What is IT automation?

It enables businesses to create and implement automation workflows that reduce the time human workers spend completing time-consuming manual tasks. IT automation is an integral component of modern IT strategy and digital transformation initiatives.

Managing and coordinating geographically dispersed data centers and hybrid cloud architectures is a monumental workload. These environments often include virtualized networks, microservice applications, evolving security requirements, continuous software delivery cycles and other components characteristic of modern computer networking. What’s more, customer expectations are equally exceptional, with fast connections and minimal downtime now the operating norm. IT automation helps enterprises meet that challenge.

Automation software provides businesses with the agility and flexibility required to scale and allocate resources in accordance with real-time demand—an important part of achieving cost and performance goals. For example, developers can use automation scripts to automatically provision resources, configure and manage networks and cloud services, enforce security and accelerate DevOps process and service delivery.  

With modern IT automation solutions, teams can use a single platform to oversee and streamline workflows, jobs and batch processes (such as network configuration, user provisioning and patch management).

These solutions enable senior IT staff to dedicate their expertise to more strategic projects, rather than spending time testing scripts for routine workflows. Businesses can even leverage IT automation—and the increased bandwidth it provides IT professionals—to explore the impact of new technologies, such as generative AI and quantum computing.

In many different applications, IT automation can help enterprises scale more quickly, with fewer errors, and deliver services with greater speed and security. 

At its core, IT automation involves running scripts that define and execute a sequence of specific actions. These actions can be triggered manually, on a set schedule or by specific events (updating a database upon a certain event, for example). If a process is complex, IT teams can combine multiple scripts into a series to create a more intricate automation workflow.

Enterprise-level IT automation tools can automate a range of tasks, from cloud provisioning and application deployment to workflow automation and project management.

Let’s say a business brings on a new employee. When the new employee’s information is entered into the employee database, automated provisioning features can set up the user’s accounts; grant access to the appropriate SaaS platforms, applications and data; and initiate onboarding mechanisms.

Automation is even more powerful when enhanced with artificial intelligence (AI) and machine learning (ML), as is the case with AIOps. AI and ML features enable intelligent automation, where algorithms analyze structured and unstructured data to help automation tools assess, learn from and optimize automation workflows.

For instance, AI models can analyze user behavior and network traffic patterns to identify potential cyberthreats. If the model detects a threat, the automation platform initiates the necessary security protocols, including threat isolation, data backups and alert processes.

IT automation typically includes four key phases:

1. Analysis. Before teams can automate tasks and processes, they must first decide how best to use automation tools. This process includes consulting with administrators and stakeholders to understand business goals, thoroughly assess each task, and decide whether—and to what extent—jobs require or might benefit from automation.¹
   
   
2. Implementation. After they define automation tasks, IT staff can convert them into sets of instructions, such as a scripts or automation elements.
   
   
3. Integration. In this phase, teams test and validate the automation script to make sure that it triggers correctly and produces the intended results. And if the script passes validation, IT staff can integrate it into the broader automation platform for routine use.
   
   
4. Maintenance. Automation elements must evolve as tech stacks, resources and business needs change, so IT teams must regularly review and update them to help ensure optimal performance.

Any IT task that is repeatable is a strong candidate for partial or full automation. Automating these tasks enables businesses to maintain faster, more consistent, more efficient operations across use cases, technologies and environments (including containers, cloud and edge computing environments, DevOps pipelines and security practices).

Common applications of IT automation include:

Configuration management is a systems engineering process that helps businesses maintain the performance quality and functionality of a product, system or other IT asset throughout its lifecycle. Configuration management practices enable system administrators to track the state of assets (such as computer systems, servers and applications) so that teams can quickly identify issues, effectively manage change control, and prevent configuration drift and unnecessary downtime.

Businesses use configuration management tools to establish and maintain settings across computing environments, devices, workflows and more. Automating configuration processes enables IT teams to quickly deploy, update and retire infrastructure components, and improve system performance and security.

Provisioning refers to the process of setting up IT infrastructure, which includes hardware, networks, virtual machines and other resources, and making resources and data available to systems and users. Resource provisioning is more specific and refers to the allocation and configuration of the resources (such as CPU and storage) that an application or service needs to operate.

