about new customers, though? In hindsight, it makes sense if you're saying there's a success rate because they're here and they're talking about it. But how do other new customers are perhaps listening to this interview, how do they sort of know? Because, I mean, at the end of the day, no one wants to feel delayed and they don't want to have implementation challenges, et cetera. So how do you sort of gauge that from the start with a new.
[00:28:16] Speaker C: Customer, perhaps in terms of giving them confidence and assurance that we can actually deliver? Well, I mean, multiple different ways. Right. One is we work very closely with our partners. So our large sis, our fusion implementation partners, they are skilled to deliver fusion cloud applications, there's certification processes, there's a lot of enablement which my team and our channels organization runs to make sure that they understand what we are talking about because the innovation is pretty fast. Every three months we are releasing new innovations and we need to make sure that the ecosystem is at pace to what we are offering. That's one. The other is we directly engage with a lot of our customers. We have a customer connect platform. We have about 80,000 plus and these are all published statistics, 80,000 plus users at any point of time who are engaging on our cloud customer connect platform. It's a public platform which folks can leverage and naturally our customers log in, they exchange a lot of information and that actually helps drive more than 50% of our product roadmap. So new capabilities are coming in from a lot of feedback from our customer community, the new customers who come in and you will hear a lot about new customers, right? Like you will hear from J Resources for example. J resources are mining company in Indonesia and they are one I would call new to the fusion system. They went live, they trusted us. They were running a non Oracle legacy platform and they are today successfully deployed fusion cloud, working closely with Deloitte and they're also speaking at the Deloitte forum. Oracle together was with Deloitte, was truly engaged with them through the journey. Right. We were giving them guidance on product capabilities. Deloitte was running the implementation strategy. We were constantly in touch through the customer success team. We have a customer success organization within Oracle who engages on a regular basis with every customer pretty much. And the role of the customer success office is to ensure cloud services get deployed. It's pretty simple. It's not about selling a software and moving out in the cloud world. We have to make sure a customer is successful and the measure of that success is done by the customer success officer. We have Gary Miller here, he's the global head of customer success services and his entire organization is one we work very closely with to make sure customers are well informed. And the implementation strategies which partners are rolling out is in line with the cloud agility principles, which means try to keep it at zero customization, try to keep it on time, try to drive new innovations into the product portfolio, into the implementation. I can give you multiple examples. For example, my team is now involved in a generative AI enablement plan because we have already announced generative AI services in our HCM cloud solution and we are constantly working on a regular basis with our key HCM customers to make sure that they adopt these capabilities, because guess what it is, it's a switch within the fusion cloud application. And that's where the customer success team comes in. My team comes in, we work with the customer to make sure these capabilities are switched on.
[00:31:48] Speaker A: What do you mean? It's just a switch? What do you mean by that?
[00:31:50] Speaker C: So we're talking about generative AI now, new innovations right now, what that means to our fusion application customers.
From a business standpoint, AI ML is something which you can divide into two areas, classic AI and generative AI. Now, in the world of classic AI, we have been constantly releasing capabilities. Classic AI has been there with us for more than a decade. We have been doing predictions, we have been doing correlation analysis, we have been studying patterns of data, driving insights from it, right from a database standpoint to our application standpoint. And that's why we run an autonomous database which can self heal, self patch, move it up to the applications layer. A lot of these core applications can leverage the inbuilt AI capabilities of our platform.
