What’s the difference between software automation and artificial intelligence?

Automation involves the use of technology to automate repetitive and often menial tasks, such as data entry or form filling. The goal of automation software is to improve efficiency while reducing costs.  Even more, automation can help eliminate manual data-entry errors.

On the other hand, artificial intelligence involves developing algorithms that can learn over time, improving their performance as they are “trained.” The goal of AI is to create algorithms to perform complex tasks, such as processing language, recognizing things in images, or even making decisions. 

In this blog post, we will explore the differences between Automation and AI. We will also explore the benefits and risks of each. Finally, we will discuss the concept of automated artificial intelligence or “intelligent automation,” which combines the power of automation with the intelligence of AI. 

Whether you are a business owner looking to streamline your operations or a technology enthusiast interested in the latest trends, this post will provide valuable insights into the world of automation and AI.

What is “Automation”?

Automation is the use of technology to perform tasks that were historically performed by a person or a team of people. Automation process software can range from simple rule-based software that automates repetitive tasks to complex systems that can handle specific business processes within a workflow faster and more accurately than a person can. Automation software is great for handling data entry or form filling, as examples. 

One of the more commonly known and used forms of automation is Robotic Process Automation (RPA). RPA involves the use of software that can be programmed to perform repetitive tasks like those mentioned above. RPA can be used to automate processes across various departments, including finance, human resources, and customer service.

RPA runs on top of existing IT systems as a complementary automation solution; however, as a legacy “rules-based” automation technology, RPA has earned a reputation for being “fragile” and inflexible to maintain. 

RPA is good for what it does, but it can be difficult to update in a large enterprise where workflows change and evolve often. To learn more about RPA, watch this demo video to see where the legacy technology falls short. 

“Intelligent” Automation has been another emerging form of automation that combines software automation technologies, including RPA and artificial intelligence (AI). Traditionally, Intelligent Automation leverages artificial intelligence and RPA to automate some complex tasks with minimal human intervention. 

However, after experiencing some temporary “hype” for a short time, Intelligent Automation overpromised and underdelivered real value, leading to more disappointment than success. This is because legacy RPA vendors automate simple, repetitive screen tasks in orchestration with an AI made by a separate vendor, essentially creating an ineffective AI “bandaid” on top of an already “brittle” RPA implementation. 

This orchestration of automation solutions presented several challenges, and we covered this in-depth in another article on the 5 automation challenges, and how to overcome them.     

Benefits of automation

Automation offers several benefits to businesses, including improved efficiency, increased productivity, consistency, and accuracy. By automating repetitive tasks, businesses can reduce the risk of human error and free up time for employees to focus on more valuable tasks. As a result of automation, businesses can recognize benefits like reduced costs of labor, improved supply chain and logistics operations, and cost savings across a wide range of business expenses.

Moreover, automation can help businesses make more informed decisions through the analysis of vast amounts of data. This analysis helps uncover valuable business intelligence and insights, leading to better decision-making and ultimately drive business growth. Additionally, automation can improve the customer experience by providing faster and more accurate service, reducing wait times and increasing overall satisfaction. 

Automating repetitive and time-consuming tasks means businesses can repurpose their human resources to focus on more valuable activities that require human skills and intuition. Additionally, automation can help businesses reduce costs and improve customer satisfaction, making it a valuable tool for businesses of all sizes.

Risks of automation

While automation has many benefits, it also poses several risks. One of the main risks of automation is the displacement of jobs, as machines and robots take over tasks previously done by humans. This can lead to unemployment and income inequality, as people struggle to find new roles in the changing job market. 

Other risks of automation include dependence on technology, which can lead to disruptions in operations if there are any technical issues or malfunctions. Additionally, with this much data in the digital domain, there is a risk of cyberattack or data breach. 

Finally, as tasks become increasingly automated, there is a risk that people may become more isolated and disconnected from their work, which can lead to reduced job satisfaction and engagement. 

It’s important to note that many of these risks can be mitigated through proper planning and implementation of automation systems. Investing in training to help workers move into new roles and implementing cybersecurity measures can mitigate a few of the risks mentioned above.

Applications of automation

Automation has a vast range of applications in a wide range of businesses and industries. In manufacturing, robots are used to improve efficiency and productivity by assembling products, performing quality control checks, and packaging finished goods. In healthcare, automated artificial intelligence systems are used to streamline administrative tasks, reduce errors, and improve patient outcomes, such as scheduling appointments, processing insurance claims, and managing patient records.

In the finance industry, automation is used to automate tasks such as data entry, report creation, and even the reconciliation of accounts. In these cases, automation helps reduce errors and has the potential to drastically increase the speed of financial reporting. In customer service, automation can be used to answer frequently asked questions, handle routine inquiries, and schedule appointments, which helps improve customer satisfaction.

In logistics and supply chain management, automation can be used to improve the efficiency and accuracy of supply chain operations, such as tracking inventory, managing orders, and optimizing shipping routes. 

