The Impact of AI and Machine Learning on Cloud Data Protection

The momentous rise of AI continues, and more and more customers are demanding concrete results from these early implementations. The time has come for tech companies to prove what AI can do beyond adding conversational chat agents to website sidebars.

Fortunately, it’s easy to see how cloud data protection has already benefited from advancements in AI and ML. Headline-grabbing large-language models are also making protecting data in the cloud easier to manage across organizations.

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Practical applications of AI and ML in cloud data protection

The potential threat landscape for organizations that work in the cloud is exponentially more complex than that of wholly on-premises solutions. Yet the benefits to productivity and accessibility that go hand-in-hand with working in the cloud are too potent to ignore.

AI and ML give human data security professionals the tools they need to magnify and automate their cloud data protection capabilities. These tools help shield organizations from vulnerabilities while empowering workers rather than limiting them. Here are some of the ways they can help:

Automated threat detection

Employees often use a mix of organizational and personal devices to access a suite of services across a range of networks. This usage exposes an organization’s data to a dizzying array of potential threats. By using AI-powered insights, organizations can build policies that limit access when services or devices have vulnerabilities they deem unacceptable.

Predictive analytics

The best way to make a sound prediction of future events is by processing a large data set of previous events. As datasets grow in size, they become more difficult to parse. AI is singularly effective at drawing insights and inferences from large quantities of data, which allows it to make better judgments about what may or may not constitute a threat to your organization’s cloud data protection.

Enhanced encryption techniques

Encryption has been part of data security for millennia. Now, rather than working by hand through complex formulas laid out in lengthy documents, AI can leverage substantial computation power to strengthen encryption algorithms. It can also spot potential risks within that encrypted data. Granted, it’s also true going the other way: AI-powered tools give threat actors much more powerful means of breaking encryption.

User behavior monitoring

Keeping tabs on user behavior in a hybrid work setting poses several challenges: privacy, of course, but also practical feasibility as scale increases. AI and ML tools help address both of those concerns by powering user and entity behavior analytics (UEBA) that can spot potential issues the moment they occur while otherwise leaving employees free to work without overbearing surveillance.

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Cloud security benefits of AI and ML

So, what do these uses for AI and ML tools mean for your organization? The potential cloud security benefits are broad and will look a little different for every use case. Here are four of the most common and compelling:

Broader perspective

Potential threats to cloud data protection span a massive breadth, from a fleet of devices running different OS versions to massive spans of CVEs in apps to social engineering tactics employed by threat actors. AI can parse and recognize patterns in these threats in ways humans cannot. This empowers human decision-makers to take a big-picture view as they set policies.

Faster analysis and action

Using AI and ML tools can also enable more rapid responses in cloud data protection. In a field where minutes can spell the difference between a contained threat and a massive data breach, speed is essential. By acting on inferences from their broad and deep data sets, AI tools can intervene to prevent risky or malicious activity.

Personalized education and onboarding

LLM-powered chat models also offer great cloud security benefits when applied thoughtfully. Lookout SAIL is a generative AI tool that can introduce Lookout’s features when and where users need them. It can even pull up relevant portions of the dashboard, including pre-filtered database searches that show exactly what the user is looking for.

Easier administration

Tools like Lookout SAIL also level the playing field in terms of protecting data in the cloud. Rather than needing to study in-depth documentation to figure out the most relevant ways a platform can help, users can ask the AI tool to surface relevant portions of the platform and explain how they may be of use — all while linking to documented sources for further detail.

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Challenges of protecting data in the cloud with AI

For a task as complex as cloud data protection, no one technology is enough. Organizations must deeply integrate AI throughout their control and data structures — which means that the AI, too, must be carefully controlled and monitored. Here are three challenges to assess as you build AI into your cybersecurity plan:

Privacy and compliance

AI tools require broad access and a degree of autonomy to use that access effectively. Yet they are just as bound by privacy and compliance standards as a human analyst paging through information. Any cloud data protection strategy that uses AI must not introduce new issues by improperly surfacing information or by using that information in a non-compliant manner.

Resource concerns

Modern developments in AI, such as LLM, can be very expensive to both train and run. This may result in economic as well as infrastructural and environmental challenges. While the end result may be worthwhile, each organization must weigh the potential costs of AI and ML solutions against the potential cloud security benefits.

Integration

The broader pushback against “AI washing” proves that organizations cannot simply add a chatbot to their current interface to achieve lasting results. To function effectively, AI and ML tools require deep integration across systems and data stores. They must be implemented with a fundamental understanding of the technology's practical capabilities as they stand today.

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Build better cloud data protection with proven AI

At Lookout, we’ve been using AI and ML to simplify security operations and increase effectiveness for years. That early push resulted in the world’s largest dataset of mobile security information and a platform that can use that data for real-time detection and response to mobile threats. We have applied the same strategy to combat phishing and monitor user behavior to prevent risky and malicious behavior.

Learn more about how Lookout uses AI and ML to help your organization stay ahead of evolving threats.