Artificial Intelligence Essentials for Business Leaders

AI has become the need of the hour and all the industries are now integrating analytics and AI to drive the decision-making process. Bhagirath Kumar Lader, who is the  Chief Manager (Business Information System) at GAIL led us through a session briefing Artificial Intelligence essentials for business leaders in today’s age. Lader is one of the key members of the digital transformation team at GAIL and carries huge knowledge about how AI, ML and DL are crucial to businesses. He gave us a quick overview of the motivation for AI, AI essentials, AI hype vs reality while taking us through use cases. 

While AI is a crucial part of businesses, one of the key drivers of its implementation is its ability to make the decision which is usually considered the forte of humans. Integrating decision making systems in work take off the workload and AI makes it that much easier as it relies on data for its decision-making capabilities. “Where humans would have typically relied on gut feelings, the availability of data and using AI on it makes it more efficient and reliant,” said Lader. 

Taking us through the early journey of analytics where it was first used in 1880 by the US Census Bureau to today’s age where it has reduced the time drastically in every process, he spoke about how analytics journey has evolved from descriptive and diagnostic analytics to predictive and prescriptive analytics. It now looks at the current and past data to find trends and patterns to help forecast the probability of situation occurring again in the future. He also spoke about how analytics also suggests decisions, actions and implications from predictive models to improve decision-making.  

While predictive and prescriptive analytics are now widely used, Laber shared how there is a wall that comes as a hindrance when it moves from descriptive to predictive analytics. “ While Business Analytics has many domains, it is highly important to understand each one of it to be able to break this wall and move into analysing correlations, root causes, forecasting and optimisation, which essentially are a part of predictive and prescriptive analytics,” said Lader. 

Once the above challenge is overcome, another crucial factor while designing AI system is to bring cognitive ability into the systems, which is nothing but the ability to do reseasoning, problem solving, planning, abstract thinking, complex idea comprehension and learning from experience — all of which are unique to humans. “Intelligence is the measure of cognitive capabilities, which if machines show can be considered showing artificial intelligence,” said Lader.