Cloud Equity Group’s Sean Frank Talks AI Mingling with the Cloud

The influence of AI continues to spread across tech disciplines including the cloud. Recently Larry Ellison said Oracle would put “billions” into Nvidia chips as Oracle looks to further expand its cloud services with an eagerness to pursue AI players. Oracle seems to want to grab cloud market share away from AWS and Microsoft Azure, and the declaration also speaks to the opportunity Ellison might see in AI’s sudden proliferation.

Cloud intersects with AI in a variety of ways, from the use of AI as a tool to manage the cloud to the cloud serving as a flexible resource to accommodate the growing demand for AI.

Sean Frank, managing partner with Cloud Equity Group, a private equity firm, spoke with InformationWeek about the influence AI is having on the cloud and what the investment scene is interested in.

What does AI bring to the cloud right now? What is it changing? What is reshaping? What is it driving in terms of demand in the cloud space?

AI is reshaping every industry right now, and you know, for those that don’t feel it yet, which might be more traditional brick and mortar businesses, they will at high level as it brings new capabilities and improves efficiencies. It enables new services.

The biggest thing that it brings to the table now is a predictive component to everything that the business needs. The idea of cloud computing is that you can scale resources on the fly, right? So, if you need more disk space, you can scale it. You need more bandwidth or processing power, you can scale it. It allows for businesses or processes or even users to go from an on-prem environment where you're limited to just the resources and processing power of your physical computer in front of you now to be cloud-based where you can scale and adjust as you need to handle the demand.

What AI is going to allow cloud to do is really kind of predict those changes that are needed. So instead of reacting to slowdowns because you’re running out of memory, you’re running out of processing power -- it could predict when those things are going to happen based on analyzing historical data and then it can allocate the resources dynamically.

For a small organization or a small environment, it may not sound like a big task but as you’re thinking about these larger enterprises that might be running hundreds or thousands of servers that are all running different programs and they interact, if one thing goes down it can affect the rest of the ecosystem. It really is a very important aspect in being able to help make sure that everything is up and can be maintained.

From a maintenance standpoint as well, it really tends to a very significant benefit. Right now, maintenance in general, in IT and cloud-based infrastructure, is largely reactive. There’s a problem, the user reports the problem, and someone from the IT department will then investigate the problem. With AI algorithms, it’s going to be able to analyze historical data and patterns and predict failures or performance degradation in cloud-based resources before they happen.

This will allow for really, truly proactive maintenance, which I think is very limited right now, and thus limiting downtime or other kinds of performance issues. The same thing is true with security. Today security is very largely reactive. Someone notices some kind of anomaly or some kind of an issue and then you research it. Maybe there’s some malware or maybe there’s a hack. What AI is able to do on sort of a massive scale and very quickly is analyze network traffic and user behavior and system logs and really identify potential security breaches or unauthorized activities way faster than the human can, potentially even instantaneously.

Even from the end-user experience too, right now deploying a cloud is a very manual process and obviously cloud is a very broad term and there's lots of different ways that you can do it. If you think of a sort of one very simplified example, like AWS, you go in and there’s a lot that you have to configure from the type of cloud environment that you want to how redundant you want, down to choosing the specific resources that you want.

How much you know disk space? It’s a very manual process in a system that’s designed to be very scalable and dynamic. AI will allow for the ability to analyze user data and user preferences and patterns, and to recommend appropriate cloud resources and optimize those service configurations and really provide personalized experience.

The rush in popularity that generative AI is having -- is that driving a demand and need for cloud resources to support the growing desire to make use of AI resources? Does mean cloud resources need to be put in play to help accommodate capacity needs?

The idea behind AI is that it processes massive and massive amounts of data instantaneously to figure out what the best answer to the question or to the problem is. It inherently requires a lot of processing power, a lot of computing power. It is quite literally powered on the cloud because of the resource scalability. It’s sort of a full circle thing here. But yeah, as AI is more vastly adopted, and it’s used in more cases that we’re not just talking about, like on ChatGPT -- eventually your computer desktop may have an AI system and you just type what you needed to do or maybe speak what you needed to do. This all requires processing power.

The scalability and the dynamic aspect of that is really appealing with AI being able to scale at the end of the day, as more people are using AI or there’s more systems or services or programs and it’s become more adopted. More processing power and machines need to be able to have the data that's being ran through and processed.

If you think about search, the idea of search today, you go into Google, it’s looking for your key terms. It’s looking at the pages that rank the highest and it’s trying to give you the top 10 links that best answer your question, but it’s not storing any information. It doesn’t know which you think was the best article or what was the best answer. There’s no interaction. Obviously with AI there's an aspect where it stores the interactions. If you go on ChatGPT, you can ask a question and then a follow-up question that remembers your first question and that needs to be stored somewhere too. It’s not just a matter of having the processing power to go through all the massive amounts of information and have a system that’s giving the answer, but it’s also a system that stores the old information or the old conversations Then it can learn based on that and it continue to grow.

Are there are other players who are going to, maybe not specifically copy what Oracle is laying out, but like the idea of its strategy? To put their money towards cloud resources and AI as they expand?

I think the technology industry as a whole is thinking about that. Oracle is obviously very close to the infrastructure. We invest in technology businesses and it’s a question that we bring up in every meeting today. How are you thinking about AI and how are you adopting it? A digital agency, for example, is thinking about ways that they can improve maybe their content writing by instead of a human going in and writing the content for marketing, collateral analysis and AI system that they have can go through all the marketing collateral they have done previously and spit out sort of the best one page or the best website.

On the private equity side of things, where does the money seem to be going? What is the money chasing right now when it comes to cloud and AI? What does the private equity sector seem to like or at least have a taste for?

If you look at private equity issues as a whole right now, it’s obviously some challenging times. There’s macro headwinds that are top of mind for everyone -- recessionary concerns, all the geopolitical conflict, inflation rising. I don’t think that the economy is going to really significantly improve in the short term. I think that inflation and interest rates will continue to have impact.

I think there’s less optimism right now than we’ve seen in previous years. I think that a lot of firms are really betting that the technology industry as a whole, kind of irrespective of where you are within the sector, will be successful early adopters of AI. That’s going to lead to strong upside.

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