What we have done, hence in the fusion applications, take an ERP example, is we have exposed these AI services as use cases within the business application itself. So when a CFO is trying to look at fusion ERP from a GL standpoint, you have engaged in a banking project. They want to run a cache forecasting scenario. We can today do a predictive cache forecasting, which is machine learning driven. That's a classic AI use case and it's now inbuilt, it's part of a fusion application. So machine learning picks up the model, it picks up the cache forecasting use case and it can come out and give you predictions on what's your cache trend going to look like. And based on that, the CFO can make relevant decisions of should I go and look for supplier discounts? Should I go, you know, look at raising funds or so on. We have announced, we have been doing this for quite many number of years. Another use case is document recognition, right? So suppliers sends hundreds of invoices to you, you get these emails, and the biggest problem is how do you detect fraud? How do you detect duplicate invoices and how do you get this data into your application? Automated invoice recognition comes in, which is AI driven, and it can load these invoices into the AP system. It learns as more and more data and more and more invoices are coming in and it starts mapping this data right into your AP invoice fields. So what's essentially happening is your productivity has just completely changed. If you are running a shared services center. You don't need to necessarily run manual processes to capture invoice data. You don't need to run complex integrations. You can just use our IDR capabilities and it pushes data into AP. I can go on and on and talk about many use cases, right. These are two examples. We have classic AI embedded also in procurement applications for supplier risk detection. For example, you know, you could do risk assessment from a supplier standpoint based on certain trends and predictions. For example, you know, a particular supplier in particular country has a lot of social news spreading out, which is negative about their market capitalization. The system can first understand this data, analyze it and come out with predictions to say that there is a risk, which we are sensing where these suppliers could actually delay delivery of your goods or inventory or your shipments. This procurement head could then start making insights around it to say, okay, how do I change my sourcing strategy? How do I look at other suppliers to mitigate my risk? Now, in the traditional days, all this would have been manually done. You look at suppliers, you start measuring their risks, you start ranking them, and you start basically figuring out how do I keep multiple suppliers in my sourcing plan. Today, AI can actually run those predictions because you have data and you could run those analysis. Now you shift this into a generative AI world, right? So last year OpenAI came out, we all woke up to the Jack Chibi phenomena.
And essentially, generative AI is the next level of this entire AI ML umbrella. And generative AI, what it's doing is basically looking at how do you offer assisted authoring capabilities or generate relevant text meaningful insights using the data which you have within your business applications. I'll give you an example. Job requisition process. You know, to create a job requisition, every time a HR officer is going to go into the system, try to pick up a job description, pick up the competencies, pick up the goals of that particular job, and start keying in manually. Generative AI comes in with AI assist capabilities in HCM cloud, the use case, which we have just announced. And that use case basically helps you completely automate the job description process. So it writes the narrative for you, Genai writes the narrative for you, it writes the goals, it writes the description for you, and then the human can actually go in and run the edits. Now, this data is coming from your own fusion application because you would have, you know, previously created a similar job type, you would have created a similar job grade. So the Genai model has picked up these insights and given you a particular job description and then the human or the HR officer can edit it and then go and publish it. Hiring.
[00:37:22] Speaker A: So I just want to switch back to the legacy customers. So would you say with your experience, it's hard to sort of do that transition to fusion cloud for historical legacy customers or what's your view?
[00:37:35] Speaker C: We have tools to move our legacy customers to cloud. We have lot of experience, tremendous amount of experience within the partner community, within our own consulting organizations to make this transition. So it's not difficult at all.
[00:37:51] Speaker A: So would you say that majority of people are fusion cloud or more legacy oracle customers? Where would they sort of sit?
[00:38:01] Speaker C: Well, I won't share percentages with you for sure, but a majority of our customers definitely today, are fusion application customers. I mean, the cloud transition has happened for the entire last ten years. It's not year one for us on fusion application. It's been more than ten years since we have developed these applications, natively built them on the OCI platform, and we have been constantly enhancing, releasing new innovation. So the core erp we have already sorted, you know, our core ahar ap gl. We have massive customers, I mean, right from Macquarie bank to Siam Commercial bank to, you know, large pharma companies in India, JP Morgan in North America, Citibank, HSBC globally runs their back office finance on our fusion cloud ERP systems. So these customers are again large marquee logo customers and they wouldn't have gone live successfully if the applications did not cater to their business requirements.
So we are fairly strong in the logos we have, we are extremely capable to deliver to the requirements which a lot of these industries ask for. I mean, in hospitality we have Marriott who's running our HCM cloud applications, we got Hilton who successfully live on HCM solutions, they run learning management, they run talent, they run recruitment on HCM cloud, and they process hundreds and thousands of transactions on a daily basis, pretty much. So it's a fairly mature footprint we are talking about at this point of time.
