There was a time when the word ‘cognition’ was synonymous with ‘human’. The original definition of cognitive is “being conscious of mental activities such as thinking, reasoning, remembering, imagining, learning words and using language.” It’s astounding to believe that with our technological leaps in artificial intelligence (AI) and generative AI, that definition can now be applied to computers.

Well, almost.

Organizations continuously seek innovative ways to streamline complex business processes, enhance productivity and gain the competitive advantage. With these advances in technology, a solution intersecting AI and automation has emerged: cognitive automation, also known as intelligent automation (IA). It harnesses the power of AI to automate complex, traditionally human tasks, bringing digital transformation to business operations.

Cognitive automation has the potential to completely reorient the work environment by elevating efficiency and empowering organizations and their people to make data-driven decisions quickly and accurately. But how is it done? That’s what we’re here to explore.

What is Cognitive Automation?

Cognitive automation is another name for IA. It mimics human behavior and intelligence to facilitate decision-making, combining the cognitive ‘thinking’ aspects of artificial intelligence (AI) with the ‘doing’ task functions of robotic process automation (RPA).

Cognitive automation performs advanced, complex tasks with its ability to read and understand unstructured data. It has the potential to improve organizations’ productivity by handling repetitive or time-intensive tasks and freeing up your human workforce to focus on more strategic activities.

How does cognitive automation work?

Cognitive automation, or IA, combines artificial intelligence with robotic process automation to deploy intelligent digital workers that streamline workflows and automate tasks. It can also include other automation approaches such as machine learning (ML) and natural language processing (NLP) to read and analyze data in different formats.

Like our brains’ neural networks creating pathways as we take in new information, cognitive automation makes connections in patterns and uses that information to make decisions.

What are examples of cognitive automation?

There are various cognitive applications to IA, including:

• Natural language processing (NLP)
• Sentiment analysis or ‘opinion mining’
• Contextual analysis
• Computer or machine vision
• Optical character recognition (OCR)
• Intelligent document processing (IDP)
• Document Automation
• Machine learning (ML)
• Predictive AI and Predictive analytics
• Intelligent virtual assistants

How does cognitive automation apply to different industries?

IA or cognitive automation has a ton of real-world applications across sectors and departments, from automating HR employee onboarding and payroll to financial loan processing and accounts payable.

The scope of automation is constantly evolving—and with it, the structures of organizations.

What is sentiment analysis?

Sentiment analysis or ‘opinion mining’ is a technique used in cognitive automation to determine the sentiment expressed in input sources such as textual data. NLP and ML algorithms classify the conveyed emotions, attitudes or opinions, determining whether the tone of the message is positive, negative or neutral.

What’s the Difference Between RPA and Cognitive Automation?

AI and ML are fast-growing advanced technologies that, when augmented with automation, can take RPA to the next level. Traditional RPA without IA’s other technologies tends to be limited to automating simple, repetitive processes involving structured data.

RPA imitates manual effort through keystrokes, such as data entry, based on the rules it’s assigned. On its own, RPA can do a lot. But combined with cognitive automation, RPA has the potential to automate entire end-to-end processes and aid in decision-making from both structured and unstructured data.

RPA provides tactical quick wins, whereas cognitive automation solutions provide a long-term strategic advantage through the technology’s ability to scale quickly across departments and throughout the organization, adapting and learning as the digital workers carry out their work.

What Are the Benefits of Cognitive Automation?

To reap the highest rewards and return on investment (ROI) for your automation project, it’s important to know which tasks or processes to automate first so you know your efforts and financial investments are going to the right place.

Task mining and process mining analyze your current business processes to determine which are the best automation candidates. They can also identify bottlenecks and inefficiencies in your processes so you can make improvements before implementing further technology.

Improved efficiency and productivity

Cognitive process automation can automate complex cognitive tasks, enabling faster and more accurate data and information processing. This results in improved efficiency and productivity by reducing the time and effort required for tasks that traditionally rely on human cognitive abilities.

Operations optimization

Since cognitive automation can analyze complex data from various sources, it helps optimize processes. With their various layers of intelligent technology, digital workers can improve operations by automating repetitive tasks, providing insights, helping with decision-making, streamlining workflows, extracting data and continuously improving and adapting as they scale.

Enhanced decision-making

By augmenting human cognitive capabilities with AI-powered analysis and recommendations, cognitive automation drives more informed and data-driven decisions. Its systems can analyze large datasets, extract relevant insights and provide decision support.

Scalability and consistency

With automation, vast amounts of data are analyzed consistently and at scale. Cognitive automation eliminates the limitations associated with human cognitive abilities, such as fatigue, inconsistency, limited capacity and even holidays and sick days.

Accuracy and error reduction

Training AI under specific parameters allows cognitive automation to reduce the potential for human errors and biases. This leads to more reliable and consistent results in areas such as data analysis, language processing and complex decision-making.

Cost savings

By automating cognitive tasks, organizations can reduce labor costs and optimize resource allocation. Automated systems can handle tasks more efficiently, requiring fewer human resources and allowing employees to focus on higher-value activities.

Customer experience and engagement

Intelligent virtual assistants and chatbots provide personalized and responsive support for a more streamlined customer journey. These systems have natural language understanding, meaning they can answer queries, offer recommendations and assist with tasks, enhancing customer service via faster, more accurate response times.

Innovation and insights

The human brain is wired to notice patterns even where there are none, but cognitive automation takes this a step further, implementing accuracy and predictive modeling in its AI algorithm.

Cognitive automation can uncover patterns, trends and insights from large datasets that may not be readily apparent to humans. With these, it discovers new opportunities and identifies market trends.

Regulatory compliance and risk management

Cognitive automation maintains regulatory compliance by analyzing and interpreting complex regulations and policies, then implementing those into the digital workforce’s tasks. It also helps organizations identify potential risks, monitor compliance adherence and flag potential fraud, errors or missing information.

If your organization wants a lasting, adaptable cognitive automation solution, then you need a robust and intelligent digital workforce. That means your digital workforce needs to collaborate with your people, comply with industry standards and governance, and improve workflow efficiency. 

Enhanced data analytics

IA is capable of advanced data analytics techniques to process and interpret large volumes of data quickly and accurately. This enables organizations to gain valuable insights into their processes so they can make data-driven decisions. And using its AI capabilities, a digital worker can even identify patterns or trends that might have gone previously unnoticed by their human counterparts.

Where’s It All Headed?

Cognitive process automation is about doing things faster: thinking, learning and adapting. And it’s something organizations need to get better at utilizing if they’re going to stay ahead of their competitors.

How do you get there?

When implemented strategically, intelligent automation (IA) can transform entire operations across your enterprise through workflow automation; but if done with a shaky foundation, your IA won’t have a stable launchpad to skyrocket to success.

When introducing automation into your business processes, consider what your goals are, from improving customer satisfaction to reducing manual labor for your staff. Consider how you want to use this intelligent technology and how it will help you achieve your desired business outcomes.

Need help reaching your goals? Check out the SS&C | Blue Prism® Robotic Operating Model 2 (ROM™2) for a step-by-step guide through your automation journey.