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Distinguishing Between AI And Intelligent Automation

Recently, advances in both artificial intelligence and intelligent process automation, or just intelligent automation, in short, have paved the way for real-life solutions that can help companies save time and money. From computer programs that can sift through thousands of documents instantaneously to collaborative robots and the latest generation AI-powered customer service chatbots, automated intelligence is utilized for necessary but tedious, time-consuming assignments that would take employees much longer to finish and be more prone to error.

Subdivisions of artificial intelligence such as deep learning, machine learning, and natural language processing can assist organizations screen through their vast amounts of data and better handle company bottlenecks like customer service difficulties through the automation of the entire process. Nevertheless, AI can rarely be considered in isolation. Artificial intelligence is a technology, and it’s the way and the environment in which this technology is deployed that presents the opportunity to be genuinely transformative. For that reason, intelligent automation can further help companies by using existing data and automating analysis based on that data, ultimately assisting to enhance business operations and workflow and reduce redundant business processes.

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However, both AI and intelligent automation are commonly misunderstood, especially when it comes to artificial intelligence, where the hype spreads faster than the actual science. In this blog post, we’ll look at the differences between artificial intelligence and intelligent automation and how both will impact the future of work.

Artificial Intelligence

Nowadays, artificial intelligence is a technology that’s often talked about, yet many of its capabilities remain misunderstood, misinterpreted, and undefined, leading to unrealistic expectations. In data science, artificial intelligence relates to a fully functional artificial “brain” that’s intelligent, self-aware, and that can learn, understand, and reason over time.

And while advancements in what is referred to as artificial intelligence technologies have come a long way and will continue to do so, the reality of artificial intelligence, however, is very different from an ultra-smart computer that can learn and make choices like a human. In practice, artificial intelligence is a technology that runs a series of algorithms, searches through enormous databases, and does deep calculations to provide in-depth insights.

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The results of AI-powered software can help companies make decisions more efficiently and quickly depending on the application. For example, suppose you want to streamline your customer service services and rely more on sophisticated technology than your human workforce. In that case, artificial intelligence solutions like the Y Meadows model can be incorporated within your existing chatbot software to deliver services with more personalization, context, and relevance within the human-to-computer interaction. Furthermore, by perceiving any given customer’s input through continuous learning and complex algorithms thanks to machine learning and NLP, AI-powered virtual assistants and chatbots can provide them with a correct answer to their inquiry that will satisfy their request without assistance from a human operator.

Nonetheless, artificial intelligence is an extensive term on its own, and when used without further clarification, it may often fail to meet expectations. In reality, what’s possible today are actually subcategories or subsets of artificial intelligence, like natural language processing, machine learning techniques that comprise neural networks, or deep learning. For instance, NLP can understand and communicate human languages like regular people, while deep learning can use task-specific algorithms to help train a computer to classify inputs correctly.  

While artificial intelligence automation is highly beneficial for well-understood applications, current AI also has its limitations. Particular use cases and algorithms can definitely help companies encounter greater operational efficiency. Still, they can’t teach themselves entirely new tasks or make sense of data that hasn’t been taught.

Intelligent Automation

Intelligent automation refers to a bundle of technologies and advanced tools that address a task holistically and execute it not just automatically but as effectively as possible. Artificial intelligence is one of the tools in this bundle that makes intelligent automation an impactful resource in any company’s automation journey.  

Intelligent automation unites the powers of robotic process automation, artificial intelligence, and machine learning to improve end-to-end business processes promptly. In order to unleash the full capabilities of business process automation, intelligent automation uses cognitive technologies like neural networks and fuzzy logic. This makes unstructured data actionable through the extraction of meaningful information and allows robotic process automation through artificial intelligence to automate anomalous processes and complicated procedures. In other words, by addressing the totality of your given automation process, automated intelligence can bring efficiency to each step of your transformation journey.

Standard business automation processes mainly depend on predefined inputs and instructions, proving to be a limiting factor in terms of use cases. On the other hand, intelligent automation is an ever-improving answer for the complete automation eco cycle. By implementing groundbreaking technologies to work side by side, like robotic process automation and artificial intelligence, for example, automated intelligence can be utilized to automate almost any digital business process there is.

Intelligent automation is a self-learning, end-to-end automation process that minimizes errors and automation management. Within automation, artificial intelligence is utilized to understand and execute digitally automated functions based on meaningful information mined from raw, unstructured data like emails, chat conversations, or voice messages, for example. Thanks to AI, unstructured data that constitutes 80% of all business data is turned into meaningful information critical for ensuring end-to-end automation. The intelligent automation process is then analyzed with the help of artificial intelligence to distinguish patterns and predict future behavior. This data is then looped back into the automation process to enhance task execution and increase efficiency.

