Future Sneak Peak- Intelligent Automation Waves every CEO should know
Intelligent Automation (IA) is poised to move businesses into becoming Enterprise 4.0 organizations. IA has wide application areas ranging from driving production efficiencies, lowering costs, simplifying business processes and generating insightful data points for better decision making. Further, IA use case are creating immense value for emerging high growth businesses, as many such solutions to complex & voluminous processes & businesses scenarios, can be implemented as plug & play.
Some of the key areas where IA is being used:-
1. Intelligent Production
The production floors with the use of IA & ML looks extremely different from the grimy shop floors of today.It is a proven fact that intelligent machines powered by machine learning will lead the automation drive. Internet of Things (IoT), embedded devices, cloud, AI coupled with machine learning will drive this. Machines will automatically do self-cleaning and preventive maintenance, increase or decrease production depending on data inputs coming from the intelligent warehouse. Production managers will have more visibility, better insights and ultimately better control over the production process.
2. Intelligent Business Process Automation & RPA’s
Business Process Automation(BPA) has been around for some time now. But the future is going to be sleeker and better organized. Integration-centric BPA Solutions with a blend of OCR & RPA technology that leads to touchless (no human involvement) ways of working, such as fully Digital Accounts Payables & Payroll processes will become more prevalent.
On one hand, human-centric BPA Solutions which require multiple layers of approvals will leverage cognitive RPAs & machine learning algorithms. Lastly document-centric BPA Solutions which require data capture & validation based on a set of documents like say vouchers will use advanced OCR (IDP-Intelligent Document Processing), coupled with AI to make the data capture & validation possible on the go.
Further, Robotic Process Automation will use intelligent BOTs to complete mundane office tasks such as data extraction, data-mining, form filling. By deploying intelligent algorithms that emulate human processes, RPA’s automate complex daily tasks. Currently the state of RPA utilizes bots extensively. However, bots follow the process defined by the user. In the future Intelligent AI bots will use machine learning to recognize patterns in the data and determine faster and easier ways to manage daily workflows.
There is no escaping the future when it comes to Intelligent Automation, bottom line pressures to improve efficiency and lower costs coupled with the growth and adoption of technology will ensure enterprise 4.0 happens inevitably.
While the future is still evolving, I believe that the below specific areas will drive enterprise 4.0 in the not too distant future
Collaborative Bots or Cobots as they are called will get increasingly deployed to assist humans in shared workplaces, especially in areas such as warehousing and assembly line. The future enterprise will deploy cobots in areas to help address labor shortages or bring about better and faster efficiencies. We will see intelligent robotic machines working in tandem with their human counterparts.
2. Growth in RPA
The robotic process automation domain is expected to see a huge fill-up in the years to come. As RPA’s continue to mimic human interaction more and more effectively, they are going to see sustained rise across all industries such as Insurance, Banking, Finance, Healthcare, Telecommunication, Logistics and Supply Chain. Use cases could range from prescription handling, insurance claim processing, billing, compliance, clinical documentation, CRM and the works
Hyper-automation refers to the use of advanced technologies like ML, AI, NLP and RPA to automate many tasks. Hyper automation is the future of intelligent automation as it brings all advanced technologies holistically to reap business benefits
4. Augmented Intelligence
Augmented Intelligence involves cognitive intelligence in machine learning. While largely machines learned from structured data, with augmented intelligence, un-structured data can be leveraged to build a completely new cognitive intelligence that feeds better human decision making. This intelligence typically mimics near human intelligence where our minds are able to process both structured and un-structured data including images and sound to make decisions. In the near future augmented intelligence will find applications across usage in sales, production, customer support and supply chain becoming the de-facto game changer for organizations evolving into enterprise 4.0 companies. As technologies like AI, ML, NLP, Cobots and the like gain wider acceptance and lowered costs, organizations will increasingly adopt them in various areas as a means to improve efficiencies, lower costs and aid better decision making.