We have traditionally utilized business automation to enhance productivity and eliminate repetitive and mundane tasks. However, with the emergence of artificial intelligence (AI), there are now instances where automation can handle analytical and even creative tasks that were previously carried out by humans.
In this article, I will guide you through the various types of business automation available today, providing you with real-life examples for each category. These include process automation, personal assistant automation, augmented AI, and autonomous AI, all aimed at streamlining business operations. Lastly, I will shed light on the latest trends in the automation landscape: hyperautomation and intelligent automation.
Business Automation – A Definition.
For business automation, I like the following definition from the International Society Of Automation (ISA).
“the creation and application of technology to monitor and control the production and delivery of products and services.”ISA
So automation is more than just technology. It is the “creation and application of technology …”. Also, information technology is a major enabler of automation. However, automation can leverage a wide range of technologies. This can include robotics, AI systems, telemetry and communications, electro-optics, process measurement and control, sensors, wireless applications, systems integration, test measurement, and much more. For more discussion on how automation differs from information technology and business automation benefits, see my article, What Is Automation? High Tech Ways To Better Replicate, Apply AI To Business Processes.
First, There Was Business Process Automation.
Automation powered by information technology has made business processes more efficient since the mid-twentieth century with the invention of the modern computer. This type of automation continues to thrive and is called process automation. Other terms for process automation include business process automation (BPA) and robotic process automation (RPA). Basically, process automation involves the use of technology to streamline simple, repetitive tasks. Examples include manufacturing assembly software applications and basic software for data entry and document management. Process automation has played a significant role in improving productivity and efficiency in various industries by reducing the time spent on mundane tasks. This allows employees to focus on more complex and value-added activities.
Below are two key definitions and examples when it comes to process automation. In many ways, BPA and RPA are similar. The difference is that BPA is usually focused on critical business processes versus RPA focuses on automated small repetitive tasks. Also, a point of clarity. The ‘R’ in RPA stands for “robotic” and in practice this automation is a software agent or bot and not a physical robot.
1. Business Process Automation (BPA) Definition And Example.
See below for a definition and example for BPA.
“Business process automation (BPA) is defined as the automation of complex business processes and functions beyond conventional data manipulation and record-keeping activities, usually through the use of advanced technologies. It focuses on “run the business” as opposed to “count the business” types of automation efforts and often deals with event-driven, mission-critical, core processes. BPA usually supports an enterprise’s knowledge workers in satisfying the needs of its many constituencies.”Gartner
BPA Example: One example of BPA is automating the accounts payable process. This involves receiving invoices from vendors, verifying their accuracy, and processing payment. By automating this process, businesses can save time and reduce errors. Invoices are received electronically and automatically routed to the appropriate department for review. The system verifies that the invoice matches the purchase order and that the price is correct. Once verified, the system generates a payment and sends it to the vendor. The system also updates accounting records to reflect the payment.
“Automation is cost cutting by tightening the corners and not cutting them.”Haresh Sippy
2. Robotic Process Automation (RPA) Definition And Example.
See below for definition and example of RPA.
“Robotic process automation (RPA) is a productivity tool that allows a user to configure one or more scripts (which some vendors refer to as “bots”) to activate specific keystrokes in an automated fashion. The result is that the bots can be used to mimic or emulate selected tasks (transaction steps) within an overall business or IT process. These may include manipulating data, passing data to and from different applications, triggering responses, or executing transactions. RPA uses a combination of user interface interaction and descriptor technologies. The scripts can overlay on one or more software applications.”Gartner
RPA Example: One example of RPA is automating data entry tasks. This involves extracting data from various sources, such as emails or spreadsheets, and entering it into a system. The software robot can be programmed to extract data from specific fields and enter it into the correct fields in the system. The robot can also perform validation checks to ensure that the data is accurate before entering it.
For more references on process automation, specifically BPA and RPA, see EnterprisesProject’ How to explain Robotic Process Automation (RPA) in plain English and Techopedia’s Automation. Also, see my article, Process Automation Technology: Its Value To Best Empower Decision Making In The Age Of AI in regard to how process automation supports business decision-making.
Second, Personal Assistant Automation Added.
Many of us have used personal assistants for years. In the past, some did not work too well. For example, Microsoft’s Office assistant, Clippy, was designed to help with MS Office productivity. It was introduced in 1995, but was soon scorned and ridiculed for providing its quirky, unsolicited advice. By 2007 Microsoft had phased it out. However, Now, things have changed. With the evolution of artificial intelligence (AI), assistant automation has taken a leap forward. AI personal assistant automation involves using AI algorithms to not only automate routine tasks but also learn from data and make decisions based on patterns.
Siri or Alexa are also personal assistance automation. They provide users with personalized assistance for various tasks in real-time. For example, personal assistant automation can include speech recognition software, which can transcribe spoken words into written text. Also, personal assistants can use predictive text algorithms, which can suggest words and phrases to a user as they type. Also with the rapid advancement of intelligent robots, every one of us may soon have a personal assistant humanoid to help us become more productive.
Today, AI Business Automation That Augments And Is Autonomous.