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Artificial Intelligence vs. Intelligent Automation: What’s The Difference?

Frequently we use intelligent automation and artificial intelligence interchangeably. Although AI and intelligent automation are indeed different technologies, there’s undeniably a strong intersection of commonality. Here’s how we think about it: as prediction is everywhere nowadays, artificial intelligence is now the world’s most incredible prediction tool. But, on the other hand, intelligent automation in both the physical form (e.g., autonomous cars, drones, robots) and software form (recommendation engines, customer service automation via the implementation of AI-powered chatbots or virtual assistants, trading software, etc.) often leverage AI to make a series of predictions that can lead to action, series of actions or combination of simultaneous activities. AI is an embedded technology, a driving force that makes other technologies intelligent and, in many cases, allows for automation of decisions, actions, and entire processes.

If you think about this in terms of intelligent physical automation, let’s say in the form of a robot, then the series of automated actions resulting from artificial intelligence predictions may be something like “lift, put down, go right, stop, go left, slow down.” Nevertheless, the software-based intelligent automation solution may create actionable steps for workers and systems in which they coherently work together to achieve process automation, such as the streamlining of a company’s customer service efforts. In other words, artificial intelligence is a considerable part or a component of intelligent automation. Therefore, it should be viewed as the most significant collaborator of automated intelligence and a prominent force of the automated future workplace.

The main point of dissimilarity between AI and intelligent automation is that while AI is about autonomous systems capable of mimicking human cognitive functions, the latter is all about building better, automated processes, both physical or software-based, by embracing and working alongside intelligent technologies like among others, artificial intelligence. Intelligent automation is a concept that’s truly a game-changer for organizations worldwide in 2021 and beyond.  

How Artificial Intelligence And Intelligent Automation Will Affect The Future Of Work

Any organization that hopes to serve its clients better and outcompete its fiercest rivals will have to re-examine its people, processes, and technology regularly. From big data and cloud computing to artificial intelligence automation, recent technological developments are undoubtedly revolutionizing the current business landscape and workplace for the better.

In fact, the “future of work” is arriving pretty fast, disrupting traditional business processes and ways of thinking along the way. What’s more, the future includes a great deal of automation. According to a report by the World Economic Forum (WEF), the rise of machines and automation would eliminate 85 million jobs by 2025 because many jobs will become fully automated by that time, redefining the very nature of work. Still, at the same time, the WEF predicts that 97 million new jobs will be generated, meaning an overall gain of 12 million jobs.

Photo from Deloitte

Automation has historically been restricted to tasks that are predictable, highly repetitive, and rules-based. Nonetheless, the latest advances in artificial intelligence and processing power have enabled increasingly complex activities to be automated as well. AI-driven software agents and systems can nowadays leverage natural language processing and machine learning to make more trustworthy judgments about what to do in an unknown situation and lengthen your employees’ capabilities, helping them become more productive and learn new business insights.

Let’s take the customer service industry as an example. By automating particular customer service tasks by incorporating AI-driven software like ours to resolve the simple tickets and streamline your entire customer service efforts, you can free up your human agents from dull, manual duties and allow them to concentrate on high-level, strategic activities that demand a uniquely human touch. This way, you’ll see significant improvements to the accuracy of your customer service processes while cutting costs. The bottom line, the cost of artificial intelligence automation software can be anywhere from $1,000 per month—a fraction of the salary of a well-trained human employee.

By all means, intelligent automation can’t arrive at your business overnight. Transitioning from an utterly human workforce to one in which humans and technology work side-by-side is a gradual process. Nevertheless, the vast majority of companies find that the benefits of intelligent automation far outweigh the effort demanded to incorporate it within their organization, so we suggest you start with a test run by implementing small automation projects and then move to a company-wide deployment to feel the full force of the “future of work” as you grow more comfortable.

Final Words

As we move toward an increasingly digitized world, intelligent automation represents a fantastic opportunity for companies to be more responsive to the economy's demands. Therefore, companies must include both AI and intelligent automation to ensure future success and understand how the difference and compliance between them can help them be more effective overall and deploy them in the right areas of the organization. Companies that will adopt intelligent automation solutions in their workflow now to support their existing human employees are putting themselves in an excellent position for later on.

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