Both infrastructure and resource provisioning processes can be improved through automation. With automated provisioning, organizations can codify infrastructure and resource configurations, and establish repeatable workflows, making the provisioning process faster, more accurate and more flexible.

Infrastructure as Code (IaC) is a great example of automated provisioning. It uses a high-level descriptive coding language to automate IT infrastructure provisioning, so developers don’t have to manually provision and manage infrastructure components every time they want to develop, test or deploy a software application.

Network automation is a process that automates the configuration, management, testing, deployment and operation of physical and virtual networks and network devices. It reduces the amount of resources that developers spend managing and provisioning computing networks.

Automation tools can run processes such as network configuration and testing, resource provisioning, load balancing and workflow deployment that help IT teams maintain consistent service and implement quicker upgrades and deployments. 

Many enterprises use hybrid cloud architectures, which include on-premises data centers and public and private cloud environments. Cloud computing can offer superior orchestration, management and application portability, but maximizing its value often requires automation tools that can choose the optimal environment for each workload.

Today, 77% of businesses use hybrid IT architectures and need orchestration tools that work across every environment.² Cloud automation services help teams shift and orchestrate workloads between environments quickly (in real time, in some cases) and precisely.

Orchestration enables coordinated management of multiple automation processes, aggregating them into end-to-end workflows. Orchestration automation helps ensure that each task correctly triggers the next, reducing the need for manual intervention and enabling fully automated operations.

Whether businesses use continuous integration and continuous deployment (CI/CD) pipelines or more traditional approaches, modern-day software development depends on reliable automation. Deployment automation enables developers to automatically integrate, test and deploy code changes, creating fast feedback loops and accelerating software releases.

Automated deployment processes are especially important during product testing and release stages. However, automatic code and performance testing throughout the development lifecycle can help DevOps teams proactively boost code quality and identify issues early.

IT migration—which includes cloud migration, data migration, application migration, operating system migration and virtual machine (VM) migration—is the process of moving data and software between systems.

Migration projects can be complicated, because migration plans are typically tailored to specific organizational needs. Automating migration processes can help streamline and accelerate these projects.

Automated data synchronization—the process of automatically and continuously updating data records to ensure uniformity across network systems and devices—helps organizations maintain accurate and up-to-date data stores.

Without data synchronization tools, teams would have to rely on tedious manual data entry to propagate record changes throughout the IT environment. With syncing tools, teams can automate data handling processes, which helps businesses minimize data loss, streamline data management and take advantage of accurate, lightning-fast synchronizations.

IT security focuses on implementing measures to protect IT environments from cyberthreats, breaches and other forms of unauthorized access. Securing IT systems used to be a post-development consideration, but many businesses now prioritize security throughout the product lifecycle. 

Security automation uses software to automatically detect, prevent, analyze and remediate cybersecurity vulnerabilities. For example, businesses can use security automation to configure user access to applications and services through identity and access management (IAM) systems. Automated security not only shortens incident response times, but it also reduces configuration errors, compliance risks and mean time to repair (MTTR).

Developers can choose to adopt various types of IT automation, including:

BPA is a strategy that uses software to automate complex and repetitive business processes. These processes include “run the business” activities such as employee onboarding, new customer acquisition, order processing and inventory management. BPA differs from other automation types due to its complexity and its connection to multiple enterprise IT systems.

Because BPA is typically customized to an organization's specific needs, it’s an effective tool for streamlining the day-to-day operations that keep businesses running smoothly.

Continuous delivery helps development teams automate the process that moves software through the software development lifecycle and delivers applications. It enables developers to automatically deliver application code (updates, bug fixes and new features, for instance) to the appropriate infrastructure environment, and helps teams improve the safety and speed of software delivery.

Kubernetes—or K8s—containers are lightweight, executable app components that combine source code with all the OS libraries and dependencies required to run the code in any environment.

Kubernetes automation simplifies the process of configuring, deploying and maintaining Kubernetes containers, which underpin many of today’s enterprise applications.

Workflow automation is the process of automating the flow of documents, data and tasks across work-related activities. Using task management software, IT teams can automatically route tasks and business processes to teams, departments and workflows across the enterprise.

Automated workflows take task and process management out of the hands of human workers, enable businesses to streamline workflows, maximize worker productivity and increase overall businesses efficiency.