As automation technology continues to evolve, the way we think about processes, workflows, and office efficiency will evolve as well. To best leverage automation in your own business, it is crucial to understand the similarities and differences between Artificial Intelligence and Software Automation, including Intelligent Document Processing.

Understanding artificial intelligence

In its most basic form, Artificial Intelligence (AI) is a software simulation of human intelligence. AI involves the development of applications that can perform complicated, complex, and unique tasks that typically require human intelligence. Artificial intelligence in many cases is capable of learning, reasoning, problem-solving, and even decision-making.

There are several different subsets of AI, including machine learning (ML), natural language processing (NLP), and computer vision. Machine learning involves using algorithms to learn patterns in data and make predictions. Natural language processing allows a computer to take a text or voice recording, make sense of it, and generate human language as a response. Computer vision involves the ability of computers to interpret and analyze visual information, like recognizing something in a photograph or video.

Applications of AI

Artificial Intelligence is emerging in almost every field and sector. Recent advancements have made AI a must-have for industries like manufacturing or financial services. 

In finance, AI is increasingly being used to improve institutional security and prevent fraud. AI-powered systems continuously crunch massive amounts of financial data, looking for patterns or sets of anomalous behavior in an effort to predict stock prices and identify potential investment opportunities. AI can analyze transaction data to identify suspicious activities and prevent fraud. What’s more, invoice processing and check recognition are key use cases for financial service organizations and teams looking to leverage AI.

In the retail industry, AI is used to deliver a personalized shopping experience for customers and improve supply chain operations. AI technology can review the purchase data of a customer or cohort and use its findings to make personalized product recommendations or provide targeted advertisements and marketing messages. AI can also be used to optimize logistics and inventory management by using historical data to predict the necessary inventory levels for a coming wave of demand. 

AI can also be integrated with customer relationship management (CRM) tools or even an email server to automate customer requests and sort incoming emails based on intent classification. 

Risks of AI

AI has the potential to transform our world, but it also comes with risks. One of the main risks of AI is the potential for bias. This is why human-in-the-loop (or HitL) solutions can be so beneficial. When considering the use of AI, keep in mind that many tools can give your team interaction with and oversight over the AI in use. 

Automation Hero’s no-code environment provides an easy-to-use HitL interface that closes the gap between automation and people. Hero Platform_ enables multi-party reviews and approvals — turning randomized audits, compliance procedures, and quality assurance processes into streamlined collaborations between employees and departments. 

Differences between AI and automation

Automation and AI have similarities and differences. While automation is focused on automating tasks, AI seeks to create machines that can perform tasks that require human-like decision-making, analysis, and problem-solving skills. Automation is typically used for repetitive and routine tasks that can be easily programmed, while AI is applied to complex tasks that require human-like judgment and intelligence.

One major difference between automation and AI is their level of decision-making ability. Automation is typically rule-based and follows predetermined instructions, while AI can learn from data and make decisions based on that data. In other words, automation software operates on a set of predefined rules, while AI can make predictions and decisions based on the data it is presented with. Automation cannot learn from its mistakes or adapt to new circumstances, while AI can adjust its behavior based on new training data.

Another key difference is how much or how little human involvement is necessary for the technology to operate efficiently. Automation systems can operate without human supervision once programmed as long as they function correctly. The problem with legacy automation solutions like robotic process automation (RPA) is that they break easily and are difficult to maintain with evolving workflows. At the same time, some automation solutions offer a human-in-the-loop user interface that brings decision-makers into the workflow to approve or direct the automation.

Lastly, there is a difference in the types of tasks each technology is best suited for. Automation is great for repeatable and often menial activities, such as data entry or form filling. AI is better suited for complex tasks that require analysis and even decision making. Processing language or identifying things within a video or image is definitely best suited for AI.

While automation and AI share some similarities, they are fundamentally different in their capabilities, decision-making ability, level of human involvement required, and the types of tasks they are best suited for. 

Automation in your business

Clearly, automation and artificial intelligence are two related but distinct technologies with different capabilities and applications. Automation involves automating repetitive tasks, while AI involves machines performing tasks that require human-like decision-making, analysis, and problem-solving skills. While automation is rule-based and follows a predetermined set of instructions, AI is capable of learning from data and making informed decisions.

At AutomationHero, we specialize in a modern AI-driven automation technology called intelligent document processing. Automation Hero offers an intelligent document processing platform that can help enterprises improve their efficiency and productivity while reducing errors and costs. 

By automating document processing tasks such as data extraction, classification, and validation, Automation Hero can help businesses streamline their operations, reduce manual labor, and improve accuracy. In turn, organizations that work with Automation Hero can count on cost savings and improved productivity across the company. To learn more about how Automation Hero’s intelligent document automation fits into your business, contact us here.

Start improving your business processes with Automation Hero

When Allianz Italy decided to scale the use of AI, they quickly discovered that the best path to reach this goal was to keep business experts involved in the process. Learn how we helped Allianz create synergies between humans and artificial intelligence to reduce total claim processing time by 80% — cutting down manual tasks from 10 minutes to just two minutes per claim. 

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