What is Generative AI?

AI is defined as the modelling of human mental functions by computer programs. It is real and causes a lot of excitement and anxiety. Today, every IT vendor is hammering the drum for Generative AI. In any recent seminars and conferences on IT technology, the leaders always mention “Generative AI”. 

Generative Artificial Intelligence

(GenAI) refers to the use of AI to create new content, like text, images, music, audio, and videos. It can produce a variety of content covering images, video, music, speech, text, software code and product designs.  Generative AI helps in faster product development, enhanced customer experience and improved employee productivity.

The GenAI and Deep Learning practices can be seen everywhere in computer science. It gives an idea of the possible number of ways how can design a computer system. It is the study of how computers perform cognitive functions as described by the humans, such as “Learning” and “Problem Solving”. The basic GenAI concepts are Deep Learning, Neural Networks, Large Language Models and Prompt Engineering. 

Various programming platforms for AI applications are Mojo, Python, Java, R etc. 

Trends of Generative AI

For the last 20 years, the research on Artificial intelligence is very aggressive and that resulted in great innovations. Big data, Robotics, Medical Research and Autonomous Vehicles are some of the applications emerged from AI development.

By 2027, nearly 15% of new applications will be automatically generated by AI without a human in the loop - Gartner

Almost 80% of CEOs believe AI is likely to significantly enhance business efficiencies in their organization – Forbes

Today, an estimated 60% of IT leaders are looking to implement Generative AI – CIO.com

44% of the worker’s core skills are expected to change in the next five years. Training employees to be able to leverage Generative AI is going to be critical – World Economic Forum.

AI in the healthcare sector in India is potentially developing. According to a report by the CIS India, AI could help add USD 957 billion to the Indian economy by 2035.

Accenture in a recent report, has highlighted that AI can boost India’s annual growth rate by 1.3 percentage points by 2035.

Industry usage of Generative AI

Generative AI use cases are endless, and they are evolving continuously. Businesses across industry are experimenting with different ways to incorporate Generative AI. Also, there is a high demand for increased efficiency and improved decision-making capabilities across industries. The Generative AI applications improve experiences, reduce costs, and increase revenues for the enterprises. 

The following is the summary of the use cases of Generative AI across industries.

Healthcare & Pharma

Generative AI based applications help healthcare professionals be more productive, identifying potential issues upfront, providing insights to deliver interconnected health and improve patient outcomes. It helps in,

Better Customer Experience: Automating administrative tasks, such as processing claims, scheduling appointments, and managing medical records.

Patient Health Summary: Provide healthcare decision support by generating personalized patient health summaries, speeding up patient response times and improving the patient experience.

Faster analysis of publications: Generative AI helps in reducing the time it takes to create research publications on specific drugs by analyzing vast amounts of data from multiple sources faster than ever. It helps in accelerating the speed and quality of care. It can also improve drug adherence.

Personalized medicine: Generative AI based individualized treatment plans based on a patient’s genetic makeup, medical history, lifestyle etc.

Healthcare Virtual Assistant: It provides end users with conversational and engaging access to the most relevant and accurate healthcare services and information.  

Manufacturing

Generative AI enables manufacturers to create more with their data, leading to advancements in predictive maintenance and demand forecasting. It also helps in simulating manufacturing quality, improving production speed, material efficiency.

Predictive maintenance: Helps in estimating life of machines and their components. Proactive information to technicians about repairs and replacement of parts and machines. This helps in reducing the downtime.

Performance Efficiency: Anticipating the problems proactively. It covers, risk of production disruptions, bottlenecks, and safety risks in real-time.

Other usage of Generative AI in Manufacturing industry is, 

Yield, Energy and throughput optimization

Digital simulations

Sales and demand forecasting

Logistic network optimization

Retail

Generative AI helps in personalizing offerings, brand management, optimizing marketing and sales activities. It enables retailers to tailor their offerings more precisely to customer demand. It helps in supporting dynamic pricing and planning.

Personalized Offerings: Enables retailers to deliver customized experiences, offerings, pricing, and planning. It also helps in modernizing the online and physical buying experience. 

Dynamic pricing & planning: Predict demand for different products, providing greater confidence for pricing and stocking decisions.

