Have you ever wondered how streaming sites like Netflix recover so quickly after a system crash during peak hours? Or how mobile apps keep rolling out new updates without disrupting the user experience? Chances are artificial intelligence is behind the scenes, automating IT tasks to keep everything running smoothly.
More and more companies are taking advantage of AI to make their IT processes more efficient. They will likely invest over $8 billion in this practice by 2032.¹ This article will discuss how automatic, AI-powered tools have improved many IT tasks that were traditionally done manually, changing the industry for good.
Read more: Leveraging AI and Machine Learning to Drive Business Innovation
Understanding AIOPS: Using Artificial Intelligence to Automate IT
AIOps—artificial intelligence for IT operations—is a collection of AI-based technologies and methods. Its main goal is to enhance the operational efficiency of IT tasks.
ITOps, or IT Operations, focuses on traditional and manual IT management. On the other hand, AIOps uses the newest AI tech, such as machine learning, artificial intelligence, big data analytics, predictive analytics, cloud technologies, and real-time monitoring.
A big part of AIOps solutions is automation, which usually means replacing manual IT tasks with tools that can do the job automatically—increasing efficiency while reducing costs. By automating many IT jobs, like issue resolution or performance monitoring, professionals save a lot of time and costs, allowing them to focus more on their major priorities.
With these advantages of AI automation, it is no wonder that almost 95% of IT and engineering leaders say their organizations are focusing on automating many of their processes.²
How AI Automation Boosts IT Efficiency
Here are seven ways AI improves the work of IT professionals through automation.
1. Predicting Potential Failures to Reduce Downtime
AI can predict when IT systems might fail in real-time, helping businesses fix problems before they happen and avoid downtime. It does this by looking at past data and how a system behaves so it can recognize early warning signs of issues. This is really helpful in industries like healthcare and manufacturing, where even a short delay in operations can have damaging results.
Machine learning is one of the main AI technologies used in predictive maintenance. For example, IBM’s Watson AIOps processes vast amounts of IT data to identify patterns that might become problems. A manufacturing company could use Watson AIOps to monitor its production line systems. If the AI detects unusual data, like changes in the temperature of an important machine, it will notify the team immediately.
2. Monitoring and Fixing Problems Without Human Input
In some cases, AI-powered tools can both monitor systems and troubleshoot issues without any human work. This type of automation is especially useful for large-scale operations like cloud services or data centers, where the sheer number of components makes manual monitoring impractical.
Instead of spending hours manually searching for problems, AI analyzes system data to quickly pinpoint the source of the issue. If the tool is capable, it can also resolve the problem automatically.
An example is Dynatrace, a tool that uses AI to monitor issues like slow performance or service outages. A massive streaming platform can be used to handle high-traffic periods. For instance, if their site slows down due to high traffic, Dynatrace can detect the issue in real-time and integrate with automation tools to allocate additional resources, ensuring smooth operations.
3. Connecting Various Factors to Find the Main Issue
Sometimes, IT problems are too complex and will need advanced analytics. AI helps IT teams solve these issues by connecting related incidents and identifying the root cause. This saves time, as technicians don’t need to manually go through logs or investigate each issue separately. In large IT environments where multiple problems can occur at once, incident correlation ensures that all your resources focus on fixing the real cause, not just the symptoms.
Splunk is a leading tool in this area, offering AI-driven insights for root cause analysis. For instance, a global e-commerce platform might notice that customers are having trouble checking out. Splunk can look at the system logs and find out that a recent update to the inventory system is causing delays in processing orders. The IT team can fix the problem quickly by undoing the update so customers can check out without issues.
4. Detecting and Addressing Cybersecurity Issues
Businesses can also automate cybersecurity using AI. Traditional methods that rely on people can be slower and less effective, especially when it comes to more sophisticated cyberattacks. AI can spot unusual activity, like unauthorized access or harmful files, and act fast before problems get worse. This anomaly detection is especially important for places like banks or hospitals that handle sensitive data.
For instance, Darktrace uses AI machine learning to understand normal business operations in a specific system. So, when ransomware or other security threats try to attack it, Darktrace can block the problem and stop it from spreading.
5. Automatically Testing and Updating Software
Gaming platforms, mobile apps, financial services, and e-commerce sites are types of systems that need fast updating. AI makes it easy for these systems to keep their software up to date by automatically testing and installing updates. Aside from saving time and costs, automatic updates also reduce human error. Plus, they improve cybersecurity since outdated software is more likely to get hacked.
Azure DevOps is a popular platform that leverages AI to automate patch and system updates. It tests updates in a staging environment to ensure compatibility and then schedules deployments during ideal hours. A financial services company can use Azure DevOps to update its trading platform overnight, keeping it secure and up to date without interrupting market hours.
6. Identifying Images with AI Vision
Computer vision is an AI technology that involves identifying objects, reading texts, and analyzing images or videos. It automates a wide range of tasks, such as managing inventories, monitoring security, inspecting products, and processing documents. By automating these tasks that are used to involve human eyes, AI helps IT teams save time and reduce human error.
For example, computer vision AI can be used in security systems to detect and track unauthorized access or suspicious activity. In software development, computer vision helps test user interfaces by finding visual errors or inconsistencies. It can also monitor server rooms in IT management, spotting problems like overheating or equipment failure.
7. Enhancing IT Support with Chatbots
AI-powered chatbots are automatic response systems that provide IT support. They can answer questions, help reset passwords or fix simple issues directly in tools like Slack or Microsoft Teams, saving employees time and effort.
These chatbots use natural language processing (NLP), a technology that helps them understand human language so they can interpret what users need and give correct answers. Machine learning and generative AI also help them improve over time by learning from past conversations so they can provide faster and more reliable support.
Examples include chatbots like Workativ’s IT Helpdesk and IBM Watson Assistant. These chatbots are available 24/7 and give fast and personalized help to businesses and their customers.
Ready to boost your IT processes with AI automation? C4 Technical Services can help!
At C4 Technical Services, we specialize in implementing cutting-edge tech solutions—from streamlining your operations with cloud computing to monitoring your systems with generative AI. Our expert team will help you find the best tools to predict trends, prevent security breaches, and achieve measurable results.
We can start by building an effective plan to integrate AI automation into your system. It all starts with you.
Contact us today to unlock your business’s full potential with tailored, AI-driven strategies.
References:
- “AIOps Market Size, Share, Trends | Global Growth Report [2032].” fortunebusinessinsights.com, 13 Jan. 2024, www.fortunebusinessinsights.com/aiops-market-109984.
- Salesforce. “IT Leaders Fueling Productivity With Process Automation.” salesforce.com, 6 Oct. 2020, www.salesforce.com/content/dam/web/en_us/www/documents/platform/it-leaders-fueling-time-and-cost-savings-with-process-automation.pdf.
