COVID-19 revealed the true potential of artificial intelligence to the commercial world. It has hastened the adoption of disruptive technology by businesses to create the new normal of work. Hyper-automation processes, which are a combination of AI and machine learning with autonomy driven by cognitive process automation and robots, have become increasingly popular in businesses throughout the industry.

Hyper-automation should be implemented systematically and well-thought-out to maximize the investment made in repetitive processes while also allowing for creativity. Hyper automation is a strong analytical tool that enables human-machine collaboration, improves customer experience, and increases productivity.

Automation might be cognitive or rule-based. When Artificial Intelligence is used across all domains in a corporation, the consequence is hyper-automation. This can result in human-like capabilities in the systems, allowing them to accomplish jobs more quickly and effectively with fewer errors. All of this, if done correctly, can free humans from boring duties and allow them to focus on more value-adding activities.

NLP can be used to interpret human speech and translate it into several languages, optical character recognition can be used to read images for relevant information, and machine learning can be used to analyze trends and uncover biases.

The Advantages Of Hyper automation

Chatbots can be used by a customer service centre to assess audience data and provide required suggestions and rapid solutions to problems based on previous transactions and history. This can help the organization save money on customer service.

During the early phases of the ongoing COVID-19 pandemic, Swiggy, an Indian food delivery service, employed artificial intelligence to determine whether all of its delivery partners were wearing masks and to order them to cease delivering non-essential items. The 2020 lockdown forced e-commerce enterprises to use natural language models to quickly split their functions between vital and non-critical commodities and services. Restaurants and cafes had to adapt their menus since many of them had to change their approach to food delivery, which was made possible by computer vision models.

Artificial intelligence was used to read and authenticate prescriptions, which put online pharmacies in the spotlight. Artificial intelligence made telemedicine and teleconsultations with health care workers faster and easier. The medical-use robots were able to provide clinicians with superior patient insights because of constant data input. 

There were other breakthroughs in the entertainment business as well. If you liked a product or an outfit while watching a movie on OTT platforms like Netflix, Amazon Prime, or Apple TV, you can now find out where to buy it thanks to picturing recognition and search features.

While artificial intelligence and hyper-automation are both necessary in today’s world, organizations must first prioritize the areas that require hyper-automation. Data gathering, ingestion, cleansing, storage, governance, and protection are all criteria for a successful and effective hyper-automation process, and they’re all backed up by cutting-edge AI technology. This indicates that the organization has a large number of domain specialists working together to achieve a single goal, thanks to hyper-capabilities. automation.