Digitalization through Intelligent Automation

Intelligent Automation (AI) is an approach to business automation that combines advanced technologies such as Artificial Intelligence (AI)  and Robotic Process Automation (RPA)  to automate and improve business processes. This technology uses machine learning algorithms to learn from data and make autonomous decisions, continuously improving its ability to perform tasks. AI can help streamline business processes, reduce costs and improve the customer experience. In addition, AI can be used for complex tasks, such as natural language processing and computer vision, that are beyond the capabilities of traditional RPA.

What is meant by Intelligent Automation? We have already partly explained it: Intelligent Automation is the use of automation technologies, artificial intelligence (AI), business process management (BPM) and robotic process automation (RPA) to simplify and scale decision making within organizations.
In the business process organization, process management is a vital element for business growth.
According to KPMG, Intelligent Automation (IA) and Data & Analytics (D&A) are at the top of companies' strategic agenda.
Intelligent automation aims to streamline processes, free up resources and improve operational efficiency. It is not directed toward a single application but to a variety of fields and declinations.
In order to achieve the goal, different departments and human resources are involved in the process, which will have to work independently but in synergy, while meeting deadlines.

Intelligent Automation is perceived by business leaders as a key tool for facilitating business growth and represents, through the use of data, a great opportunity for the improvement of high-value business activities such as the customer experience.

Companies around the world are turning their attention to intelligent automation to empower the digital workforce.

In fact, post pandemic era, more and more people are working remotely, and intelligent automation has the potential to expand and investigate new ways in which companies operate.

Intelligent Automation is not to be confused with RPA. In fact, the former covers a broader scope of work than RPA: it augments and enhances traditional fixed rule-based automation by inserting the ability to express decisions to deliver results with maximum efficiency.

Intelligent automation consists of three useful technologies to create a solution that fuels business and technology transformation toward a digital future.

1. The AI decision engine, which is the most critical component of automation. In essence, companies using machine learning and complex algorithms to analyze structured and unstructured data can develop a knowledge base and make predictions based on that data. 
   
2. The second component of intelligent automation is business process management (BPM), also known as business workflow automation. BPM is a great value-add for cost- and time-efficiency of work. This is possible through continuous process reengineering. In fact, business management suites have been particularly useful in speeding up digital transformation strategies and the achievement of business goals.
   
   
3. The third component of AI is robotic process automation (RPA). RPA targets tasks that are simple and routine but contribute largely to business optimization, enabling human resources to create new value by leveraging their professionalism and skills in more strategic tasks where human expertise finds application. These bots integrate artificial intelligence, and the RPA can leverage AI information to handle more complex tasks and use cases.

The integration of these three components creates a transformative solution that streamlines processes and simplifies workflows to improve the customer experience.

Intelligent automation platforms offer many advantages in all areas through the use of big data.  Key benefits include:

1. Reducing costs by increasing the workforce and improving productivity: automation of systems and processes and the use of data and analytics ensure accuracy and enable faster production. AI also is a scalable technology this means business is optimized without increasing risk, compromising quality or putting a strain on the existing workforce. 
   
   
2. Improve accuracy through consistent, quality-enhancing processes and approaches: the strength of intelligent automation is the use of artificial intelligence to drive decision making and bring a consistent, data-driven approach to repetitive tasks.
   
   
3. Improving the customer experience: being able to deliver a higher quality and more reliable product to the market in a shorter time also allows us to get responses from the market faster and thus a competitive advantage for the company.
   
   
4. Better coordination of actions if we combine it with BPM to RPA the intelligent Automation, it will be possible to coordinate work between robots, people and systems. 
   
   
5. Freeing employees from routine tasks so they can work in more efficient areas with greater business value.
   
   
6. Agility and speed, as it helps speed up data processing and enables continuous improvement of business processes.
   
   
7. Simplifies document management, With automated processes you make document management and maintenance activities simple and secure. In fact, manual data management is time-consuming and increases the possibility of errors.

With the understanding that the applications of AI extend to all industries, providing efficiencies in different areas of business, the following are the industries that make the most use of it.

• Automotive: with AI, manufacturers are able to predict and adjust production more effectively in response to changes in supply and demand. AI is useful for increasing efficiency between production and procurement and reducing manual tasks.  Hidden Link To The Hurry case study
  
  
• Biotech & Life science: drug manufacturing is highly regulated and requires precise equipment calibration and product measurement. A large amount of data processing is required; in fact, a trial is not complete unless it has been tested on large databases. AI makes these processes scalable; think of the production of Covid-19 vaccines in record time.
  
  
• Healthcare: the healthcare sector is using intelligent automation with natural language processing (NLP). The use of chatbots in remote healthcare appointments requires less human intervention and often optimized time to diagnosis.
  
  
• Insurance: with AI, manual rate calculations or payments are eliminated and can simplify the processing of documents such as claims and appraisals. In addition, intelligent automation also helps insurance companies more easily meet compliance regulations.