Artificial Intelligence (AI) and Intelligent Automation (IA) are two terms that have become ubiquitous in today’s world. Although they are often used interchangeably, they are distinct concepts, each with its own advantages and disadvantages. Unfortunately, there is a growing tendency to use the term “AI” as a catch-all phrase that obscures the fact that we’re not really doing AI. What we are really using today is a practical application of IA. In this blog, I’ll tell you why AI is more a buzzword than the breakthrough we all hoped it would be.

Buzzword: an important-sounding usually technical word or phrase often of little meaning used chiefly to impress laymen¹.

Comparing AI to IA

Artificial Intelligence refers to the simulation of human intelligence in machines that are designed to think and learn like humans. It encompasses several subfields, including machine learning, natural language processing, and computer vision. It enables machines to perform tasks that typically require human intelligence, such as understanding language, recognizing patterns, and making decisions. The ultimate goal of AI is to create systems capable of autonomous reasoning and problem solving.

Intelligent Automation combines Artificial Intelligence technologies with automation tools to improve business processes, on the other hand. It integrates elements such as robotic process automation (RPA), business process management (BPM), and AI to streamline and scale decision-making across the enterprise. Unlike traditional automation, which handles repetitive tasks based on predefined rules, Intelligent Automation can manage complex processes by learning and adapting over time.

Distinguishing The Concepts

While Artificial Intelligence focuses on creating systems that simulate human intelligence, Intelligent Automation leverages these AI capabilities to automate end-to-end business processes. In essence, AI is the brain that provides cognitive functions, while Intelligent Automation is the body that executes tasks using AI’s intelligence. This distinction is critical; although Artificial Intelligence is a component of Intelligent Automation, not all AI applications result in automation, and not all automation requires advanced Artificial Intelligence.

For example, a chatbot that uses Artificial Intelligence to understand and respond to customer queries is an example of AI. However, when this chatbot is integrated into a customer service workflow to handle routine inquiries without human intervention, it becomes part of an Intelligent Automation system. This integration allows companies to automate complex workflows and tasks, increasing efficiency and reducing operational costs.

There is a very fine line between AI and IA. A line that often blurs in front of our eyes. Instead of sharpening our vision, we let it overwhelm us and drift with the tide we so eagerly call AI.

The Role Of AI/IA In Enterprise Architecture

Enterprise Architecture is the structured planning and alignment of IT infrastructure with business goals. Integrating Artificial Intelligence and Intelligent Automation into Enterprise Architecture can lead to significant improvements in efficiency, agility, and innovation.

For example, AI’s ability to analyze massive amounts of data enables organizations to gain insights that inform strategic decisions. AI can predict market trends, customer behavior, and operational bottlenecks, allowing organizations to proactively address challenges and seize opportunities. This data-driven approach improves the accuracy and speed of decision making. Today, we are far from using AI as intended.

Intelligent Automation automates and optimizes business processes by combining AI with automation tools. This integration results in increased efficiency and reduced operating costs. For instance, Intelligent Automation can streamline supply chain operations by automating inventory management, order fulfillment, and logistics, resulting in faster turnaround times and fewer errors. This is what we see happening in the world today.

The Misconception Of Labeling IA As AI

In recent years, the term “AI” has been widely used as a marketing buzzword, often applied to technologies that do not have true AI capabilities. This phenomenon, sometimes referred to as “AI washing,” involves branding traditional automation or data processing systems as AI in order to capitalize on the term’s popularity. Such practices can mislead consumers and businesses, leading to inflated expectations and potential disillusionment with the technology.

It’s like walking through Trafalgar Square and seeing nothing but AI neon signs.

In today’s market, there’s a tendency to label all automation technologies as Artificial Intelligence, leading to confusion. Understanding the distinction between AI and Intelligent Automation can help organizations set realistic expectations and choose the right solution for their specific needs.

An Outlook To The Future

We would all like to implement and use AI to its full potential. In reality, however, we are still in the phase of automating existing processes, trying to get what we all call AI to save us time and money. Basically, we are implementing Intelligent Automation, not Artificial Intelligence.

Let’s say a financial services company implements an AI-powered analytics platform within its Enterprise Architecture to improve fraud detection. The system would analyze transaction data in real time and identify anomalies that could indicate fraudulent activity. By integrating this AI solution, the company could reduce fraud-related losses and improve customer confidence. This is a nice view of the future, but not our current reality.

So What Is Our Current Reality

Our current reality is this. A manufacturing company takes an AI approach to streamline its procurement process. By integrating RPA with AI-driven data analytics, the company automates supplier evaluation, purchase order creation, and invoice processing. This integration results in a 30% reduction in procurement cycle time and significant cost savings. Excellent results, so nothing to complain about. Well, except maybe for the fact that it’s not AI, it’s Intelligent Automation.

Conclusion

While the terms AI and IA are often used interchangeably, they are distinct concepts with unique applications. AI focuses on simulating human intelligence, while IA combines AI with automation technologies to streamline business processes. Recognizing this distinction is critical for organizations that want to leverage these technologies effectively. Incorporating AI and IA into the Enterprise Architecture can lead to improved decision making, streamlined operations, and enhanced customer engagement to drive business success in today’s competitive landscape.

Artificial Intelligence has become a ubiquitous term in today’s technology landscape, often used to describe a wide range of systems and processes. However, this broad application has led to confusion, particularly in distinguishing AI from Intelligent Automation. While these terms are related, they are not synonymous. In fact, many solutions labeled as AI are more accurately described as IA. This conflation can obscure the unique characteristics and benefits of each, making it imperative to clarify their differences and understand the implications of their misrepresentation.

1. Buzzword definition ↩︎