How do you properly adapt AI?

There are two myths surrounding artificial intelligence (AI). First, AI is a threat to employment. However, such assistive technologies in partnership with humans form a successful team of two.

For example, ChatGPT cannot create new information, it can aggregate human-created information from multiple sources to provide a definitive answer. Automation and filtration are the main reasons for using such a “machine”. However, requirements such as skills, judgment and ability are still the control of “human”. What is the right approach to adapting AI? Even though multiple uses of AI are reported, there is still a sense of insecurity, threat and doubt. Accordingly, important questions arise: What is the most efficient use of AI that contributes to increasing performance in all industries? How can AI increase adoption across industries? Is AI a threat to humans? In this regard, we have found that AI is best used in decision-making and human-to-human communication. A look at examples…


Agro-industrial systems using renewable energy can study energy efficiency, solar irrigation, drip irrigation, and geothermal irrigation by allowing AI to calculate energy consumption or resource utilization. Smart sensors help monitor plant vitals with real-time analytics and solutions. For example, Sentient grows perfect plants using AI that accounts for variables like water, soil, UV light, and heat on basil. Smart farming can combine the real and automated worlds using AI to improve decision-making between agricultural workers and AI.


The benefits of using AI in manufacturing are the reduction of errors and quality defects, an increase in the acceptance rate for predicting errors, easy maintenance, less overproduction and better demand forecasting. Robotic process automation uses multiple systems that help reduce time spent on redundant tasks and increase productivity. This leads to continuous innovation of “smart products” through collaborative efforts of manufacturers and AI dyads.


The curriculum at each level of education should be able to adapt to the needs of students, faculty and government. For example, during the 2023 budget process, Nirmala Sitharaman announced AI, robotics, and 3D planning as a New Age course. Teaching techniques, curriculum and co-curriculum can be developed using AI. Therefore, learning “with” and “about” AI creates “smart classrooms” that produce technology-driven and “smart students” or “smart resource people.” Learning with intelligence empowers the faculty-student dyad for a better education.


Hospitals have found that the effort involved in documenting each patient case can be reduced. The focus shifts from paperwork to patient care. This also creates a well-designed and labeled repository of all records. “Smart surgeries” in hospitals can curb the chaos in emergencies such as oxygen needs during Covid-19, vaccine formula or free hospital beds. For example, Bharat Biotech and other pharmaceutical companies conducted vaccine discovery experiments during Covid-19. Natural and social sciences require multiple experiments for new insights. However, it has been found that when certain connections are recognized by AI from previous studies, it contributes to a faster study process.

financial services

AI has been heavily adapted in global banking solutions. Banks like JP Morgan Chase use AI algorithms to note transactions that show fraudulent patterns that don’t fit the normal patterns. Several financial service providers have stated that ChatGPT can process customer interactions for claims processing for simple claims. A comprehensive way to increase the potency of trading is AI. Trade transactions are processed by algorithms. Consequently, AI-powered algorithms that help read market data can help people make faster decisions.

electronics and technology

Digital language assistants (e.g. Alexa), online decision support system (e.g. with chatbot), social augmented reality (e.g. companies that allow products to be “try out” online) can use image processing, information retrieval and communication benefits of AI for interactions between humans and machines.

retail trade

Assimilated, automated, and professional advice that aggregates information from multiple sources helps provide better customer support. Amazon is trying to develop an AI algorithm that can predict exactly what you need. This helps to establish a balance in the trader-customer exchange relationship.

AI applications are not limited to human-to-machine communication, but also help improve decision-making in “human-to-human communication”. For example, Amazon, which develops algorithms to predict purchases by an individual, can take into account the product preferences of their family and friends because decisions are not made alone. Metaverse, Virtual Reality (multiplayer games in a virtual world), Social Augmented Reality, Online Messaging Apps (WhatsApp), Social Media (Facebook) and Virtual Workspaces (Gather) focus on the “social life” of humans. AI will support decision-making in such an environment where there are multiple interactions and shared decisions are required.

Decisions are never made in isolation and multiple stakeholders are involved. AI is not only good for learning about a person, but also the social interactions they have with colleagues, friends, clients, customers, family, audience and others, both online and offline across all industries. Therefore, the true need and use of AI lies in decision making and human interactions.

(The author is a PhD student at ICFAI Business School, Hyderabad and co-founder of Byrut Business Solutions)