Intelligent automation combines the use of Artificial Intelligence (AI) with other technologies such as Robotic Process Automation (RPA) and Business Process Management (BPM). It aims to enable the automation of complex business processes, freeing teams to focus on more strategic business tasks.
These tasks can be manual, rule-based, or automated but dependent on human intervention. In any of these scenarios, AI helps facilitate the orchestration of processes.
In this context, AI, combined with other automation methods, is essential to create a culture of hyperautomation. This culture will allow technical teams to gain more recognition, and automation projects to achieve higher ROI within companies.
Thinking about this, the combination of AI and RPA allows for even more comprehensive and effective automation of business processes, as you will see throughout this article.
What is intelligent automation?
The components of intelligent automation are technologies that enable organizations to perform complex or even unpredictable tasks in an automated way.
We mentioned some of them at the beginning of this article, but let’s delve deeper into their main characteristics. Check out a more detailed view of these components!
Artificial Intelligence (AI)
AI is an area of computer science aimed at developing systems capable of simulating human intelligence. That is, these systems have the ability to rationalize, learn, and make decisions autonomously.
Therefore, AI is used in the automation of functions that involve decision-making and problem-solving, for example. Through devices or computer programs, it reproduces patterns of behavior similar to humans.
This means that, from it, companies start using techniques and models like machine learning and natural language processing (NLP) so that their robots learn and make decisions autonomously.
In fact, a global IBM survey showed that 41% of Brazilian companies already use some form of artificial intelligence in their daily routine. Whether for security/threat detection, internal and external chatbots, or data science initiatives, AI is already applied by companies with robust automation initiatives.
Robotic Process Automation (RPA)
This technology automates repetitive or rule-based tasks using robots capable of interacting with desktop systems, web applications, and distinct infrastructures.
Gartner defines that RPA is capable of “automating tasks in business and IT processes through software scripts that emulate human interaction with the application’s user interface.”
Activities such as form filling, report generation, and email sending can be automated through RPA. Thus, companies have the possibility to direct employees to more strategic assignments. The result is greater operational efficiency and error reduction.
Business Process Management (BPM)
Business Process Management, or BPM, is an approach employed to help organizations map and understand their processes. BPM solutions serve to assist in the mapping of business processes and the implementation of changes.
BPM is used to raise the layers of tasks that can be automated, as well as for the development, implementation, and monitoring of intelligent automation solutions.
What to consider in an intelligent automation strategy?
Before revising your automation tools, it’s necessary to have clarity about the necessary scale of automation in your company, existing orchestrations, and governance models.
This will prevent the creation of unrealistic expectations or the lack of resources, such as people and tools, to successfully implement intelligent automation. Here are some reflections to make:
- Analyze the automation stage of your company: does it already have robust automation initiatives or is it just starting to automate simple processes? Intelligent automation is more suitable for companies of the first type.
- Think about governance: does your company already have mapped processes and understand where the greatest opportunities and bottlenecks for automation are?
- Know your skills: does the company already have RPA developers and professionals with programming and orchestration skills?
- Think about scalability: when expanding your automations, how to optimize infrastructure costs, licensing, and allocation of people on the team?
Finally, it is necessary to choose the right tools and technologies for the orchestration of intelligent automation. They will not provide the expected gains by themselves if there is no structured planning behind their use.
Where is intelligent automation used?
Intelligent automation is applied to various sectors, to serve different purposes. Industry, services, health, retail, and government are some examples of segments where it is employed. Learn more about these uses below.
In the industry, intelligent automation is useful for automating repetitive tasks and also for activities that can put people in danger. Product assembly, machine operation, and equipment maintenance are among them.
Thus, it is possible to ensure more safety, productivity, and efficiency in industrial processes.
Service orchestration is one of the great gains made possible by intelligent automation for the service sector. Customer service, billing, and data processing are among these activities. Thus, service companies can reduce costs and improve customer service.
Back office processes
Beyond specific industries, intelligent automation can significantly enhance administrative processes across all sectors. Impacted processes include Intelligent Document Processing (IDP), automation of accounts payable, HR task management, financial management, and supplier management.
In healthcare, intelligent automation can automate medical tasks such as diagnosis, treatment, and research. Beyond cost reduction, healthcare institutions can improve patient care quality with these technologies.
In retail, customer service, inventory management, and data analysis can be automated. This process improvement enhances customer experience and boosts sales.
Intelligent automation is used by public administration to streamline bureaucratic activities, like license issuance, benefits processing, and compliance. It contributes to increased productivity and reduced public service costs.
Combining AI and RPA
While AI can automate more complex and unpredictable tasks, RPA is used for simple, repetitive activities. For teams already mature in automation, adopting pure code RPA solutions allows for implementing and modifying custom algorithms.
Moreover, it’s now possible to use advanced machine learning and AI libraries in RPA projects, such as TensorFlow, PyTorch, and GPT models. This flexibility is crucial for specialized tasks in generative AI.
For instance, a company might use AI to analyze insurance claims data to identify fraud patterns. Identified fraudulent claims can then be processed by an RPA bot trained for this type of scenario.
To successfully combine AI and RPA for intelligent process automation, it’s essential to clearly understand the automation objectives and the processes to be automated.
Beyond these practical examples, there are numerous other applications for combining RPA with AI, including:
- Data entry or migration;
- Monitoring payment deadlines and sending reminders;
- Reading, extracting, and classifying information from emails, PDF documents, and other formats;
- Converting and sorting files.
Understanding how these two technologies complement each other is crucial. However, for successful implementation of intelligent automation combining AI and RPA, it’s essential to have a clear understanding of the automation goals and the processes that will be automated.
Is Your Organization Ready to Implement Intelligent Automation?
This article explored how intelligent automation combines technologies like AI, RPA, and BPM to make organizational processes more agile and efficient. However, it’s important to consider whether the goal is to automate specific tasks in different areas or to enhance the performance of existing automation initiatives.
For companies with robust RPA initiatives, a multi-vendor architecture, combining low-code and high-code tools, is recommended for a versatile and adaptable approach to intelligent automation.
For companies seeking scalability and flexibility for technical teams, BotCity‘s RPA orchestrator is an excellent choice. With it, your team can create bots up to 20 times faster than on low-code platforms. Additionally, manage parallel bots centrally, schedule executions and queue management, monitor bots in real time, and manage access and permissions directly in the orchestrator.