Now, businesses are starting to use AI automation in every area of their operations. Technologies include machine learning (ML), virtual and augmented reality, recommendation systems, self-driving cars, drones, and automated financial trading algorithms to name a few. AI automation primarily falls into two categories, augmented and autonomous. Below, I’ll provide definitions and examples of these types of AI automation. Also, I’ll discuss how the line between augmented AI and autonomous AI is getting more and more blurred. This is because AI continues to evolve where it continues to get better at replicating human intelligence. Also, businesses are gaining more confidence in using AI.
1. AI Augmentation Automation Definition And Example.
AI augmented automation is designed to augment, not replace the skills of humans. See definition and examples below.
Definition Of AI Augmentation Automation or “Augmented intelligence goes a step beyond assisted intelligence, as it involves a more active collaboration between humans and machines. In this case, the machine is not just a tool, but an active participant in the decision-making process.”Dirox
AI Augmented Automation Example. One example of AI augmentation is using machine learning algorithms to improve fraud detection in financial transactions. This involves analyzing large amounts of data to identify patterns and predict potential fraud. By using AI to analyze this data, financial institutions can identify fraudulent transactions more quickly and accurately than traditional methods. In this case, the machine is an active participant in the decision-making process, flagging transactions that are likely to be fraudulent for human review. The human can then make the final decision on whether or not to block the transaction.
2. Autonomous AI Automation Definition And Example.
Autonomous AI automation operates independently of humans. See definition and examples below.
Definition Of Autonomous AI Automation or “Autonomous intelligence involves machines that are capable of making decisions and taking action without human input. In this case, the machine is not just a tool or a collaborator, but a fully independent agent.”Dirox
Autonomous AI Automation. One example of AI is using autonomous drones for search and rescue missions. These drones are equipped with sensors and cameras that allow them to navigate difficult terrain and locate people in need of rescue. Once the drone has located the person, it can make a decision on the best course of action, such as dropping supplies or calling for additional help. The drone can take these actions without any human input, making it a fully independent agent.
3. The Blurring Line Between Augmented And Autonomous AI Automation.
As AI gets better mimicking higher-level human thinking skills, soon some AI functions that previously augmented humans may become autonomous agents. Currently, there are many cases where AI is augmenting less experienced humans to work at the same level as a highly skilled human. At this point, automation is not replacing the human, just augmenting their skill sets. However, soon many augmented AI automation implementations may become autonomous. This will happen because AI continues to get better and people gain confidence that the AI can do the same function better than human experts. Below are some examples where augmented AI automation is starting to combine with autonomous AI automation
AI Automation Examples – Augmented Vs Autonomous
Call Center. Today, augmented AI automation is prompting less experience call center agents with information to resolve customer issues. Next steps as AI evolves are to identify more use cases where AI agents take the lead in resolving issues better than an experienced call center agent.
Personal Transportation. Automation to include augmented AI automation has enabled less skilled Uber drivers to effectively compete against taxi drivers and taxi cab companies. How soon before it becomes commonplace for autonomous cars for hire?
Medicine. Augmented AI automation is coming into play for medical diagnostics such as x-ray diagnostics. How soon before autonomous AI agents are providing expert medical diagnostics?
Language Translation. Translation is already being used as autonomous AI automation as well as both augmenting and assisting us in day-to-day translations.
Writing. This is another case, where AI is assisting and augmenting humans today as well as acting as an autonomous agent in some cases. For example, I get an informative daily news email where an autonomous AI agent decides what is in the newsletter and summaries each news item.
For more detailed discussion on augmented and autonomous AI, see Brookings report, The Turing Transformation: Artificial intelligence, intelligence augmentation, and skill premiums, and Dirox’s Assisted, Augmented, And Autonomous Intelligence: What Differences?. Also, see my article, AI Impact On Business Decisions – Know How To Best Apply To Get The Most Benefits, for more on AI automation as it supports decision-making.
But Where Does Hyperautomation And Intelligent Automation Fit In?
From my perspective, the major components of automation are: process automation (RPA / BPA), virtual assistant automation, augmented AI automation, and autonomous AI automation. As I have previously stated, the boundaries between these terms can be blurred as in the case of augmented and autonomous AI automation. Additionally, some technology companies may brand different types of automation as a different name. For example, augmented intelligence is basically the same thing as augmented AI or augmented AI automation.
Also, there are many cases where businesses have a need for several types of automation to automate a complex business process. Or technology firms create a marketing term that encompasses several types of automation. In particular, there are many references today for terms like hyperautomation and intelligent automation (IA). As these two automation terms come up rather frequently, I have provided definitions for them below.
Definitions Of Emerging Automation Terms
“Hyperautomation is a business-driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms, including: artificial intelligence (AI), machine learning, event-driven software architecture, robotic process automation (RPA), business process management (BPM) and intelligent business process management suites (iBPMS), integration platform as a service (iPaaS), low-code/no-code tools, packaged software, and other types of decision, process and task automation tools.”Gartner
“Intelligent automation (IA), sometimes also called cognitive automation, is the use of automation technologies – artificial intelligence (AI), business process management (BPM), and robotic process automation (RPA) – to streamline and scale decision-making across organizations. Intelligent automation simplifies processes, frees up resources and improves operational efficiencies, and it has a variety of applications. For example, an automotive manufacturer may use IA to speed up production or reduce the risk of human error, or a pharmaceutical or life sciences company may use intelligent automation to reduce costs and gain resource efficiencies where repetitive processes exist. An insurance provider can use intelligent automation to calculate payments, make predictions used to calculate rates, and address compliance needs.”IBM
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