Intelligent automation, sometimes called cognitive automation, is the use of AI, natural language processing (NLP) and robotic process automation (RPA) to streamline and scale decision-making across organizations. For example, an insurance provider can use IA to calculate payments, estimate rates and address compliance needs.

Because IA relies on pre-trained AI models, ML algorithms and data analytics tools, it requires less data—and even less human intervention—to identify data trends and optimize automation workflows.

Robotic process automation (RPA)—also known as software robotics—uses application programming interfaces (APIs), scripts and intelligent automation technologies to complete repetitive tasks between enterprise and productivity applications.

Using rules-based software, RPA can autonomously complete jobs and run processes (such as extracting data, filling in forms and moving files) without human resources.

Front-end automation focuses on streamlining the configuration and maintenance processes that support a user interface (a website, for example). It enables teams to quickly complete tasks—such as user monitoring, website testing and data entry and extraction—and to create frictionless user experiences.

Backend automation, also called workload automation or API automation, leverages the connective nature of APIs to automate high-capacity backend systems and processes. It includes database processing and migration automation, file transfer automation, service discovery automation (which enables services and microservices to discover and interact with each other across a network) and testing automation for backend functions.

Backend automation enables businesses to assess and optimize backend functions so that applications remain fast, reliable and scalable.

Successful IT automation requires businesses to choose which manual processes and jobs to automate. They typically must fully map and analyze processes; standardize those processes and assess their impact, complexity and mission criticality; and continuously monitor automation workflows for optimization opportunities.

However, successful automation is also dependent on how developers choose to implement it. Businesses can choose from a range of strategies, including:

The terms IT automation and IT orchestration are often used interchangeably. And while both are invaluable tools for managing IT environments, they differ in their goals and purpose.

IT automation uses technology to handle individual tasks and processes automatically, such as performing backups, applying software updates and monitoring systems. Automating these routine tasks frees up valuable time and resources for IT teams.

Orchestration is the process of coordinating and managing several automated tasks—or entire workflows—in a unified way. The primary aim of orchestration is to enhance overall operational efficiency, reducing costs and increasing scalability.

In short, automation handles individual jobs, while orchestration coordinates multiple automated tasks to manage broader, more complex processes.

Enterprises seeking to deploy innovative IT automation tools have no shortage of options.

For example, with ML-driven automation tools developers can process large datasets, identify patterns in performance data, dynamically assign resources and scale IT environments in real time.³ They also help streamline DevSecOps—a shift-left practice that embeds security at the beginning of the development process—so developers can deliver more secure products.

Furthermore, AI agents are set to transform industry-specific operations, especially in engineering and finance, where they can offer context-aware automation insights and solutions.⁴ Agentic AI refers to autonomous, intelligence-driven systems that operate independently across various environments, without human input. IT teams can, for instance, use AI agents to track user data, and detect and investigate incidents of fraud.

The increasing use of AI agents underscores the value of customizable AI-powered tools for enterprises looking to tackle unique challenges, refine and automate their processes, and enhance personalization.

Hyperautomation is also trending for businesses that want to optimize enterprise IT management.⁵ Hyperautomation uses AI, ML and RPA to create a single, interconnected environment that fully automates business processes from end to end. Unlike traditional automation, which targets isolated tasks, hyperautomation connects and automates multiple, interrelated functions across an organization, creating a faster, more cohesive, more efficient automated system.

Self-service automation is becoming increasingly popular as developers attempt to empower different departments with automation capabilities.⁴ Today, 63% of businesses have more than 200 citizen automators.²

Low-code and no-code platforms are making automation accessible to nontechnical users, helping them design and manage automated workflows using intuitive, drag-and-drop tools. These self-service platforms accelerate automation and enable users to implement solutions without extensive IT support.

And with the help of automation fabrics (an approach that integrates various automation technologies and tools), developers can weave together fragmented elements into a seamless, unified automation structure, tightly aligning existing applications, workflows and data.

Automation fabrics address the issues associated with disconnected systems, isolated data and fragmented processes. Fragmented automation approaches can still be successful when applied to specialized apps that excel at individual functions, but they don’t translate well to large, dynamic IT environments where elements must work well together.

Automation fabric helps businesses establish a “central nervous system” for their IT architectures, helping ensure clear communication and smooth operations throughout the enterprise.

IT automation offers businesses of all sizes several significant benefits, including: