From process improvements to cost-savings and enhanced customer experiences, cognitive automation is rapidly transforming the way businesses operate. This cutting-edge technology goes beyond traditional rule-based automation by incorporating artificial intelligence and machine learning capabilities, enabling it to handle complex tasks that require understanding and interpreting unstructured data.
Introduction
In today’s fast-paced business environment, organizations are constantly looking for ways to improve efficiency, reduce costs, and deliver better value to their customers. One technology that’s making this possible is cognitive automation. It is a form of the process automation capabilities that leverages artificial intelligence (AI) and machine learning (ML) to perform tasks that would otherwise require human intelligence. Unlike traditional robotic process automation (RPA), which is limited to rule-based tasks, cognitive automation can handle unstructured data and learn from past experiences.
The potential cost savings with using cognitive computing and automation are substantial, and estimates suggest that organizations can achieve an average cost reduction of 15% to 40% in business process costs through the implementation of cognitive technologies.
What Is Cognitive Automation
Cognitive automation is an advanced form of automation that uses AI technologies such as natural language processing, machine learning, and semantic technology to simulate the decision-making process of a human brain. It allows machines to handle complex tasks that were previously thought to require human intelligence, or cognitive tasks like understanding natural language or recognizing patterns in unstructured data.
Cognitive Automation is gaining traction, and the global market is expected to reach a value of approximately $12.4 billion by 2026, reflecting the growing adoption of cognitive technologies in complex business processes.
How Does Cognitive Automation Work
Cognitive automation works by using AI technologies to understand, learn, and make decisions. It begins by processing unstructured data, such as text or images, using natural language processing or computer vision. The system then uses machine learning algorithms to identify patterns and learn from the data. Finally, it applies this learning to make informed decisions or predictions.
One of the key advantages of cognitive automation is its ability to handle exceptions. While traditional unattended RPA requires human intervention when it encounters a situation that it hasn’t been programmed for, cognitive automation and automated processes can adapt and learn from these situations, reducing the need for human intervention.
The job landscape is evolving with cognitive automation. By 2025, it’s projected that 85 million jobs may be displaced, but the same technologies are expected to create 97 million new jobs, indicating a dynamic shift in the skills required in the workforce.
AI Capabilities Of Cognitive Automation
The AI capabilities of cognitive automation extend far beyond those of traditional automation technologies. These include the ability to understand natural language, process unstructured data, identify patterns, learn from past experiences, and make informed decisions based on this learning. This enables cognitive and automation capabilities to handle tasks that are more complex and less rule-based than those that can be handled by traditional automation technologies.
For instance, ServiceNow’s cognitive automation solution was able to streamline the employee onboarding process at Asurion by handling labor-intensive tasks like account setup, email configuration, and system access provisioning. This saved the company considerable time and resources, demonstrating the potential of using cognitive automation solutions in improving operational efficiency.
The implementation of cognitive automation tools can lead to efficiency gains, with studies indicating that organizations leveraging cognitive technologies experience an average of 25% to 50% improvement in process execution times.
Advantages Of Cognitive Automation In Business Processes
Cognitive automation offers numerous advantages in business processes. First, it can significantly improve productivity by automating repetitive and time-consuming tasks, freeing up employees to focus on more strategic activities. Second, by handling exceptions and learning from them, it reduces the need for human intervention and the associated costs. Third, it can improve decision-making by providing insights derived from unstructured data that would be difficult to obtain otherwise.
Machine Learning, a key component of cognitive automation and predictive analytics, relies on vast datasets. It’s estimated that the amount of data globally is increasing exponentially, with predictions suggesting that the world’s data will reach 175 zettabytes by 2025, fueling the capabilities of cognitive systems.
Implementing Cognitive Automation In Your Organization
Implementing cognitive automation in your organization requires careful planning and execution. It starts with identifying the tasks that are suitable for the cognitive automation benefits, particularly those that are high-volume, repetitive, and time-consuming. The next step is to select the right cognitive automation platform that meets your organization’s needs. Then, you need to train the system using relevant data so that it can learn and improve over time. Finally, it’s important to continuously monitor and adjust the system to ensure optimal performance.
Setting Goals For Cognitive Automation
When implementing cognitive automation, setting clear and realistic goals is crucial. These goals should align with your organization’s overall strategy and objectives. For instance, if your goal is to improve operational efficiency, you might want to automate repetitive tasks that take up a lot of your employees’ time. On the other hand, if your goal is to enhance customer service, you might want to use cognitive automation to provide personalized recommendations or responses to customer inquiries.
Using Intelligent Technology To Achieve Business Outcomes
Cognitive automation is not just about automating tasks; it’s about using intelligent technology to achieve better business outcomes. By automating complex tasks, it allows your organization to scale operations without a proportional increase in costs. By providing insights from unstructured and structured data, it supports better decision-making. And by learning from past experiences, it continuously improves over time, leading to incremental improvements in performance.
Chatbots, a form of cognitive automation, are becoming prevalent. Industry reports suggest that by 2024, 85% of customer interactions will be handled without human intervention, showcasing the transformative impact of cognitive technologies in customer service.
The Future Of Cognitive Automation
The future of cognitive automation looks promising, with advancements in AI and machine learning technologies driving its capabilities to new heights. As these technologies continue to evolve, we can expect our cognitive applications of automation to become more intelligent, adaptable, and capable of handling even more complex tasks.
Advancements And Trends In Cognitive Automation
One of the key trends in cognitive automation is its growing integration with other technologies, such as Internet of Things (IoT) and blockchain. These integrations can further expand the capabilities of cognitive automation, enabling it to handle tasks that involve data processing time interacting with physical devices or secure transactions.
Another trend is the increasing use of cognitive automation in industries like finance, healthcare, and retail. As these industries deal with large volumes of unstructured data, they stand to benefit greatly from the ability of cognitive automation to process this data and extract valuable insights.
Staying Ahead Of Competitors With Cognitive Automation
In today’s competitive business environment, staying ahead of competitors is crucial. Cognitive automation can provide a competitive edge by improving operational efficiency, reducing costs, enhancing customer service, and supporting better decision-making. By implementing cognitive automation, your organization can not only stay competitive but also set a new standard in your industry.
The integration of Natural Language Processing (NLP) in cognitive automation is expanding. Research indicates that NLP algorithms can achieve natural language understanding at a human level, with some models achieving a performance rate of over 90% accuracy in language-related tasks.
Final Note
Cognitive automation represents a major leap forward in the evolution of automation technologies. By combining AI and machine learning capabilities, it enables organizations to automate complex tasks and improve operational efficiency. The benefits of cognitive automation are numerous, from increased productivity and cost savings to enhanced decision-making and customer experiences.
As technology continues to advance, the future of cognitive automation looks promising. With advancements in AI and machine learning, we can expect cognitive automation to become even more intelligent and capable of handling increasingly complex tasks. By embracing cognitive automation, organizations can stay ahead of competitors and drive innovation in their industries.
Last Updated on December 3, 2023 by Parina
