The Basics of Intelligent Automation
Intelligent Automation (IA) is becoming a far greater priority for organizations. In fact, Intelligent Automation is set to become a mainstream investment and focal point for various industries in years to come. Leading organizations have already implemented advanced process automation and other digital technologies, and have combined them to balance human and machine workforces.
Intelligent Automation is now at the stage where engineers can control each aspect of the automation journey—discovering needs, automating processes, and optimizing operations. It’s now possible to automate all tedious business processes and create refined workflows by creating a digital workforce that leverages both humans and machines.
Intelligent Automation is the powerful fusion of Artificial Intelligence (AI) and Robotic Process Automation (RPA). These two technologies work together to enable fast end-to-end business task automation, driving increased operational efficiency by reducing costs and delivering better customer experiences.
Intelligent Automation vs. RPA
There’s often confusion regarding the difference between Intelligent Automation and RPA. To clarify, Intelligent Automation is actually the combination of RPA and AI.
IA enhances the task automation capabilities of RPA by adding the cognitive power of Machine Learning (ML) and AI. By doing so, the IA industry has been able to massively expand the horizons of business process automation. Simply put, here’s how IA works:
- IA enables organizations to automate complex end-to-end processes.
- These processes typically involve the use of structured and unstructured data.
- Thanks to AI and Machine Learning (ML), IA systems are able to communicate using human languages, classifying and recognizing ‘sentiment’.
- This understanding of sentiment or language enables IA to operate in a completely automated fashion, even automating workflow steps that would have previously required human intervention.
How Intelligent Automation Works
Intelligent Automation has made it very easy to automate extremely multifaceted business processes. Here are the typical steps within the IA cycle:
- Discovery: AI-powered tools mechanically and systematically detect the work activities and responsibilities they need to achieve. These tools study the workers who are accomplishing these tasks to recognize optimal workflows.
- Proposal of automation paths: The AI-powered tools help the IA system to select the best plan of action.
- Automation: AI-tools are used again to access and decode unstructured data. Human language input (in the form of chat conversations, text documents, audio files, and video) is assessed. 80-90% of the information used by most companies is unstructured. Hence, this step is a trailblazer. Thanks to this revolutionary step that IA systems can take thanks to AI tools, the possibilities are limitless for industries.The IA system uses RPA bots to complete the tasks it has detected.
- Analysis: Analyzing automation relies on AI tools to recognize patterns and regularities in the process data. Based on this assessment, the system predicts future productivity levels, profit projections, etc.
The final result is a self-adjusted, end-to-end automation process. Regardless of what the business tasks are, over time, IA systems reduce error risks via stringent RPA bot management.
The Transformative Capabilities of Intelligent Automation
Combining RPA with AI and ML technologies makes it possible for businesses to automate all types of scenarios. RPA bots are able to act cognitively. They can assess situations and make appropriate decisions. Thanks to AI, RPA bots “learn on the job”. They don’t repeat mistakes. They correct and better themselves with each process. Such rapidly and constantly improving RPA bots have the potential to become invaluable resources to any company’s human-digital workforce, irrespective of the scale and the complexity of the tasks.
Intelligent Automation has ‘transformative’ capabilities. Intelligent Automation can help business leaders re-imagine how their workflows operate. The rapidly growing Intelligent Automation industry can seamlessly integrate technology into work processes, helping people to focus on other aspects of the business.
Intelligent Automation with RPA is completely different from traditional automation programs. Those programs relied heavily on narrow instructions. The programs could only process structured data. Intelligent Automation that combines RPA with AI, on the other hand, deals with unstructured data. These bots assess and improve each automated step of the cycle. The average investment recovery period for Intelligent Automation investments is 6 months. Hence, companies can expect fast improvement and near-perfect results over time.
Benefits of Intelligent Automation
Organizations benefit from Intelligent Automation because it saves money in the long run and leads to improved processes, productivity, and customer experiences.
Improved Productivity
- Cost and Time Savings – Intelligent Automation systems help us save time and money. There’s a massive reduction in the need for human interactions. Business processes are now faster and all outputs are carefully regularized.
- Digital Workforce – Digital RPA-powered workers improve efficiency in routine and complex tasks. Over time, intelligent bots can self-learn to radically improve customer experiences. These bots guarantee faster response times and consistently improving outputs.
- Improved Processes – As operational obstacles are reduced, cognitive IA systems are able to improve their ability to deal with inconsistent and unstructured data. The RPA + AI combinations help Intelligent Automation legacy systems navigate through complex front-desk and back-office operations of all kinds.
- Better Compliance – Intelligent Automation systems guarantee that all operations that they carry out adhere to the necessities installed by supervisory statutes. These systems are designed to follow orders and come up with the best practices and plan of actions that improve efficiency while still following the compliance standards.
Automating Tasks For Departments
A study by Tractica revealed that the global AI market is expected to reach the $120 billion mark by 2025 in terms of revenue. The study also suggests that there’ll be over 300 IA use cases. Businesses that combine AI application development with RPA can devise their unique IA systems to automate different departments of their company, including traditionally ‘human’ responsibilities such as:
- Human Relations
- Finance & Accounting
- Customer Service
- Business Process Outsourcing
Intelligent Automation Use Cases By Industry
For many industries, Intelligent Automation transforms how they work. The industries at the forefront of Intelligent Automation include healthcare, insurance, finance, and manufacturing.
Healthcare
Intelligent Automation helps medical institutions carry out mundane tasks such as processing insurance forms, patient referrals, in-house sharing of information, supplier integrations, and supporting the front-line staff with logistics and data. The rise of RPA in healthcare has laid the groundwork for organizations to begin implementing Intelligent Automation.
Insurance
Insurance agents are no longer required to invest hours of manual effort into mundane tasks. Intelligent Automation radically improves their ability to process claims. Intelligent Automation performs analysis that is beyond human capabilities on multi-dimensional data sets, and can handle complex tasks like fraud detection, chatbots/digital customer service agents, and recommendation engines. It is the next evolution of RPA, which is best used to remove the need for people to perform repetitive, low-value, structured data processes like address changes, billing/invoicing, purchase orders, and claims processing, and make the time spent on those tasks available for more valuable and strategic work.
Finance
The finance industry is ripe with opportunities for Intelligent Automation. IA presents a huge chance for Finance functions within financial services institutions to deliver information and value to the business more quickly, more accurately, and at a lower cost. On top of increased process speeds and improved quality, the redeployment of people to higher-value activities brings increased flexibility to cope with short-term volume variations. From fraud detection and prevention through Automated Machine Learning to loan processing and approval, IA is rapidly transforming the finance space.
Manufacturing
Manufacturing industries use data from logistics companies to predict demand and maintenance. Leveraging existing data, manufacturers can use predictive analytics to solve new problems and facilitate product engineering.
Intelligent Automation Technology
Who are the leaders in this industry? The most notable trailblazers include:
- WorkFusion – top creator of AI-driven automation processes and nuanced RPA software
- UiPath – the leading provider of RPA tools across many industries
- Automation Anywhere – another industry-leader in creating RPA bots.
Implementing Intelligent Automation
The challenge that has held back industrial growth for centuries was the inability to automate any and every business process completely. Thanks to Intelligent Automation, most business processes are now suitable candidates for Intelligent Automation.
At Productive Edge, we work with leading organizations to help implement Intelligent Automation for their teams. To learn more about how we can help you, speak to one of our experts.
