Understanding IT Process Automation: Technologies, Benefits, and Use Cases

Today’s complex IT landscape is the primary result of rapidly evolving technologies and customer demands. Companies are constantly juggling multiple repetitive tasks like service requests, ticketing, auditing, and asset management, which ultimately reduce business efficiency and agility.

IT process automation is now the need of the hour. Primarily driven by technologies like CI/CD, DevOps, artificial intelligence, and machine learning models, automating IT processes has become a priority for achieving faster time-to-market and consumer fulfillment. In this blog, we take a deeper look at why automation in information technology is imperative, which processes require automation, which technologies drive the IT automation process, and the most common use cases of it today.

Before diving into what IT operations automation means and its advantages, let’s first understand what IT processes are and why they require automation.

An IT process is a set of tasks, activities, and procedures that an IT department undertakes to fully manage and support the technologies its organization uses. This comprises a range of activities from handling service requests and implementing new technologies to monitoring compliance, ensuring software and hardware maintenance and documentation.

The list of IT processes can often be too exhaustive and involve day-to-day tasks that are time-consuming. This has resulted in the need to automate such processes and streamline business operations, allowing teams to utilize their time more efficiently.

The IT automation process typically involves implementing technologies like machine learning and artificial intelligence to automatically execute repetitive IT tasks. Development teams use AI and machine learning algorithms that they can train through data to enhance efficiency in performing time-consuming activities.

Today, IT process automation is one of the most important undertakings in modern businesses, as creating automated workflows allows them to minimize human intervention and, in turn, save resources, expedite IT activities, and reduce error margins. Plus, automating an IT process also empowers teams to yield more efficient and faster results, allowing the organization to deploy better services or products and adapt to changing business environments efficiently.

As beneficial as IT process automation is, not all processes can be automated. Some of the most common processes that are suitable for automation include:

Handling service requests is one of the most common tasks for an IT department. These requests vary from issuing new hardware to employees to debugging internal software tools and fixing damaged hardware.

Implementing IT operations automation for such tasks significantly frees up time for IT professionals to cater to other high-value activities. Moreover, even if such processes are initially ad-hoc, teams can establish a strong workflow to automate them and ensure that undocumented requests don’t pile up from everyone in the organization.

In such cases, requests can be assigned to concerned IT members after they’ve been raised. Once the IT personnel completes a request, it can go off the queue without requiring any signed forms or other paperwork from one IT department to another, which is possible through automation. This saves massive time as records remain up to date and all paperwork is filed automatically, allowing IT departments to focus on other areas.

Companies often employ AI-driven IT process automation to streamline their incident management and ticketing systems. Teams can use machine learning models to analyze historical incident data, segregate and prioritize tickets based on impact and urgency, and assign them to appropriate IT staff for resolution.

Automating ticketing systems and incident management has proven to be extremely helpful. This automation allows companies to ensure critical issues receive quick attention, resulting in decreased downtime and faster incident resolution. AI can also help identify incident data patterns to detect recurring issues, enabling the IT department to establish permanent fixes.

Apart from service requests, another repetitive task IT departments handle are change requests, which refers to updating databases and records, implementing ERP system changes, and updating organizational information as and when needed.

IT process automation is also often implemented in this situation, removing the need for employees to collaborate with the IT department to make changes manually. Automating change requests can streamline the entire process, allowing the IT team to track the request and resolve it promptly. Any clarification needed is carried out via the request itself, ensuring that all concerned stakeholders are in the loop, and unnecessary emails and documentation are averted.

Irrespective of the organization type, compliance is of high priority. Company software must comply with regulatory and safety standards, and teams must conduct frequent audits to ensure all employees are compliant with data security protocols.

This is where IT process automation can help. Instead of relying on digital forms and emails sent across the company, IT teams can employ automated forms to maintain a master record to check if all employees have filled out the required paperwork. This eliminates the need to conduct frequent follow-ups with employees or juggle countless emails to ensure compliance testing is completed.

IT asset management is yet another area that gains massively from automation. AI-driven IT asset management automates the inventorying and tracking of the organization’s software and hardware assets. Here, machine learning models are implemented to assess data from multiple sources like usage patterns, procurement records, and configuration management databases (CMDBs).

This IT process automation of asset management offers better asset visibility while maintaining an accurate asset inventory without the requirement of manual labor. Automating asset management also helps to optimize software license usage and enable efficient hardware allocation, freeing up IT staff to focus on tasks that need their engagement.

