“Business Automation AI Remake” isn’t just a catchy title; it’s the stark reality of our current landscape. We’ve moved beyond technology that merely empowers our processes to systems that now operate with startling autonomy. So, it is critical to look at Business Automation from a big picture perspective – where we are and how we got there. Moreover, what has worked, what’s hype, and what’s poised to redefine our future. With this knowledge we do not need to repeat the past, blindly following the hype or burying our heads in the digital sand.

Without a doubt, Business Automation has always been our ally in the quest for productivity and innovation. However, now, with recent advances in AI its evolution is accelerating. In this article, I’ll look at Business Automation, guiding you through its different categories and its evolution. In particular, I’ll highlight through examples both the hype and what works. Key categories include process automation, personal assistant automation, augmented AI, and autonomous AI agents.

“Maybe history wouldn’t have to repeat itself if we listened once in awhile.”

Wynne McLaughlin

The 5-Minute Supply Chain Tech Brief

1. Business Automation – A Definition.

Let’s start with a definition. I like the following business automation 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

What Is Automation? High Tech Ways To Better Replicate, Apply AI To Business Processes

So automation is more than just a technology product or piece of software. It is a capability that monitors and controls a process, namely, production and delivery. Also at its core, business automation’s major enabler is information technology. However, automation can also leverage a wide range of technologies. This can include robotics, telemetry and communications, electro-optics, process measurement and control, sensors, wireless applications, test measurement, and much more. For more discussion on how business automation differs from information technology, see my article, What Is Automation? High Tech Ways To Better Replicate, Apply AI To Business Processes.

Now, let’s go through the various types of business automation from conventional business process automation (BPA) to virtual assistants to various forms of AI automation.

“You’re either the one that creates the automation or you’re getting automated.”

Tom Preston-Werner

2. Process Automation: From Repetitive Tasks to Critical Business Processes and Beyond.

Process Automation to include Business Process Automation (BPA) and Robotic Process Automation (RPA), has been enhancing business efficiency since the mid-20th century. To best understand how process automation supports businesses, I’ll share with you the definitions for both BPA and RPA as well as provide you examples of these different types of process automation.

a. Business Process Automation (BPA) Definition And Example.

First, let’s start with BPA’s definition and an example.

“… the automation of complex business processes and functions beyond conventional data manipulation and record-keeping activities …”

Gartner

An example of BPA is an automated accounts payable process. In this case, the BPA would collate invoices from vendors, verifying their accuracy, and process payment. Lastly, the BPA could either mark the invoice, “OK to pay” or trigger a payment from the accounting system.

b. Robotic Process Automation (RPA) Definition And Example.

Next, below is a RPA definition and an example.

“… 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 …”

Gartner

For example, RPA can automate data entry tasks. For instance, this could involve extracting data from various sources, such as emails or spreadsheets, and entering it into a system. Also, the software robot could 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.

c. Process Automation and Beyond: BPA vs RPA, Decision Automation, and Leveraging AI.

Without a doubt, Business Process Automation (BPA) and Robotic Process Automation (RPA) share similarities. Thier primary distinction lies in their scope: BPA typically targets critical, end-to-end business processes, whereas RPA focuses on automating smaller, repetitive tasks. Also, to clarify, the “R” in RPA, standing for “robotic,” refers to software agents or bots, not physical robots.

Process Automation Technology: Its Value To Best Empower Decision Making In The Age Of AI

Beyond traditional Process Automation, Decision Automation is a specialized subset of Process Automation. At the same time, its core function isn’t the delivery of a product or service, but rather the automated generation of decisions or recommendations. Also, it is important to remember that historically Process Automation has relied on rules-based systems driven by static algorithms. However, with the rapid advancements in AI, modern Process Automation is increasingly leveraging artificial intelligence to automate more dynamic and complex business processes. Thus, Process Automation is moving beyond rigid rules to intelligent, adaptive solutions.

For more references on process automation, see below:

• Kevin Casey’s How to explain Robotic Process Automation (RPA) in plain English
• SC Tech Insights’ article, Process Automation Technology: Its Value To Best Empower Decision Making In The Age Of AI

“… modern Process Automation is increasingly leveraging artificial intelligence to automate more dynamic and complex business processes.”

3. Personal Automation: From Digital Assistants to AI Copilots.

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, things have changed. With the rapid evolution of artificial intelligence (AI), digital assistant automation has taken a leap forward from its quirky, rules-based algorithms. Now, AI personal assistant automation increasingly uses AI. In particular, it leverages advanced AI capabilities such as Large Language Models (LLM) and Natural Language Processing (NLP).

