Types of automation

Automation is a broad term that can cover many areas of technology where human input is minimized. This can include everything from business-specific types such as: business process automation (BPA), IT automation, marketing automation and industrial automation. It also covers personal applications such as home automation. This article focuses on the main business specific automation areas of IT automation and BPA.

 

One way to think about the types of automation is breaking it down by the level of complexity – low to high.

Basic automation

Basic automation takes simple, rudimentary tasks and automates them. This level of automation is about digitizing work by using tools to streamline and centralize routine tasks, such as using a shared messaging system instead of having information in disconnected silos.

Examples include:

Business process management

Business process management (BPM) leverages software and services to provide total visibility into an organization’s business processes. BPM helps automate, monitor, optimize and improve business processes to increase efficiency and reduce costs.

Robotic process automation

The use of software bots to automate highly repetitive, routine tasks normally performed by knowledge workers. RPA bots complete tasks faster, so employees can perform higher-value work. Using RPA can reduce time to create, test and deploy new automation schemes from months to hours.

Companies are beginning to use business process management (BPM) libraries and workflow software with select robotic process automation (RPA) capabilities for faster implementation.

Process automation

Process automation manages business processes for uniformity and transparency. It is typically handled by dedicated software and business apps.

Examples include:

Process mining

Process mining uses algorithms to discover, validate and improve workflows. While business process management (BPM) collects qualitative data, process mining focuses on the quantitative side of processes and helps to show whether processes are working as they were intended to work.

 

Workflow automation

Orchestrates multiple business processes within operations and provides visibility into each step. Automating a manual workflow safeguards against potential disruptions or slowdowns, and directly involves business professionals in the design of business solutions.

Using process automation can increase productivity and efficiency within your business. It can also deliver new insights into business challenges and suggest solutions.

Integration automation

Integration automation is where machines are able to mimic human tasks and repeat their actions once humans define the machine rules.

One example is:


The digital worker

In recent years, people have defined digital workers (also called digital employees) as software robots that are trained to work in conjunction with humans to perform specific tasks. They have a specific set of skills, and they can be “hired” to work on teams.

Artificial Intelligence (AI) automation

The most complex level of automation is Artificial Intelligence (AI) automation. The addition of AI means that machines can “learn” and make decisions based on past situations they have encountered and analyzed.

One example is:

Automation in customer service

With breakthroughs in automation, companies can automate critical parts of the service function while still giving their customers a positive experience. Virtual assistants powered by artificial intelligence can reduce costs through automation while empowering both customers and human agents, creating the optimal end-to-end customer service experience.


Overview of IT automation

IT automation is using a system of instructions to execute a repeated set of processes — taking the place of IT work performed manually. Automated processes can increase IT productivity and efficiency — and reduce human errors. Recently the focus on IT automation has shifted to enhanced business productivity, greater innovation and faster speed to market.

Areas related to IT automation include:

Content management

Solutions that capture, store, activate, analyze and automate business content. Content management helps companies take unstructured and unavailable information and convert it into business insights.

Document processing

Solutions that combine artificial intelligence and deep learning to streamline the processing of business documents such as refund requests or contracts. This helps to eliminate repetitive manual tasks and reduce errors.

Document management

Solutions that capture, track and store information from digital documents. Document management can help organizations manage information more securely and eliminate many of their paper-based storage systems.

Workflow automation

Solutions that use rules-based logic to perform tasks with limited to no human interaction. Workflow automation can improve business productivity and allow companies to scale quickly.

Decision management

Solutions that model, manage and automate business decisions through machine learning. Decision management provides advanced analytics that organizations can use to provide better customer experiences.

Process mapping

Solutions that illustrate business processes through digital flowcharts. Process mapping can improve operations by identifying bottlenecks and enabling cross-organizational collaboration.


Automation use cases

Automation is dramatically impacting almost every industry. The following are examples of how innovative automation is transforming numerous organizations.

ProMare

“No ship has ever been built that can survive whatever the ocean could throw at it.” ProMare and IBM worked together to launch the Mayflower Autonomous Ship (MAS) which could change the future of ocean research. It may also drive sustainable advances for industries that operate on or near the ocean, such as shipping and logistics, oil and gas, and security/defense.

Carhartt

Discover how the clothing retailer is planning to use AI and automation so that replenishment orders happen automatically, without anybody touching anything.

Administrative Office of the Courts

See how this southeastern state used automation to eliminate repetitive tasks — and paved the way for its first pay increase in a decade for public defenders.

Turkcell

Learn how this company was able review more than 7.9 million contracts and ensure it was in compliance with new data privacy guidelines.

Mitsubishi

See how the organization’s infrastructure scales automatically, seamlessly and handles natural fluctuations in automotive sales volume.

Volkswagen

Discover how Volkswagen is creating the mobility ecosystem of the future.

 

CDG Prevoyance

Explore the way this company used process automation to deliver customer-centric services.


Automation trends

Where it began

The modern era of workflow automation began in about 2005 with the introduction of business process management (BPM) methodology and tools. In 2011, the release of Apple’s Siri sparked a new chapter of automation and AI-driven assistants. The trend was to move away from physical robots to computerized automation using AI software conceived in the late 80s and early 90s.

Trends we’re seeing now

Since then, we’ve seen advancements in:

Machine learning and workflow

Artificial intelligence (AI) is taking its strategic place in both operational and strategic business process management. New software enhancements to robotic process automation (RPA) will allow the technology to better observe and learn from human patterns optimizing — front-office and back-office experiences. Machine learning is poised to revolutionize workflow, helping to enable companies to trigger new processes, reroute running processes and make action recommendations based on predictions.

 

Hyperautomation

Gartner Research has coined the term “hyperautomation” to describe the merging of machine learning, packaged software and automation tools to rapidly maximize the number of automation processes in a business, and greatly increase productivity. Hyperautomation requires a range of cognitive and automation technologies coming together to deliver both the intelligence and the power to put the intelligence into action.

 

Intelligent automation

AI-based systems will be able to remember (automating future robot configurations) and reason (predictive and probabilistic processing) so that automated systems gain the ability to learn and interact.

 

Intelligent industrial robots

Robots will perform multiple tasks, make decisions, and work autonomously — including self-diagnostic and predictive maintenance capabilities.

 

Low-code or no-code workflow software

Workflow software requiring minimal or no coding will continue to be a strategic priority to make process automation more accessible to the entire organization — especially line of business.


AI and machine learning in automation

There are distinctions between terms:

Automation

Streamlines repetitive, instructive tasks to speed workflows. Automation encompasses everything from mundane activities, like keeping an icemaker filled, to important business functions, such as keeping a set schedule for server backups. Basic automation is programmed to perform a repetitive, usually mundane, task so humans don’t have to.

 

Artificial Intelligence (AI)

AI is programmed with logic and rules so that it can mimic human decision making. However, the only way AI can “learn” is if its programmers provide additional input. AI can be used in cybersecurity to detect threats such as subtle changes in user behavior or increased data transfers. AI can also be programmed to assist users on websites with chatbots that free up customer service reps from mundane questions that AI can easily answer.

 

Machine learning

An advanced form of AI. It can use data and experiences to “learn” over time without needing additional programming. Machine learning can recognize patterns on its own and make predictions. It uses large data sets to learn facial recognition, speech recognition and translations — and become more proficient with repeated exposure. Because machine learning software learns something new with every dataset, it can provide insights that are more sophisticated and informed.

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