Intelligent process automation (IPA) applies machine learning and other forms of artificial intelligence to automate operational workflows. Systems for intelligent workflow automation will potentially transform the way we work across every industry.
In fact, the value of IPA worldwide is projected to increase by almost 14% from now until 2027 to reach a total of nearly $26 billion.
In this guide, we explore the autonomous technology used for IPA and explain how it can enhance productivity and streamline your daily operations.
Intelligent process automation is a technology-driven approach to automating and optimizing business processes.
Intelligent business process automation involves creating and executing systems that can initiate, execute, and complete operational tasks with limited or no direct human intervention. IPA involves three distinct phases with varying levels of user input.
With digital automation, team members use a virtual interface to initiate, execute, and/or complete a defined process. While the system may automate one or two of these three steps, the user still takes an active role each time the task takes place.
This is the most common level of automation in most industries. Many of your business processes probably already exist in the digital space, so your teams can experiment with automating repeated tasks within those workflows.
The next level of IPA eliminates human input from task initiation, execution, and completion. However, an employee must manually set up each process in the system before the software system can perform these steps automatically.
This type of automation removes the manual human set-up and relies on robotic processes. These intelligent systems initiate AI software to mechanically execute the given tasks. For example, these robots can fill out forms and extra data from spreadsheets. Implementing robotic automation requires a commitment to advanced, full-scale business process reengineering.
Saving time, labor, and money is the main purpose of IPA for most businesses.
You can reduce the human effort required for tedious and time-consuming tasks. In turn, your teams can redirect their energy toward key business objectives designed to fuel growth and innovation.
Thorough business process models provide the blueprint for successful automation. To develop these models, each team should document every separate task involved in its processes and subprocesses. Building this map can illuminate areas that would most benefit from automation.
When you have your models, you can start by selecting one or two tasks as pilot projects. Then, the responsible team member can use enterprise workflow management software to initiate, execute, and complete the task in question.
Once the employee inputs these steps, AI programs can automatically identify these phases and carry out the necessary operations accordingly. Team members will test and monitor the automated process to ensure it meets project requirements.
You can even use AI to transform analog tasks. For this approach, you’ll first need to shift these pen-and-paper processes to the digital space to take advantage of machine learning and related tools.
As you transition each process from a digital format to full automation and fine-tune the new system, you can slowly decrease the level of employee engagement required for that task. Many programs incorporate machine learning, which means their accuracy increases with repeated performance of tasks. Ultimately, successful automation eliminates the need for team members to participate, manage, oversee, or intervene in the specified processes.
Many technological advancements play roles in facilitating robotic and intelligent process automation systems. These systems fall into the broader category of AI, which uses machines to mimic human intelligence by recognizing patterns and schematics in provided data.
These systems rely on software algorithms to analyze data from video, audio, and text files. Machine learning means that the algorithm becomes smarter and more accurate as it gathers and processes more data. ML can support marketing initiatives, drug discovery in the pharmaceutical space, image processing, and code creation.
These systems are designed to support a paperless, completely digital operation. Intelligent document capture can decrease costs and reduce the risk of human error by automatically gathering, authenticating, categorizing, and extracting information.
This technology is a type of ML that can process large volumes of speech, such as recordings. Companies can use NLP to summarize information, translate text from one language to another, and automate responses to spoken commands.
In the right context, intelligent process automation tools eliminate the need for direct human intervention in or continued oversight of specified processes.
Most organizations derive the most benefit from a combination of digital and intelligent automation technologies. By implementing intelligent process automation strategies, your company can:
Although IPA has transformative potential in nearly every business sector, the industries most rapidly adopting this type of tech include customer service, healthcare, finance, packing and shipping, manufacturing, and transport.
With the rise of e-grocery delivery services that accelerated in 2020, the industry has increasingly adopted automated fulfillment centers. These operations reduce labor costs, accelerate fulfillment, and create capacity for small businesses to scale and compete with larger enterprises.
For example, according to a report by McKinsey & Company, the Albertsons chain uses an automated warehouse model for nonfood and dry goods that can pick and pack 800 items per hour.
Some of the easiest ways to incorporate IPA include data entry, document distribution, form completion, and signature collection.
For example, automating these steps in the employee onboarding workflow streamlines and speeds up the process while eliminating the need to manually send forms, gather information, and follow up about pending and late items.
Widespread adoption of intelligent process automation is projected for 2024 and beyond. These are the key trends shaping the future of IPA.
Enterprise software offerings will continue to reduce the learning curve associated with automation. Your company can benefit from low-code and no-code IPA solutions for fast implementation and accelerated results. Digital platforms have amplified the focus on user experience, which means it will be easier for your teams to start using tech to streamline day-to-day tasks.
Generative artificial intelligence systems like ChatGPT harness both ML and AI to create completely new content. You can use generative AI to automate product research and development, process and innovate from audio and image files, and quickly write everything from marketing materials to software code.
Companies like Amazon increasingly use robots to interact with humans in the warehouse and transport space. They can speed up fulfillment and assist your teams by lifting heavy objects and building smart assembly lines.
Autonomous intelligent process automation is most likely to succeed when pursued within comprehensive business process reengineering. This approach calls for the large-scale redefinition of workflows, processes, subprocesses, and tasks to accommodate this new technology and optimize its advantages.
For best results, organizations should rely on robust enterprise management software to map and incorporate user-prompted digital automation into workflows. The most straightforward route to smart process automation is a next-generation process management platform.
The Fluix workflow system offers intuitive support for automation with minimal coding.Gain operational insight and explore the power of automation to create new opportunities for your business.
Please enter your business email to download this file
Receive expert tips twice a month