There’s no denying the widespread adoption of the cloud. From fledgling boutique stores to some of the world’s largest corporations and everyone in between, nearly anyone dealing with data is looking to the cloud for storage. This trend bears out in the numbers as well. Fortune Business Insights has valued the cloud computing market at $588 billion as of 2023. This value is expected to grow to nearly $2.3 trillion by 2032.
Of course, a specialized data storage solution like the cloud requires a security infrastructure that’s geared toward its unique environment, and there’ve been various offerings stepping up to fulfill this need ever since enterprises started migrating to the cloud. But technology moves at a fast pace, and enterprises need to stay one step ahead of the game or risk losing it all to malicious actors. Enter generative AI (Gen AI).
Gen AI is another growing modern-day technology trend that offers a wealth of use cases within the tech space. AI-led automation and processing tools are augmenting, and even revolutionizing work processes the world over. As Bloomberg reports, the market for Gen AI had already breached the $40 million valuation by 2022 and is well on its way to becoming a trillion-dollar industry within a decade. When it comes to cloud security, AI has the potential to overcome some of the most prominent hurdles in the industry today. Let’s look at these concerns, and how an AI-powered security solution can help.
Seven Major Cloud Security Issues that Generative AI Solves
Observability Across Multiple Cloud Environments
Multi-cloud setups are prevalent for enterprises operating in the cloud. In fact, as per this Forbes article, 76% of enterprises have already adopted a multi-cloud approach, and this number is set to rise to 85% by the end of 2024. However, being able to effectively manage and secure multiple cloud sources from different cloud service providers (CSPs) is its own challenge. One that CISOs the world over are struggling to meet. Using generative AI-powered cloud security can help mitigate this issue. AI can be deployed to provide a single-pane-of-glass view across CSPs, allowing you to run a single detection across multiple clouds.
Optimizing Threat Hunting
The traditional model for cloud security involves writing code in a query language to run detections. The more CSPs you use, the more query languages you need to know. With AI though, that task is significantly simplified. Instead of mastering a laundry list of different query languages for each service provider or data lake, AI lets you initiate queries using simple English. So, you can type in your search parameters like you would in a normal conversation, with no coding required. The AI then does the heavy lifting, translating your question into code, running said code, and serving up the results.
Bridging the Gap Between Development and Security Teams
Security and development teams can often be at odds, especially in larger enterprises. Development teams often see security as an inhibitor, while security teams worry about lax controls in development environments. The establishment of DevSecOps has gone a long way toward integrating development and security team cultures to mitigate the discourse. However, a key to conflict resolution is providing clarity, and AI can help with that too. Simplified and user-friendly insights using Gen AI, from well-defined data sets, enable effective, time-saving communication of cloud security posture. This can make understanding the state of the cloud much easier for both security and development teams.
Compensating for the Lack of Skilled Security Analysts
The massive skill gap prevalent in the security space is no secret. A 2023 Cybersecurity Insiders study found that 89% of the respondents were either moderately or extremely concerned by the shortage of qualified security professionals. This gap can be bridged with the use of AI, however. Since query languages are not needed (as we covered earlier), that’s one thing you can take off the list of requirements, which would automatically widen your search pool. Plus, you can focus on quality rather than the quantity of the cloud security team, making sure that you have a lean but capable team that can leverage everything that the AI-powered security infrastructure has to offer, rather than having a team of analysts who are scrambling to stay on top of threats in multiple cloud environments and always fighting against the clock.
Prioritization of Threat Findings
Depending on the size of your enterprise, the number of threats detected over say, one week could range from the hundreds to the thousands, and beyond. So how do you figure out which are the fires that need putting out immediately, and which are flashes in the pan that can be left for later? Either you roll in an army of analysts to sift through the results, or if your cloud security service has the capability, let AI handle it. Because yes, generative AI can assess your threats and pick out the ones that require the most attention, making sure your remediation actions are focused on the major issues rather than the minor ones.
Countering AI-driven Cyberattacks
Online discourse is awash with opinions on the impact of AI as a threat actor in the security space. In fact, it is being reported as one of the biggest trends to watch out for in 2024. And the best way to guard against this threat? To fight fire with fire. Phil Venables, VP/CISO of Google Cloud put it best when he said,
“While we also expect to see AI help attackers, AI should give defenders an advantage because AI is good at amplifying capability based on data—and defenders have more data.”
Reducing Cloud Security Spends
According to Gartner, the total cost of security and risk management totaled a staggering $118 billion in 2023, and that number is expected to rise to $215 billion in 2024. This is not surprising considering, per Infosecurity Magazine, enterprises use anywhere between 64 to 76 security tools on average. However, the advantages of AI-based security in terms of multi-cloud observability, no-code threat hunting, automated prioritization, and more will reduce both expenditures on tool sprawl and specialized security analysts.
If you are looking for a security tool that harnesses the power of AI and brings all of these advantages to the fore, schedule a demo of our HTCD cloud security SaaS. Visit our website for more details on how you can use AI-first cloud security to help better protect your cloud environment.
