What is an example of an intelligent Automation solution that makes use of Artificial Intelligence?

Intelligent automation is also known as hyperautomation, digital process automation, and intelligent process automation. It uses Robotic Process Automation (RPA), business process management (BPM), and other forms of artificial intelligence (AI) to simplify system integration and fully automate a broad variety of tasks.

In order to coordinate and automate the whole workflow of a process, both automated and human-completed tasks must be linked by a robust intelligent automation system. To put it another way, intelligent automation is the process of combining several layers of technology to achieve results that exceed the capabilities of any one component.

Intelligent automation and RPA automate tedious and time-consuming operations, which increases output, reduces human error, and frees up workers to focus on other initiatives.

Problems with efficiency are universal, affecting organisations of all sizes and in all sectors. Most of our customers come to us looking for assistance after realising that inefficiencies are having a detrimental effect on their company’s bottom line. Even if they can’t put their finger on what it is, they know that something is preventing them from developing to their full potential. Here are some instances of clever automation solutions that employ AI. This article might be helpful if you want to learn more about what is an example of an intelligent automation solution that makes use of artificial intelligence?

Intelligent automation: what is it?

Cognitive technologies such as AI, ML, CV, NLP, and RPA make up intelligent automation (IA), which strives to replicate human intellect. By doing so, human error in a commercial process is reduced or eliminated entirely. Modern businesses employ Intelligent Automation to advance more quickly and add brainpower to their back-office operations.

The tremendous increase in the installation of automation centres of excellence (COEs), as shown by the figures, is a crucial element highlighting the acceptance of IA, according to data from Intelligent Automation Network. Only 54% of respondents in 2021 had implemented an automation CoE, but 72% stated they had one in place by 2022, according to the 2023 Intelligent Automation Spend & Trends Report.

Businesses are automating processes and expanding their infrastructure to keep up with business needs and evolve in ways that were previously unthinkable.

What is an example of intelligent process automation?

Use of machine learning to examine past and present workload and compute data is an instance of intelligent automation. Provisioning and deprovisioning virtual machines to meet real-time demand could then be handled by an intelligent automation platform that also managed workloads to optimise runtimes and eliminate delays.

Why should a business invest in RPA and intelligent automation?

By eliminating the need for humans to do repetitive and time-consuming operations, intelligent automation and RPA boost productivity, cut down on mistakes, and free up workers’ schedules.

Companies across all sectors and all industries have efficiency issues. Most of our clients come to us because they’ve seen that their inefficiencies are negatively impacting their company’s bottom line and want to find a way to fix the problem. They are aware of the issue’s existence even though they cannot always identify its source. (If this describes you, have no fear; we’re here to assist.)

There are several upsides to doing away with unnecessary steps and the money they cost.

Productivity gains: 

Intelligent automated procedures are more efficient since they operate continuously. The remainder of your team, meanwhile, is working on more crucial matters that contribute more directly to the success of your business.

Increased participation by workers: Dull and tedious employment can be found in menial, repetitive jobs. (From 43% to 53% of the current labour force is bored.) Disengagement, attrition, and financial losses all stem from a lack of interest for workers. Having your staff work on more important projects increases the likelihood that they will be fully invested in their work and give you their all.

Greater accuracy:

 Although most individuals see the need of having accurate data, few really take the time to do something about it. One research found that 1-5% error rates in data are rather typical in enterprise-level databases. Manual data input is rife with chances lost and mistakes in decision making that may be mitigated with the use of intelligent automation technologies.

Quick expansion: 

Scalability is not a problem with RPA and other intelligent automation systems. More bots can be deployed rapidly at little cost and with little in the way of training to immediately begin contributing to increased productivity.

Gaining a deeper understanding of your procedures: 

Intelligent automation gives data surrounding each phase, making it easier to oversee the entire process. Intelligent automation enables data collecting to continually watch operations and report on them, so you may see where a bottleneck is developing, for example, even if you had very little insight into the process before.

Intelligent process automation has certain challenges.

There are still obstacles to overcome, despite the expanding number of use cases for IA in areas like document validation, demand forecasting, and spreadsheet automation. The Global Intelligent Automation Survey from Deloitte for 2022 focuses on three major difficulties.

Fragmented processes: 

Many businesses’ procedures are in disarray because of inefficient technology, awkward interfaces, or an abundance of boring, repetitive tasks that might be automated. There should be more transparency into these operations from time to time. In order to acquire a complete image of the business process and how it functions, firms utilise process and task mining prior to adopting IA.

Technological unreadiness:  

Technology breakthroughs in areas like artificial intelligence (AI), process discovery (PD), and low code (low code) have made this possible, but many businesses still aren’t IT-ready to reap IA’s benefits.

Budgetary implications: 

The implementation costs are an additional factor. Dashboards that clearly and succinctly demonstrate the advantages of intelligent automation can help reduce this difficulty by empowering stakeholders to make educated decisions and defend the costs of deployment.

You need to read, What is a benefit of Applying Artificial Intelligence (AI) to Accenture’s work?

The future of IA

Intelligent automation has undeniable importance in today’s global economy across all sectors. By using IA to automate formerly manual processes, firms may save money and improve workflow consistency. Digital transformation initiatives have been accelerated by the COVID-19 epidemic, leading to increased investment in infrastructure to facilitate automation. Roles will change further as the number of people working remotely increases. Workers formerly assigned to menial jobs will now be responsible for rolling out and expanding these improvements. To maintain employee motivation, middle managers will need to turn their attention to the more human aspects of their work. Workforce skills gaps will become more apparent as automation increases the pace of change in the workplace. Employees’ ability to weather periods of change can be bolstered by the supportive actions of middle management during such times. Without using intelligent automation, businesses would struggle to remain competitive in their particular marketplaces.

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