Many companies also implement IT process automation to automate network and infrastructure monitoring. For this, machine learning and AI are used to create monitoring tools that offer real-time insights into the health and performance of IT systems, eliminating the need for IT personnel manually tracking the same.

AI-driven monitoring tools can analyze massive amounts of network data to detect anomalies and promptly alert the IT department about potential threats. This proactive approach can effectively minimize system downtime, boost network reliability, and enhance overall system performance.

AI and machine learning-driven IT process automation is also a game-changer in cybersecurity. Automation using these technologies enables advanced threat detection and prevention by analyzing large amounts of security data, including network traffic, user behavior, and network traffic.

AI-driven cybersecurity solutions can help IT teams detect patterns indicating malicious activities, like unauthorized access attempts or malware infections. By automating this detection, IT departments can swiftly respond to mitigate potential threats and implement safety protocols.

As evident already, automating IT processes can significantly increase business efficiency and streamline IT operations. Here’s a deeper look into the many benefits of automating day-to-day IT activities:

Automating workflows is one of the most effective ways for organizations to reduce IT costs. The lesser delays and bottlenecks, increased process efficiency, and minimized data errors or duplicates are massive cost savers. Plus, IT process automation also removes the need to hire extra employees to cover repetitive tasks and reduce hardware and software costs via optimal resource utilization.

Manual IT processes often lack visibility into the status of operations, resulting in several IT requests falling through the cracks. Automating IT operations, especially request management, enhances visibility into activities, allowing IT personnel to remain updated with urgent requests or tickets. This automation also eliminates the need to rely on manual inputs and enables team leads to stay on top of workflow updates, hassle-free.

As mentioned earlier, IT process automation eliminates the risk of human errors that can often occur during manual processes. Any automated activity follows the pre-established guidelines and rules consistently, ensuring that processes are executed uniformly and accurately. In turn, automation leads to high-quality deliverables and a reduced likelihood of costly mistakes that can harm the company’s reputation and customer satisfaction.

Automating IT processes also involves the automation of emails, feedback requests, and other communication elements that seal any collaboration gaps within teams. Automating communication promotes collaboration across the company and ensures better team collaboration, with lesser time spent on communicating important information.

IT process automation, particularly when combined with anomaly detection and predictive analytics, enables organizations to implement a proactive approach to problem resolution. By continuously analyzing data and monitoring systems, IT automation can detect potential issues before they escalate into major obstacles. This proactive response aids companies in preventing costly downtime and IT disruptions, ensuring that their IT infrastructures operate at the optimal level.

Automating repetitive IT processes like help desk support and incident resolution can also help organizations offer an efficient and seamless user experience. Using machine learning and AI, automated virtual assistants and chatbots can be built to deliver instant solutions and responses to users, decreasing wait times and boosting customer satisfaction.

Lastly, one of the biggest benefits of IT process automation is ensuring maximum flexibility and scalability to meet changing business demands. As organizations grow or experience workload fluctuations, automation can help them adapt to evolving needs without requiring significant changes in either their teams or the underlying processes.

Given the many benefits of IT process automation, companies often implement it today for anomaly detection, virtual assistants, better decision-making, and other key use cases. However, before we take a look at what these use cases are, let’s first check which tools and technologies help in the implementation of automation in IT.

AI and machine learning are an integral part of IT process automation. The two work together to help IT teams establish and implement seamless automation workflows that enhance efficiency, accuracy, and decision-making. Here are the most popular AI and ML tools that are commonly used for automating IT processes:

• TensorFlow: An open-source ML framework, TensorFlow offers a comprehensive ecosystem of libraries, tools, and resources that enable IT teams to create and deploy anomaly detection algorithms, predictive analytics models, and other ML-driven automation solutions.
• PyTorch: Another open-source ML framework, PyTorch’s dynamic computational graph allows IT professionals to build custom models and facilitate IT automation seamlessly.
• Scikit-learn: Scikit-learn is a popular Python library that’s highly useful for IT process automation tasks involving feature engineering, data analysis, and model training.
• AutoML tools: Automated machine learning (autoML) tools simplify model selection and feature engineering. AutoML tools like H20.ai let IT personnel build ML models effectively, automating model development and streamlining process automation. AutoML tools are commonly used for automating tasks like capacity planning, forecasting, and resource allocation.

