Maaz Ansari, Co-Founder and CEO, ORI

Maaz is the CEO and Co-founder of ORI and leads the business and strategy at ORI. Before co-founding ORI, he has helmed Equity research for a boutique advisory brokerage firm and led pre-sales for applied data science products at Fractal Analytics. He has also worked with 3 other start-ups in various capacities.

 

AI and Machine Learning have been the hottest buzzwords in the decade that has gone by. According to a study, 77% of devices that we use in our day-to-day lives are now powered by AI and ML. From platforms like Netflix and Facebook to products like Amazon’s Alexa and Google Home, AI has become the core of nearly every product and service that we come across.

In 2020, the enterprise world has also added to the capabilities of AI assistants, as they help build strong customer relationships and smooth business operations. No wonder Conversational AI has become a fascination of global business leaders and SMEs alike.

AI-ML Industry is growing rapidly and unlocking new avenues for enterprises aiming to bring vital changes in the ecosystem. According to a Gartner study, around 37% of all companies reviewed were found utilizing some type of ML in their business. It is anticipated that around 80% of modern advances will be based around AI and ML by 2022. The Global Artificial Intelligence Hardware Market was valued at approximately USD 9.8 billion in 2019 and is pegged to grow with a healthy CAGR of more than 37.5% over the forecast period 2020-2027.

So, as we begin a promising decade in the New Normal, it becomes important to know about the trends of AI-ML that might follow.

  1. Robotic Process Automation + Artificial Intelligence = Hyper-automation

Hyper-automation was identified by Gartner, as one of the best technology trends to be used in an organization for automation. Pandemic has stepped up the adoption of the concept in which all the company’s operations should be automated including legacy business processes. AI and ML are the significant drivers of hyper-automation. If Robotic Process Automation (RPA), Machine Learning (ML), and Artificial Intelligence (AI) work in harmony to automate complex business processes, then hyperautomation is a means for real digital transformation.

  1. Power of Machine Learning (ML) + Internet of Things (IOT)

Kevin Ashton is considered as the father of IOT, which comprises a smart infrastructure connected via the internet to the cloud. The Internet of Things became a rapidly emerging segment in the last decade. Economic analyst Transforma Insights has forecasted that the worldwide IoT market will comprise 24.1 billion devices by 2030, producing $1.5 trillion in income. Arthur Samuel is the inventor of Machine Learning who defined this term in 1959. The utilization of Machine Learning is progressively interlaced with IoT. Machine Learning, Artificial Intelligence, and Deep Learning, for instance, are now being used to make IoT devices and services smarter and more secure.

  1. Augmented Reality in Chatbots

Artificial Intelligence together with Augmented Reality (AR) is considered one of the main enablers of the Internet of Senses (IoS), a megatrend from 2021 toward 2030. AR is quite a unique technology which actually takes customer engagement to virtual reality. Innovation in this regard is the app for the users where chatbot leverages augmented reality to facilitate the purchase decision, prompting customers with relevant recommendations. For example, if you want to see how trousers would fit you, you can use AR technology or use AR to determine the correct size for your shoes by clicking and uploading a picture of your feet.

  1. Reinforcement Learning

Reinforcement Learning is the area of machine learning that can be used by companies in the future for deep learning, thereby improving the effectiveness of gathered data. An ideal illustration of reinforcement learning is a chatbot that addresses simple user queries like greetings, order booking, and consultation calls and through reinforcement learning builds and improves on these interactions giving it the ability to address more complex user queries such as product demos etc.

  1. Business Forecasting and Analysis

This technology is strategized by experts to screen a set of data over a period of time which then is examined and utilized for making smart decisions. With the changing strategies, the ML networks can give conjectures with accuracy as high as 95%. Companies will soon start fusing recurrent neural networks for high fidelity forecasting.

  1. Increased adoption of Hyper Personalized and Contextual communication

We have all heard of the saying that Content is King. But 2021 will bring in a change where we hear “Context is King”.

With the adoption of AI & ML tools and methods – we will see brands and organizations increasingly adopt a more personalized and context driven approach to communication.

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