Gone are the days when “cognitive” was only attached to the human mind. With the strong foothold of AI technologies, cognitive definition also applies to computers. In the digital world of AI automation, businesses are trying to utilize practices that may enhance operational efficiency for business outcomes. They are finding ways to decrease the human errors. This is where the emerging cognitive automation technology comes into the ground of different business processes. Let’s understand the process of cognitive automation and how it is beneficial for business progress!
What is Cognitive Automation?
Cognitive automation is the other name for Intelligence automation IA. This process mimics human behavior for decision-making and sorting out unstructured data by combining the cognitive level of Artificial Intelligence AI with RPA (robotic process automation) functions. The major purpose of cognitive automation for business processes is to automate repetitive tasks without utilizing manual labor help. This practice is effective to improve the operational efficiency free from human error.
Intelligence automation and AI: same-same, but different. Wanna know how? Check out our guide!
What are Examples of Cognitive Automation?
Although cognitive automation is a murky term, there is a range of terms that professionals use to elaborate on the different aspects of this automation process. Here are the possible variants of cognitive automation:
- Natural language processing (NLP)
- Sentiment analysis or ‘opinion mining’
- Contextual analysis
- Optical character recognition (OCR)
- Computer or machine vision
- Intelligent document processing (IDP)
- Document Automation
- Machine learning (ML)
- Predictive AI and Predictive analytics
- Intelligent virtual assistants
Examples of Cognitive Automation
Claims Processing: Processing claims is time-consuming and burdensome for insurance companies. Cognitive automation simplifies this by automating routine steps. It can instantly transfer data from completed or printed forms into the company’s database, reducing the need for manual work.
Document Processing Automation: Cognitive automation excels at converting unstructured documents into structured data, making it easier to integrate with other systems. These tools can also classify PDFs and trigger actions based on the document type. This streamlines workflows and brings significant efficiency.
How Does Cognitive Automation Work?
Cognitive automation works by leveraging several AI technologies to perform tasks that would typically require human intelligence. Imagine having a super smart digital assistant. That’s basically cognitive automation, or IA for short. It’s like mixing a robot that can follow rules (RPA) with an AI that can think and learn (artificial intelligence).
This smart assistant can handle all sorts of tasks, from boring paperwork to making tough decisions. Artificial intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and Robotic Process Automation (RPA) are the major automation systems that cognitive automation uses to read and analyze different complex data formats.
Cognitive automation is like teaching a computer to think like a human, but faster and without getting tired. By understanding information like we do, it can find patterns and solve problems. So, think of it as giving your business a brain boost for positive business outcomes!
RPA Vs Cognitive Automation
RPA and cognitive automation are key components of intelligent automation, which blends AI and RPA to enhance business processes. The main difference between RPA and cognitive automation is that RPA automates simple, rule-based tasks, while cognitive automation software uses AI to handle more complex tasks that require decision-making and learning. Let’s uncover the key difference between Robotic Process Automation and Cognitive Automation.
- Robotic Process Automation is only limited to automating repetitive tasks, while cognitive automation is a lot more versatile.
- RPA only works for structured data, while intelligent automation aligns the unstructured data to simplify the tasks.
- RPA gives quick ROI, while cognitive process automation requires time for workflow.
- RPA is good for quick wins while cognitive automation is best for long-term structured business outcomes.
- RPA is simple to utilize while intelligence automation is tough to manage (adaptable to changes)
Cognitive Automation and Business Progress
The term cognitive automation summarizes the use of machine learning technology for automation, taking over tasks that would otherwise need to be completed by human labor.
By streamlining their workflows beyond the capabilities of existing automation technology, businesses can achieve the next level of operational efficiency. As per McKinsey research, companies who implemented cognitive automation solutions can:
- Automate 50–70% of their tasks
- Reduce data processing times by 50-60%
- Reduce annual labor costs by 20–30
- Achieve Triple-digit ROI
Business Benefits of Cognitive Automation
Before leveraging intelligent automation for business outcomes, it is necessary to figure out which task to automate first. Task mining helps to determine what your business actually requires and which automation system would be the best for that specific task.
Enhanced Operational Efficiency
Cognitive automation solutions improve operational efficiency by automating routine, rule-based tasks. cognitive process automation works wonders for reducing human errors and eventually helping you utilize your team for more strategic activities. These systems can handle large volumes of work quickly and accurately resulting in reducing the time consumption.
Cost Savings
Automated systems especially cognitive automation solutions effectively reduce the labor cost. With intelligent automation, you can process complex tasks with more accuracy and timely.
Improved Customer Service
With cognitive automation, customer service becomes faster and more personalized. Automated systems powered by machine learning can analyze complex data to understand customer needs and deliver tailored responses in real-time, enhancing the overall customer experience.
Effective Knowledge Management
Businesses deal with vast amounts of knowledge-based information. Cognitive process automation can sort, classify, and organize this complex data, making it easier to access and use. This leads to better decision-making and smoother operations.
Scalable Workflow Automation
Cognitive automation is perfect for workflow automation, especially when handling large volumes of data. These solutions can adapt and scale as your business grows, ensuring processes remain efficient and manageable, no matter the workload.
Smart Decision-Making
Machine learning allows cognitive automation systems to learn from past data and make informed decisions. Unlike traditional rule-based systems, these smart solutions can adjust to new information, improving outcomes and making your business more agile.
Wrapping Up
Automation technology is the hottest concern for business owners. Whether you are thinking of increasing process efficiency or looking forward to leveraging automation to reduce manual labor, intelligent automation is the best choice. When implemented strategically, cognitive automation easily sorts out complex tasks and time-consuming repetitive business processes quickly. So, consider your business goals first and then implement the automation for positive business outcomes.
Frequently Asked Questions
What is an example of cognitive automation?
Chatbots for customer service support are a common example of intelligent automation with a blend of RPA. Voice power boats for telephonic conversations also utilize this automation process.
Is cognitive automation based on software?
Yes, intelligent automation is based on software. This automation technology utilizes AI, RPA, ML, data mining, text analytics, and NLP to mimic human cognitive power to perform complex tasks with efficiency.
What is the difference between RPA and cognitive automation?
RPA (Robotic Process Automation) automates simple, rule-based tasks without any decision-making or learning ability. Cognitive automation goes further by using AI and machine learning to handle complex tasks that require understanding, decision-making, and learning from data.