Continuous integration and continuous deployment (CI/CD) are imperative to automating software development and deployment, allowing teams to make code changes reliably and rapidly. Here are the most commonly-used CI/CD tools in IT process automation:

• Jenkins: One of the most widely-used tools for CI/CD pipelines, Jenkins lets IT professionals automate the building, testing, and deployment of apps across multiple environments. It’s mainly used for IT tasks like software deliveries, code compilations, and artifact deployments.
• GitLab CI/CD: A component of the GitLab platform, GitLab CI/CD offers native CI/CD capabilities that makes it easier to define CI/CD pipelines directly within their code repositories. Hence, using this tool, IT teams can automate the testing, building, deploying, and packaging of applications.
• Travis CI: Travis CI integrates seamlessly with GitHub repositories, allowing IT teams to use ‘.travis.yml’ configuration files to define build and deployment workflows.

Automating and streamlining IT processes rely heavily on DevOps technologies as well. DevOps tools foster collaboration between teams, enabling efficient software deliveries and reliable IT automation. Here are the most popular DevOps tools for automating IT tasks:

• Docker: Using Docker, IT teams often automate application deployment and scaling, hassle-free. Docker allows teams to package applications and their dependencies into lightweight containers. These containers are then deployed to numerous on-premises infrastructure and cloud providers for process automation.
• Ansible: An open-source configuration management and automation tool, Ansible, simplifies IT process automation. It defines infrastructure configurations and automates repetitive tasks like configuration updates, software provisioning, and application deployment.
• Kubernetes: Kubernetes is an imperative DevOps platform for automating complex microservices architectures in IT, ensuring maximum resilience and availability. Its self-healing, service discovery, and load-balancing features allow teams to automate the process of deploying, scaling, and managing containerized applications.
• Terraform: Terraform is an IaC (infrastructure as code) tool that lets teams define and manage cloud resources in a version-controlled manner. Plus, Terraform enables DevOps teams to automate infrastructure scaling, provisioning, and management.

Configuration management tools are critical to manage and maintain consistent configurations across various systems in the IT department. These tools ensure that all IT systems are properly established, enabling IT teams to automate the process of setting up, configuring, and managing applications and systems. Here are some of the most popular configuration management tools:

• Puppet: Puppet is one of the most widely-used configuration management tools that allow IT teams to automate the management of IT infrastructure elements, including services, files, packages, and user accounts.
• Chef: Chef is another popular configuration management tool that uses code to describe the desired configuration of applications and systems. Teams often use Chef to automate IT processes like configuration file management, software installation, and application deployment.
• SaltStack: An automation and configuration management platform, SaltStack excels in remote orchestration and execution. Teams use SaltStack for it’s scalability and speed, which allow them to automate the management of complex and large IT environments seamlessly.
• CFEngine: An open-source configuration management and automation tool, CFEngine allows IT teams to easily maintain system configurations and ensure system compliance. This tool is mainly suited for the automation of tasks like security compliance, system hardening, and configuration management across diverse IT infrastructures.

Workflow automation tools are vital to IT operations automation, as they enable teams to create and automate workflows through the visual representation of processes. Here are some of the most common workflow automation tools:

• ServiceNow: ServiceNow is the leading cloud-based platform that IT teams use for business process automation. ServiceNow offers tools for process orchestration, workflow design, and task automation, allowing IT professionals to automate complex tasks like change management, service request fulfillment, and incident management.
• Zapier: Zapier is a popular cloud-based integration tool that lets IT teams connect and automate workflows between various web applications. While it’s not specific to IT processes, Zapier is often used for integrating and automating IT tasks like data transfer, system updates, and notifications.
• Microsoft Power Automate: For IT teams primarily working with Microsoft products and services, Microsoft Power Automate enables automation of workflows connecting multiple applications, the triggering of event-based actions, and data flow management.
• WorkflowMax: Similar to Zapier, WorkflowMax isn’t specific to IT process automation. However, its host of features like task allocation, reporting, invoicing, and time tracking enables IT teams to automate and streamline project management and task execution, hassle-free.