For example, Siri and Alexa are personal assistance automation. They provide users with personalized assistance for various tasks in real-time. In particular, 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. Further, the rise of LLMs are further augmenting the usefulness of virtual personal assistants. Lastly, with the rapid advancement of intelligent robots, every one of us may soon have a personal assistant humanoid to help us become more productive. For more on the quirky origins of AI and digital assistants, see my article, The AI Evolution: From Silly Novelty To Being Mainstream.

The AI Evolution: From Silly Novelty To Being Mainstream

“With the rapid evolution of artificial intelligence (AI), digital assistant automation has taken a leap forward from its quirky, rules-based algorithms.”

4. 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 AI agents to name a few. Moreover, 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.

a. Augmented AI Automation Definition And Example.

Below is a definition Of AI Augmentation (Augmented Intelligence) with an example:

“… 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 …”

Dirox

So, AI Augmented Automation is designed to augment, not replace humans. For example, AI augmentation can use machine learning algorithms to improve fraud detection in financial transactions. For instance, this can involve analyzing large amounts of data to identify patterns and predict potential fraud. As a result, 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.

b. Autonomous AI Automation Definition And Example.

See definition of Autonomous AI Automation (Autonomous Intelligence) and examples below.

The New AI Agent Business Specialist: You Need to Know Their Skill, Expertise, and Comparative Performance

“… 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

An autonomous drone for search and rescue is an example of Autonomous AI Automation. For instance, equipped with sensors and cameras, they navigate difficult terrain to locate people. Once found, the drone’s AI decides the best action, like dropping supplies or calling for help. In this case, the autonomous drone acts as a fully independent agent without human input. For more details on AI agent capabilities, see my article, The New AI Agent Business Specialist: You Need to Know Their Skill, Expertise, and Comparative Performance.

c. The Blurring Line Between Augmented And Autonomous AI Automation.

As AI’s cognitive abilities advance, tasks currently augmented by AI are poised to shift towards fully autonomous agents. Today, in many cases, AI presently enhances less experienced humans to perform at expert levels. Hence, it augments skills rather than replacing roles. However, this dynamic is rapidly evolving. In fact, this is evident by AI’s continuous improvement, coupled with growing public confidence in autonomous systems like self-driving cars. As a result, it is likely that many augmented AI implementations will soon become autonomous. Below are some specific examples.

AI Automation Examples – Augmented Vs Autonomous

• Call Center. Today, augmented AI automation helps less experienced call center agents with information to resolve customer issues. At the same time, AI is evolving rapidly. Now, in more and more cases, dynamic AI agents are autonomously taking the lead in resolving issues, surpassing even experienced human agents.
• Personal Transportation. Mobile phone apps to include augmented AI automation have enabled less skilled Uber drivers to effectively compete against taxi drivers and taxi cab companies. Now, autonomous cars for hire are hitting the road in major cities.
• Medicine. Augmented AI automation is coming into play for medical diagnostics such as x-ray diagnostics. The question now is how soon before autonomous AI agents are providing expert medical diagnostics?
• Language Translation. Also, there are many use cases today where AI is performing translation tasks autonomously as well as both augmenting and assisting us in day-to-day language 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. To illustrate, I can now get an informative daily news email where an autonomous AI agent decides what is in the newsletter and summarizes each news item.

“… many augmented AI implementations will soon become autonomous.”

More References.

For more detailed discussion on augmented and autonomous AI, see these references:

• Brookings report,  The Turing Transformation: Artificial intelligence, intelligence augmentation, and skill premiums
• Dirox’s Assisted, Augmented, And Autonomous Intelligence: What Differences?
• How Automation Supports Business Decisions: Business Decisions Made Better: First Automation, Then Data, Now AI Tech
• AI’s Impact on Decision-Making: AI Impact On Business Decisions – Know How To Best Apply To Get The Most Benefits

AI Impact On Business Decisions – Know How To Best Apply To Get The Most Benefits

Need help with an innovative supply chain solution that leverages emerging information technologies? I’m Randy McClure, and I’ve spent many years helping logistics organizations to make the most of new information technologies. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in new strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. If you’re ready to supercharge your supply chain or if you are a solution provider, let’s talk. To reach me, click here to access my contact form or you can find me on LinkedIn.

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