[00:39:46] Speaker A: Yeah. So definitely not questioning sort of the capability of the application more. So just customers intention. No one likes doing things they haven't done. It's hard, it's risky, it's more expensive, we've got to get new people in. There's those reservations, people that. So it's more this their intent. As soon as you put the word cloud in anything, people do still feel fearful, even if it is ten years, like just anywhere with cloud generally, I would say that, you know, maybe people still don't get it, they don't send the value still even, you know, it seems maybe obvious for people like yourself, but isn't as obvious for customers. Perhaps it's more so they're in motivation.
[00:40:23] Speaker C: Well, I mean, you have a fair point and I'll tell you what's happening, right. So I think five or six years back, the conversation among cxos was about why cloud, right. And we used to get into these discussions to say cloud offers a B, c agility, low cost of ownership, faster ROI, low risk XYz. Today, a lot of cxos you're going to talk about, the biggest concern is how do I move to cloud at a rapid pace. So the question is not about cloud or no cloud, the question is how cloud. And with that question in mind, naturally there are a lot of software providers who have come in with multi cloud strategies. There are options which customers have to decide whether they should go for a unified cloud platform like fusion applications, where they could bring ERP, procurement, CRM, HR, supply chain on a common platform. Or they look at point cloud solutions. So the conversations or what we are trying to do today is essentially give them sufficient confidence and sufficient quantified business outcomes that a unified cloud model like a fusion cloud solution can actually be better, more agile for you and way more cost effective than going for point cloud solutions. And I can give you examples in that space as well.
[00:41:49] Speaker A: So just going back to the customer side of things, historically, if you look at the last 1020 years, a lot of people probably went more, one provider, then we saw a shift to point solutions and now we're sort of seeing it come back the other way. Why do you think that's the case?
[00:42:03] Speaker C: Customers have also gone through sufficient amount of suffering. I mean, you know, initially everyone thought like the procurement office thought they're going to set up their own procurement cloud. The finance office wanted to go and do their own finance cloud transformations, and the supply chain office or the CEO's office wanted to go do their own thing in manufacturing because they never believed that manufacturing can run on cloud. They did that and then companies came in with integration solutions to say, hey, we are integration providers. We can help you orchestrate business processes across different cloud solutions. But at the end of the day, it just became a very complex architecture if you think about it. Different technologies, different learning skills, different capabilities and expensive integrations which are again being costed, charged by these cloud providers. Hence that entire wave anyways, had to turn back. Because when you look at ingress and data charges, which these cloud providers would then charge these customers, they got a reality check and they started realizing the value of a unified cloud platform. It could be phased out. So don't get me wrong on that.
[00:43:16] Speaker A: So we could go back to point solution again, what?
[00:43:19] Speaker C: Not to a point solution. You could phase out your deployment, for example. You could start with, I mean take any example, a successful rollout of PSA, for example. PSA started with a back office finance transformation. J resources did the same, AirAsia did the same. You could start with GL accounting hub core, AR, AP modernization. And from there you could move into a phase two of I want to now go and tackle my supply chain, my procurement, and then you could hit a phase three to say, now I want to look at HR, I want to look at customer experience and I want to look at my data strategy. The beauty of the fusion cloud story is that it's all on a common platform, it's all on a unified cloud. So you have a choice as to how do you want to deploy this? Yes, we have customers who go for a big bang approach as well, but then they have the internal DNA. They have kind of figured out the cloud implementation models internally so they don't struggle that much if they decide to go for a big bang. Other customers naturally have a flexible approach to go faced and cloud services are subscription driven. So basically you're paying what you're using.
[00:44:29] Speaker A: So in terms of moving forward, do you sort of see more market consolidation like in terms of trends or what do you think?
[00:44:37] Speaker C: I mean, AI, ML, Genai, these capabilities are coming out as key differentiators for companies, right? And they are asking, CFO's, cxos are asking the IT organizations, their IT organizations to help them devise an AI strategy. So every CXO forum we go into, they are talking about how do we differentiate with leveraging these solutions? And I think that's going to create a huge edge for cloud service providers like us who would have a lead in these applications to leapfrog, right.
This consolidation opportunity as it exists. And that's going to basically define the role of cloud players. That's going to define how we are going to continue innovating on that particular path. And I think the journey is already set. We are on that journey. We are deleting very confidently.
[00:45:37] Speaker A: And there you have it. This is KB on the go. Stay tuned for more.