IT process automation remains incomplete without scripting languages, which are one of the most vital components that facilitate automation. These languages enable IT teams to automate various IT tasks, and some of the most popular scripting languages in IT operations automation include:

• Python: Python is one of the most versatile and commonly-used scripting languages for IT automation. It's versatility and large ecosystem of third-party packages make it an excellent pick for writing automation scripts, tools, and utilities to automate IT operations.
• Bash: Bash (Bourne Again Shell) is a scripting language popularly used in Linux, macOS, and other Unix-like operating systems. Bash offers a robust set of features that allows IT teams to automate tasks, manage files, and facilitate seamless OS interactions.
• PowerShell: A powerful scripting language, PowerShell is primarily used in Windows environments. It enables IT professionals to automate tasks related to system configuration, administration, and management.
• Ruby: Ruby, although not as popular as PowerShell or Python, provides capabilities for IT process automation of tasks like file manipulation, system administration, and text processing.

Currently valued at $13.96 billion, the IT process automation market is estimated to reach $51.26 billion by 2032, growing at a 13.89% CAGR. This clearly indicates the importance of automating IT processes, and its rising popularity. IT operations automation has become mainstream for many organizations, and that’s largely due to the rapid technological advancements that offer real business value. Here are some of today’s most significant use cases that show how automating repetitive IT tasks has positively impacted the IT landscape:

The integration of machine learning and AI in intelligent virtual assistants and chatbots has completely revolutionized IT process automation. These conversational tools follow a natural language format when interacting with users, making it simpler for both customers and employees to engage with their IT systems.

Chatbots have become indispensable for businesses today, and are undoubtedly one of the most significant use cases of IT operations automation. From a business perspective, companies can use chatbots to streamline their customer service activities and allow IT personnel to work on issues requiring more personal attention. Using natural language processing (NLP), AI, and machine learning, chatbots can handle various inquiries and tasks, like checking system status, resetting passwords, and delivering software updates.

The power of machine learning and AI comes into play as chatbots continually learn from user interactions. Leveraging NLP algorithms, chatbots understand the context of user queries to deliver accurate responses. Over time, a chatbot becomes more adept at handling complex requests, reducing the need for manual labor in routine tasks. In turn, this frees up IT professionals to focus on more strategic initiatives, enhancing overall operational efficiency and making chatbots a key part of IT process automation.

As we discussed earlier, AI-driven IT operations automation has been highly transformative in cybersecurity. Today’s digital landscape, which is more complex than ever, is no stranger to cybersecurity threats. AI and machine learning plays a crucial role here, enabling sophisticated anomaly detection to safeguard both companies and their employees.

Anomaly detection algorithms are based on machine learning. IT teams can leverage these algorithms to automate anomaly detection and continuously monitor network traffic, system logs, and user behavior, while they focus on their respective activities.

Automatic anomaly detection requires no human intervention, as it flags any unusual activities, like data exfiltration or unauthorized access attempts, automatically. Trigger alerts instantly notify the concerned IT team member, resulting in quick response and effective threat mitigation.

Robust anomaly detection has been one of AI and machine learning’s biggest contributions to IT process automation. Automating anomaly detection has allowed companies to detect security threats more promptly than ever before. As such, preventing data breaches, intellectual property thefts, and other malicious threats is more effective now. Additionally, machine learning algorithms used for automating threat detection can adapt to new attack vectors. Such algorithms can help IT teams identify and prevent emerging threats seamlessly.

Predictive analytics, driven by machine learning and AI, empowers IT teams to undertake a proactive approach to solving bottlenecks. Analyzing large amounts of historical data, AI and ML can detect trends, patterns, and potential threats that often lead to performance degradation or system failures. This allows IT teams to automate problem resolution by anticipating issues before they occur and implementing necessary measures to prevent them.

For instance, by assessing past network traffic patterns and system behavior, predictive analytics can forecast traffic surges and allocate resources accordingly. Resource allocation for system traffic is one of the most common IT processes commonly automated, as this helps to prevent network congestion and downtime faster since there’s no human intervention involved.

Similarly, predictive analytics can help with server performance, detecting hardware bottlenecks and prompting IT teams to replace components before they cause a system crash. Since this entire process is automated, there are lesser people involved, resulting in lesser resource consumption and a more proactive solution.

Additionally, proactive problem resolution through predictive analytics also helps to enhance user experience. Since there are fewer disruptions, employees and customers enjoy a smoother IT environment.

IT process automation also enables systems to become self-diagnosing and self-healing entities. As IT systems continuously monitor system health and performance, self-healing capabilities can help them detect abnormalities and initiate remediation actions automatically.

