Top 10 IT Automation Trends in 2024

Hazal Şimşek

Workload automation

Updated on Mar 6

5 min read

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Table of contents

Common IT automation trends 1- Artificial Intelligence (AI) and Machine Learning (ML)2- Hyperautomation 3- No-Code/Low-Code Automation Domain-specific IT automation trends 4- Cloud Automation 5- Container Management 6- DevOps pipeline automation 7- Infrastructure as Code (IaC)8- ITOps management 9- Security Automation 10- Workload Automation and Intelligent job scheduling Further reading

Latest automation trends indicate that 20% of jobs will be automated by the late 2020s and 30% by the mid-2030s. ¹ IT automation is one area that enables organizations to automate repetitive tasks in IT operations, integrate systems and manage infrastructure by deploying various tools.

Figure 1 shows the upward trajectory of interest in IT automation since 2011, pointing out the gradual recognition of its potential its potential to drive operational efficiency.

In this article, we explore experts’ opinions and combine them with our research to comprehensively analyse the anticipated IT automation trends in 2023 so businesses can gain a competitive edge and unlock the full benefits of IT automation.

IT automation trends show that the interest in IT automation term on google search data has increased since 2011. — **Figure 1:** Interest in IT automation since 2011 on Google Trends ²

Common IT automation trends

Certain trends touch every aspect of IT automation and should be considered by all practitioners:

1- Artificial Intelligence (AI) and Machine Learning (ML)

90%of enterprise apps and software are expected to use AI by 2025. 61% of ML applications are in the automation market.

AI and ML technologies enable IT automation tools to learn and adapt autonomously, referred to as intelligent automation solutions. AI-powered IT automation tools can analyze data, make decisions, and automate complex tasks to optimize business processes and improve overall system performance. The ways AI/ML transforms IT automation efforts include:

Automated machine learning (AutoML) refers to automated processes that apply ML to real-world problems. AutoML can help data scientists in daily operations and increase efficiency. The autoML market is expected to grow by 43.7% until 2030.
ML in test automation: ML algorithms and techniques can improve various aspects of test automation, such as test case generation, test case execution, and test data management.
Intelligent document processing (IDP): allows businesses to automate document processes, including unstructured data such as PDFs and images, by leveraging natural language processing (NLP), optical character recognition (OCR), and robotic process automation (RPA).

2- Hyperautomation

Hyperautomation refers to automating end-to-end business processes, including structured and unstructured tasks, by combining AI/ML and multiple automation technologies, such as:

Business process automation (BPA)
RPA
Workflow automation
IT automation.

Almost 99% of IT decision-makers consider automation a critical factor in their digital transformation strategy. ³ Hyperautomation accelerates digital transformation, ensuring higher efficiency, productivity, and agility levels.

3- No-Code/Low-Code Automation

The low-code statistics show that 70% of new applications will use low-code or no-code technologies by 2025.

Low-code/ no code automation empowers non-technical users to create applications and automated processes without extensive programming knowledge. Low-code automation platforms provide visual interfaces and pre-built components that enable business users to drag and drop elements, define workflows, and configure automation logic.

These tools enable citizen developers to manage digital business initiatives, democratizing and streamlining the automation process with less automation spending.

Domain-specific IT automation trends

4- Cloud Automation

It is estimated that 40% of all enterprise workloads will be deployed in cloud infrastructure and platform services by the end of this year. ⁴

IT automation can streamline the orchestration and management of complex cloud environments while scaling and monitoring resources across multiple cloud platforms. It can also enable hybrid cloud automation through data, IT operations and compliance management automation.

5- Container Management

The rising adoption of cloud-native infrastructure will affect 75% of large enterprises to leverage container management by 2024. ⁵ Container management refers to revising, adding, or changing large quantities of software containers.

IT automation streamlines container management by:

Providing infrastructure resource for container environments, including virtual machines and cloud instances.
Automating the creation, testing, and storage of container images, ensuring consistency and reproducibility.
Configuring and orchestrating containerized applications and their dependencies.
Enabling dynamic scaling of container instances based on predefined rules or resource utilization.
Configuring automated monitoring systems to detect issues and trigger alerts or remediation actions.
Automating lifecycle management processes like updating container images, version rollout, and canary/blue-green deployments.

Therefore, increasing container management will lead to adopting digital technologies like IT automation tools.

Resource availability
Workload priorities
Dependencies
Service Level Agreements (SLAs).

6- DevOps pipeline automation

DevOps pipelines refer to processes and strategies to build, test and deploy software applications. DevOps pipeline involves code compilation, testing, artefact creation, deployment, and monitoring.

According to estimates, 40% of IT teams will adopt AIOps and MLOps in these pipeline stages to reduce downtime by 20% this year. ⁶ However, businesses need a systematic and automated approach to leverage AI and ML effectively.

IT automation or RPA software can help scale these advanced technologies by providing the necessary infrastructure, tools, and workflows. For example, IT automation can:

Provide infrastructure resources required for DevOps pipelines
Automate DevOps pipeline stages for a faster and error-free software delivery
Enable the automated configuration management of infrastructure and application settings to increase consistency in the work environment.
Automate testing activities to identify issues in application development
Proactively set up monitoring configurations, define alerting rules, and trigger notifications.

7- Infrastructure as Code (IaC)

IaC automates infrastructure provisioning and management through code and configuration files. Organizations can automate IT infrastructure deployment and configuration by defining infrastructure elements (e.g. servers, networks, and storage) as code.

IaC improves scalability, repeatability, and consistency in infrastructure management, enabling the rapid and efficient deployment of resources.

8- ITOps management

Organizations can reallocate 30% of ITOps management efforts into continuous engineering by 2024. ⁷ One way to reduce these efforts is to automate IT operations management with IT automation tools. Some of these tools include:

Data warehouse automation to improve data quality
Extract, Transform, Load (ETL) automation to streamline data integration
ITSM automation to assure compliance and service orchestration
Remote monitoring management (RMM) to enhance the endpoint support.

9- Security Automation

Cybersecurity becomes increasingly demanding for more organizations due to increasing cyberattacks. According to cybersecurity trends, at least 50% of companies will need to check the cybersecurity posture of their potential business partners by 2025.

IT automation can help enhance security automation through automated functionalities like:

Real-time threat detection
Incident response
Vulnerability management
Security policy enforcement.

10- Workload Automation and Intelligent job scheduling

IT automation trends indicate that the adoption of workload automation has risen exponentially. For example, survey respondents reported that they:

Embraced workload automation by 82%
Consider automation as the first two to digital transformation by 47%.

Workload automation manages various tasks and workflows and executes batch jobs and business processes across different systems and applications to ensure the timely and accurate processing of workloads. Intelligent job scheduling combines enterprise job scheduling capabilities with artificial intelligence and analytics to optimize task execution based on various factors, such as:

Discover WLA and Job scheduling tools in detail through our: