What is intelligent automation?

Intelligent automation simplifies processes, frees up resources and improves operational efficiencies through various applications. For example, an automotive manufacturer may use IA to speed up production or reduce the risk of human error, or a pharmaceutical or life sciences company may use intelligent automation to reduce costs and gain resource efficiencies where repetitive processes exist. An insurance provider can use intelligent automation to calculate payments, estimate rates and address compliance needs.

Intelligent automation comprises 3 cognitive technologies. The integration of these components creates a solution that powers business and technology transformation.

• The most critical component of intelligent automation is artificial intelligence, or AI. By using machine learning and complex algorithms to analyze structured and unstructured data, businesses can develop a knowledge base and formulate predictions based on that data. This is the decision engine of IA.
• The second component of intelligent automation is business process management (BPM), also known as business workflow automation. Business process management automates workflows to provide greater agility and consistency to business processes. Business process management is used across most industries to streamline processes and improve interactions and engagement.
• The third component of IA is robotic process automation (RPA). Robotic process automation uses software robots, or bots, to complete back-office tasks, such as extracting data or filling out forms. These bots complement artificial intelligence well as RPA can leverage AI insights to handle more complex tasks and use cases.

This integration leads to a transformative solution that streamlines processes and simplifies workflows to ultimately improve the customer experience.

Intelligent automation platforms provide many benefits across industries as a result of using large data volumes, precise calculations, analysis and business implementation. The key benefits include the following:

• Reduce costs by augmenting the workforce and improving productivity: Automating systems and processes and using data analysis to safeguard accuracy can accelerate production. IA also enables companies to scale quickly without increasing risk, compromising quality, or putting a strain on the existing workforce. Business leaders are reaping the benefits of this capability through higher production yields and improved ROI.
• Improve accuracy through consistent processes and approaches to boost quality: The strength behind intelligent automation is the use of artificial intelligence to drive decision-making and bring a consistent approach to repetitive tasks.
• Improve customer experience: Providing a higher quality, more reliable product to market faster, or getting answers to queries faster (or immediately) provides a richer, more positive experience for the customer and thereby a competitive advantage for the company.
• Address compliance and regulations with confidence: Many industries are required to adhere to specific regulatory policies. Intelligent automation can leverage its task automation features to prove a more consistent approach to compliance.

Intelligent automation streamlines processes that were otherwise composed of manual tasks or based on legacy systems, which can be resource-intensive, costly and prone to human error. The applications of IA span across industries, providing efficiencies in different areas of the business.

• Automotive: The automotive industry is impacted greatly by the improvements manufacturers can make by using intelligent automation. With IA, manufacturers are able to more effectively predict and adjust production to respond to changes in supply and demand. They can streamline workflows to increase efficiency and reduce the risk of error in production, support, procurement and other areas. With the use of robots they are able to reduce the need for manual labor and improve defect discovery, providing a higher quality product to customers at a lower cost to the business. For example, a Volkswagen engine production plant in Germany uses “collaborative robots" that work with the production team to handle a physically demanding step in the engine-assembly process. This helps prevent injury, speed processes, promote accuracy and ease the physical burden on employees.
• Life Sciences: Drug production is highly regulated and requires precise calibration of equipment and measurement of product. It also requires a tremendous amount of data collection, collation, processing and analysis. A drug trial cannot be considered successful without trusted analysis and results. A manual approach could lead to calculation errors and take volumes of resources and considerable manpower to accomplish. In contrast, the production of Covid-19 vaccines in record time is an example of how intelligent automation provides automated processes that improve production speed and quality. Before AI and the resulting efficiencies, “…it used to take 40-plus scientists with doctorate degrees 25 years or more to discover a single marketable drug."
• Healthcare: The healthcare industry is using intelligent automation with natural language processing (NLP) to provide a consistent approach to data collection, analysis, diagnosis and treatment. The use of chatbots in remote healthcare appointments requires less human intervention and often a shorter time to diagnosis.
• Insurance: With IA, the insurance industry can virtually eliminate the need for manual rate calculations or payments and can simplify paperwork processing such as claims and appraisals. Intelligent automation also helps insurance companies adhere to compliance regulations more easily by ensuring that requirements are met. In this manner, they are also able to calculate the risk of an individual or entity and calculate the appropriate insurance rate.

The value of intelligent automation in the world today, across industries, is unmistakable. With the automation of repetitive tasks through IA, businesses can reduce their costs and establish more consistency within their workflows. The COVID-19 pandemic has only expedited digital transformation efforts, fueling more investment within infrastructure to support automation. As remote work also surges, roles will continue to evolve. Individuals focused on low-level work will be reallocated to implement and scale these solutions as well as other higher-level tasks.

Middle managers will need to shift their focus on the more human elements of their job to sustain motivation within the workforce. Automation will expose skills gaps within the workforce and employees will need to adapt to their continuously changing work environments. Middle management can also support these transitions in a way that mitigates anxiety to make sure that employees remain resilient through these periods of change. Intelligent automation is undoubtedly the future of work and companies that forgo adoption will find it difficult to remain competitive in their respective markets.