For instance, if an IT server experiences a sudden surge in CPU usage, its AI-powered system can detect the issue and implement corrective measures, like restarting affected services or reallocating resources. Automating such IT processes through AI makes it possible to restore normal operations faster, drastically reducing downtime and enhancing service availability.

Furthermore, self-healing systems are critical as they not only boost operational efficiency but also relieve IT personnel from the burden of constant monitoring and manual intervention in incident resolution. This minimizes human errors and ensures consistent IT infrastructure performance, ultimately resulting in better user satisfaction and system reliability.

Machine learning and AI are also pivotal in facilitating better decision-making in IT process automation. As mentioned earlier, ML and AI assess large amounts of data, identify patterns, and offer critical forecasts. These allow IT teams to make data-driven, informed decisions that help to improve IT efficiency, reduce system downtime, and enhance user experience. Here’s how AI and ML enable better decision-making:

• Pattern recognition and data analysis: AI and ML algorithms excel at processing and analyzing data generated from IT environments, like network traffic and performance metrics. Upon analysis, the algorithms can identify key patterns to uncover insights IT personnel may overlook. All in all, ML and AI can correlate seemingly unrelated variables to recognize trends, enabling better decision-making during IT process automation.
• Predictive analytics: As discussed earlier, predictive analytics forecast future outcomes using historical data and current trends. In IT operations automation, this capability is imperative for accurate decision-making. For example, predictive analytics can anticipate server failures or application performance issues. Using this foresight, the IT department can proactively schedule maintenance tasks, allocate resources, and establish safety protocols for better system reliability.
• Real-time decision assistance: AI and ML offer real-time decision support via continuous monitoring of IT systems. This constant monitoring offers key insights in the moment of need, which is particularly helpful in complex and dynamic IT environments where quick decisions are critical to maintaining optimal system performance. When implementing IT process automation, teams can use AI-driven monitoring tools to alert IT personnel during security threats and anomalies, facilitating efficient risk mitigation.
• Automating routine decision-making: Similar to routine IT processes, there are repetitive and routine decision-making processes that can be automated for more efficiency. These automated systems can follow pre-defined protocols to make accurate and consistent decisions without the risk of human error. For example, an AI-driven ticketing system can classify and prioritize incoming support requests based on severity and urgency, ensuring that vital issues get prompt attention.

Preparing and disseminating reports is a repetitive, yet crucial activity that many organizations undertake. Historically, this task has involved manual handling, with responsible IT personnel preparing reports and sending them via email. This also led to the process being more time-consuming and error-prone, and decreasing the organization’s flexibility to adapt to evolving market conditions.

IT process automation makes this process simpler and more efficient for changing market scenarios. For instance, if the IT team needs to prepare and send out weekly reports, they can simply create algorithms that automatically collect data from pre-established sources and combine them into reports. This significantly reduces human error when generating reports, and also allows the IT department to react quickly to market changes, freeing up time for other high-value activities.

Additionally, IT teams can employ predictive analytics via machine learning to forecast market changes. This way, more accurate reports or other required documentation can be prepared, equipping the company with the best possible measures to tackle unforeseen changes or issues.

As complex as data can be, companies must still put it into structured formats for high accessibility.

In such cases, OCR (optical character recognition) platforms can be of help, as they convert document images into machine-readable text information. However, any OCR platform, irrespective of how accurate it is, can only be of use if it ties up all the extracted pixel data to the current metadata when processing documents. This is the only way it can create a system of record, which is not always possible.

Using AI and ML for IT process automation poses an excellent solution to this hurdle as well. Companies handling a lot of documents can implement automation through algorithms that scan, read, digitize, and categorize them. If needed, IT teams can create an automated system to process documents and store them online for easy access. In turn, this saves a ton of time over manual scanning and processing, making it drastically easier to access important documents when needed.

While many companies still believe that IT cannot be automated, technological advancements are proving that it’s just a myth. IT process automation is certainly doable, and the earlier it’s implemented, the better. From streamlining repetitive IT processes to enabling better decision-making and robust anomaly detection, there are numerous benefits to automating IT operations, irrespective of which industry the organization belongs to.

At Turing, our IT consulting services combine innovative thinking and cutting-edge technologies to cover various business solutions, including IT process automation. Our team of experts brings in-depth industry knowledge and software development expertise to offer tailored services. Over 900 fast-scaling startups and Fortune 500 companies trust Turing with their engineering requirements, and so can you.

Book a call with us today to leverage our deep IT expertise and get expert consulting services tailored to your business goals.