COVID-19 demonstrated the true value of artificial intelligence to the commercial sector. It has accelerated the rate at which businesses are adopting disruptive technology to create the new normal of work. Businesses across the industry have experienced a growth in hyper-automation processes, which are nothing but more than a combination of AI and machine learning with autonomy driven by cognitive process automation and robots, by 2021.
Rules-based or cognitive automation can be used. Hyper-automation results when artificial intelligence is used across all domains in a firm. This can help systems accomplish jobs more quickly and efficiently, with fewer errors. When done correctly, all of this can free humans from monotonous chores and allow them to focus on more value-adding activities.
Using natural language processing (NLP) to interpret human speech or translate it into many languages, optical character recognition to read images for important information, and machine learning to analyze trends and uncover biases are some examples of hyper-automation use cases.
Advantages of Hyper-automation
Chatbots can be used by a customer service center to assess audience data and provide appropriate recommendations and rapid solutions to problems based on previous transactions and history. This could help the business save money on customer service.
During the early phases of the ongoing COVID-19 pandemic, Swiggy, an Indian food delivery firm, 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 companies to use natural language algorithms to quickly split their functions between vital and non-essential commodities and services. Restaurants and cafes had to alter their menus, and many of them had to adapt their approach to food delivery, which was made possible by computer vision models.
Artificial intelligence (AI) was used to read and authenticate prescriptions, putting online pharmacies in the spotlight. Artificial intelligence made telemedicine and teleconsultations with healthcare professionals faster and easier. The medical-use robots were able to provide greater patient insights to clinicians due to constant data intake. To prevent and identify communicable diseases, AI systems analyzed enormous volumes of data from electronic health records.
Many breakthroughs took place in the entertainment business as well. If you liked an object or an outfit while watching a movie on OTT platforms like Netflix, Amazon Prime, or Apple TV and wanted to know where you could buy it, image recognition and search technologies have made it easy.
While artificial intelligence and hyper-automation are critical in today’s world, organizations must first select the areas that require hyper-automation. Prerequisites such as data capture, ingestion, cleaning, storage, governance, and protection, backed up by futuristic AI technologies, form the cornerstone of a successful and effective hyper-automation process. This implies that the organization has a large number of domain specialists working together to achieve a single goal, thanks to hyper-capabilities.