Artificial intelligence is the driving force to start innovation
COVID-19 showed the business world the real potential of Artificial intelligence. It accelerated the pace at which organizations adopted disruptive technologies to make the new normal work. By 2021, businesses across the industry have seen a rise in hyper-automation processes which is nothing but a combination of AI and machine learning with autonomy driven by cognitive process automation and robotics.
Having a strategic and well-thought-out implementation of hyper-automation will help in utilizing the investment made for repetitive tasks while initiating innovation. Hyperautomation is a powerful analytical tool and has abilities that facilitate human-machine collaboration, improve the customer experience while boosting productivity.
Automation can be either rule-based or cognitive. When employed across all the domains in a company with Artificial intelligence, the result is hyper-automation. This can create human capabilities that allow the systems to complete tasks faster and more efficiently with fewer mistakes. All this done right can relieve humans from mundane tasks and give them a chance to focus on more value-adding aspects.
Some use cases of hyper-automation are using NLP (natural language processing) to understand human speech or translate it to many languages or using optical character recognition (OCR) to read images for relevant information or using machine learning to analyze patterns and detect biases.
The Advantages Of Hyperautomation
A customer support center can use chatbots to analyze their audience data and give necessary suggestions and quick solutions to problems based on past transactions and history. This can save the company costs for customer support.
During the initial stages of the ongoing COVID-19 pandemic, Indian food delivery company Swiggy used Artificial intelligence to check if all the delivery partners were using masks and make them stop delivering non-essential items. The 2020 lockdown made e-commerce businesses quickly divide their functions between essential and non-essential items and services using natural language models. Restaurants and cafes had to update their menus as many had to change their approach towards food delivery which was possible thanks to computer vision models.
Online pharmacies saw the spotlight by having AI read and authenticate prescriptions. Telemedicine and teleconsultations with health care workers were faster and easier thanks to artificial intelligence. With constant data input, the medical-use robots were able to give better patient insights to the doctors. AI algorithms were analyzing large amounts of data from the electronic health records to prevent diseases and diagnose communicable diseases.
The entertainment industry also saw many innovations. While watching a movie on OTT platforms like Netflix, Amazon Prime, and Apple TV, if you fancied an object or an outfit and wanted to know where to buy it from, it is now possible to know thanks to image recognition and search features.
While Artificial intelligence and hyper-automation are essential to use today, businesses must prioritize the areas that need hyper-automation first. The foundation of a successful and effective hyper-automation process requires prerequisites like data acquisition, ingestion, cleaning, storage, governance, and protection backed up by futuristic AI technologies. This means the company has many domain experts collaborating to achieve a common goal, enabled by the capabilities of hyper-automation.