What is automation?

Automation is becoming increasingly ubiquitous in the modern world and has countless applications, including: enterprise applications such as business process automation (BPA), AIOps, and enterprise automation, industrial automation applications such as robotics used in automotive manufacturing, and consumer applications such as home automation.

Automation software and technologies are used in a wide array of industries, from finance to healthcare, utilities to defense, and practically everywhere in between. Automation can be used in all aspects of business functions, and organizations that wield it most effectively stand to gain a significant competitive advantage.

Organizations use automation to increase productivity and profitability, improve customer service and satisfaction, reduce costs and operational errors, adhere to compliance standards, optimize operational efficiency and more. Automation is a key component of digital transformation, and is invaluable in helping businesses scale.

Basic or task automation takes simple, routine tasks and automates them. Basic automation is used to digitize, streamline, and centralize manual tasks such as distributing onboarding materials to new hires, forwarding documents for approvals, or automatically sending invoices to clients.

Using automation instead of human workers to complete these tasks helps eliminate errors, accelerate the pace of transactional work, and free employees from time-consuming tasks, allowing them to focus on higher value, more meaningful work.

Process automation takes more complex and repeatable multi-step processes (sometimes involving multiple systems) and automates them. Process automation helps bring greater uniformity and transparency to business and IT processes.

Process automation can increase business productivity and efficiency, help deliver new insights into business and IT challenges, and surface solutions by using rules-based decisioning. Process mining, workflow automation, business process management (BPM), and robotic process automation (RPA) are examples of process automation.

Intelligent automation is a more advanced form of automation that combines artificial intelligence (AI), business process management, and robotic process automation capabilities to streamline and scale decision-making across organizations.

For example, virtual agents that are powered by technologies like natural language processing, intelligent search, and RPA can reduce costs and empower both employees and external customers. Such automation contributes to increased productivity and an optimal customer experience. AIOps and AI assistants are other examples of intelligent automation in practice.

The use of a repeated set of processes can increase productivity and efficiency and reduce human errors. Automation can drive business value in numerous areas, including:

Business automation refers to technologies used to automate repetitive tasks and processes to streamline business workflows and information technology (IT) systems. These solutions can be tailored specifically to the needs of an organization.

IT automation is the creation and implementation of automated systems and software in place of time-consuming manual activities that previously required human intervention. IT automation helps accelerate the deployment and configuration of IT infrastructure and applications and improve processes at every stage of the operational lifecycle.

Integration is the connection of data, applications, APIs, and devices across your IT organization to be more efficient, productive, and agile.

Formerly known as digital workers, AI assistants are software robots (or bots) that are trained to work with humans, or independently, to perform specific tasks or processes. AI assistants use a range of skills and AI capabilities, like machine learning, computer vision, and natural language processing.

Artificial intelligence for IT operations (AIOps) uses AI to improve and automate IT service and operations management. By integrating separate, manual IT operations tools into a single, intelligent, and automated IT operations platform, AIOps provides end-to-end visibility and context. Operations teams use this visibility to respond more quickly—even proactively—to events that if left alone, might lead to slowdowns and outages.

Artificial intelligence, or AI, is technology that enables computers and machines to simulate human intelligence and problem-solving capabilities. Machine learning, natural language processing, and computer vision are fields of artificial intelligence.

The chief automation officer (CAO) is a rapidly emerging role that is growing in importance due to the positive impact automation is having on businesses across industries. The CAO is responsible for implementing business process and IT operations decisions across the enterprise to determine what type of automation platform and strategy is best suited for each business initiative. The CAO works with a wide range of leaders across all business pillars such as IT, operations, and cybersecurity.

Computer vision is a field of artificial intelligence that uses machine learning and neural networks to teach computers and systems to derive meaningful information from digital images, videos, and other visual inputs—and to make recommendations or take actions when defects or issues are identified.

FinOps (or cloud FinOps), a portmanteau of finance and DevOps, is an evolving cloud financial management discipline and cultural practice that aims to maximize business value in hybrid and multi-cloud environments.

Green or sustainable IT puts a focus on creating and operating more efficient, environmentally friendly data centers. Enterprises can use automation in resourcing actions to proactively ensure systems performance with the most efficient use of compute, storage, and network resources. This helps organizations avoid wasted spend and wasted energy, which typically occurs in overprovisioned environments.

Hyperautomation is an approach that merges multiple technologies and tools to efficiently automate across the broadest set of business and IT processes, environments, and workflows.

Low-code and no-code refer to workflow software requiring minimal (low code) or no coding that allows nontechnical line-of-business experts to automate processes by using visual designers or natural language processing.

Machine learning (ML) is a branch of artificial intelligence and computer science that focuses on using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy. Applied to IT automation, machine learning is used to detect anomalies, reroute processes, trigger new processes, and make action recommendations.

Natural language processing, or NLP, combines computational linguistics—rule-based modeling of human language—with statistical and machine learning models to enable computers and digital devices to recognize, understand, and generate text and speech. Natural language processing is often used in modern chatbots to help chatbots interpret user questions and automate responses to them.