More and more businesses today are moving to the cloud. This shift has many operational and security benefits, but those advantages don’t come automatically. Making the most of the cloud means taking a new approach to security and artificial intelligence (AI) can help.
The cloud holds more than 60% of all corporate data — and that number will likely keep growing over time. Consequently, protecting these environments is essential, but many conventional, manual approaches to that goal fall short. Here are five ways AI helps teams overcome these challenges and improve cloud security.
1. Accelerating Response Times
One of AI’s most significant advantages in cloud security is its speed. Machine learning algorithms can identify common activity patterns from past cyber incidents to learn the early warning signs of similar events. They can then spot potential attacks or breaches and take action sooner.
Because these algorithms can monitor a company’s entire cloud environment at once, they can detect unusual behavior far faster than employees can. Their response speed doesn’t end at alerting people to the issue, either.
AI security tools can also contain the breach as soon as they spot it. When an algorithm recognizes a potential hack, it can restrict access privileges and take things offline as necessary to prevent it from spreading. This quick reaction helps security teams investigate and resolve the issue faster, minimizing the incident’s impact.
2. Minimizing Human Error
Another critical security benefit of AI is the reduction of human error. Even veteran staff can make mistakes — especially in a field like cybersecurity, where small, easily missed factors can have a significant impact. By contrast, AI is excellent at recognizing minor details and provides the same level of accuracy every time.
Humans get tired and distracted in monotonous, data-heavy work like network activity monitoring. AI doesn’t, so it can handle these tasks more reliably. Automated solutions will find things employees may miss and reduce false positives, too.
This error reduction applies to more than just mistakes in security workflows. Experts estimate between 65% and 70% of cloud security problems stem from errors like misconfiguration. By automating more cloud processes through AI, teams will minimize the chances of simple mistakes that could jeopardize safety.
3. Reducing IT Burden
Similarly, AI also reduces the workload for already busy IT staff. While many businesses move to the cloud to make things easier on their IT departments, manual configuration increases their work burden in the end. Automating it through AI means fewer tasks they have to complete, helping them focus on other issues.
As tech employees’ workload shrinks, they’ll likely feel less stressed and distracted. Consequently, they could make fewer mistakes, improving cloud security by further reducing the risk of human error.
While AI is typically better at data-heavy and repetitive tasks, humans are better at more nuanced work. Automating the more mundane, rule-based workflows with AI gives workers more time and energy to focus on what they’re good at. Overall operational efficiency can improve as a result.
4. Improving Threat Detection
AI also provides new ways for cloud security teams to spot attacks. Cyber threats in the cloud change quickly and are often sophisticated, making them difficult to detect with basic tools. Machine learning can adapt to these changes to ensure cloud environments stay safe.
One of AI’s most advanced and innovative uses in this field is User and Entity Based Analytics (UEBA). UEBA analyzes how different users and programs operate within a given environment. As AI algorithms learn these habits, unusual behavior will stand out, helping identify breached accounts or apps.
This level of analysis would be virtually impossible with a manual approach, especially over every action at any given moment. As a result, using AI in cloud security opens up otherwise unattainable levels of safety.
5. Predicting Potential Threats
In some advanced use cases, AI can even help predict incoming security threats before they happen. Predictive analytics has already seen widespread use in marketing and supply chain management, but it can also improve cloud security.
Machine learning algorithms can analyze past incidents and compare them to current trends and cloud architecture to see where security falls short and which attacks are likely. Some models have achieved 92% accuracy in predicting if systems are vulnerable to malware and ransomware threats. Teams can use this information to patch their weak points before a breach happens.
Businesses can use this technology to run regular penetration tests to see how they could improve. These ongoing updates will help them protect their cloud environments as new threats emerge and systems change.
AI Is a Crucial Step Forward for Cloud Security
Cloud systems are becoming more advanced and many organizations are relying heavily on them. Protecting these environments becomes all the more important as those trends continue. While AI is a helpful tool now, it could be a necessity before long.
AI improves cloud security in many different ways. As businesses continue to move more critical data to the cloud, they can’t afford to overlook those benefits. Wider AI adoption could make the cloud a safer place.