Other usage of Generative AI in Retail industry is, 

Campaign Management

Content Management

Augmented customer support

Search engine optimization

Banking

Generative AI applications help in delivering personalized banking experience to customers. It improves the financial simulations, developing Risk Analytics and fraud prevention.

Risk mitigation and portfolio optimization: Generative AI help banks to build data foundation for developing risk models, identify how events that are impacting the bank, how to mitigate that risk, and optimize portfolio.

Customer Pattern Analysis: Generative AI can analyze patterns in historic banking data at scale, helping relationship managers and customer representatives to identify customer preferences, anticipate needs, and create personalized banking experiences.

Customer Financial Planning: Generative AI can be used to automate customer service, identify trends in customer behavior, predict customer needs and preferences. This helps to understand the customer better and provide personalized advice.

Other usage of Generative AI in Banking Industry is, 

FinanciAnti-money laundering regulations

Complianceal Simulations

Applicant Simulations

Next Best Action

Risk Analytics

Fraud Prevention 

Insurance

The capability of analyzing and processing large amounts of data by Generative AI helps in accurate risk assessments and effective claims process. Various data categories are customer feedback, claims records, policy records and economic conditions etc.

Customer Support: Generative AI can provide multilingual customer service by translating customer queries and responding to them in the preferred language.

Policy Management: Generative AI analyzes large amounts of unstructured data related to customer policies, various policy documents, customer feedback, social media literature to implement better policy management.

Claims Management: Generative AI helps in analyzing various claims artifacts to enhance the overall efficiency and effectiveness of claims management.

Other usage of Generative AI in Insurance Industry is, 

Customer Communications

Coverage explanations

Cross sell and up sell of products

Accelerate Product development lifecycle

Innovation of products

Education 

Generative AI helps to connect teachers and students. It also enables the collaboration between teachers, administrators, and technology innovators to enable students and provide better education.

Student enablement: Generative AI helps the students with real-time lesson translation that speak different languages. Help blind students with classroom accessibility.

Student Success: Deep analytic insights into student success and help teachers to make informed decisions on how to improve student outcomes.

Telecommunication

Generative AI adoption by the telecom industry improves operation efficiency, network performance. In Telecom industry the Generative AI can be used to,

Analyze Customer purchasing pattern

Personalized recommendations of services

Enhance sales,

Manage customer loyalty

insights into customer preferences

Better data and network security, enhancing fraud detection

Public Sector

The goal of digital governments is to establish a connected government and provide better citizen services. Generative AI enables these citizen services to deliver citizens more effectively and protect confidential information. 

Smart cities: Generative AI helps in toll management, traffic optimization, and sustainability.

Better Citizen services: To provide citizens with easier access to connected government services through tracking, search, and conversational bots.

Other services that are enabled using Generative AI are,

Service operations optimization

Contact center automation

Courses Offered in Generative AI 

Some of the institutions in India that offer courses related to Generative Artificial Intelligence (AI) are, 

Manipal Academy of Higher Education, Manipal: Known for its quality education, Manipal offers programs in AI and related fields

VIT-AP University: VIT-AP provides courses in AI, including Generative AI

VIT Bhopal University: This university is recognized as a Category-1 institution by the UGC and offers AI-related programs

Indian Institute of Science Education and Research, Bhopal: Offers a 4-year BS program in AI

Gujarat University, Ahmedabad: Known for its academic excellence, Gujarat University provides AI courses

Cochin University of Science and Technology, Kochi: Offers AI-related programs

Sri Ramachandra Institute of Higher Education and Research, Chennai: Known for its research and education offers AI courses

The list of some of the reputed institutions in India that are offering courses in AI are listed below. These institutions provide various programs and courses related to AI, including Generative AI. 

Indian Institutes of Technology (IITs)

Indian Institutes of Information Technology (IIITs)

Indian Statistical Institute (ISI)

International Institute of Information Technology (IIIT) Hyderabad

Birla Institute of Technology and Science (BITS) Pilani

Amity University

IISc launched a two-year M.Tech. Program in Artificial Intelligence starting August 2019.

The GenAI courses cover the fundamental theoretical principles as well as hands-on component and industry GenAI use cases. The students will have the opportunity to work on live projects. 

Trainings within Organizations

Today there is a huge demand for skilled AI engineers because almost every organization is planning to adopt artificial intelligence for a better tomorrow. 

Major companies that employ most AI professionals in India are Wipro, TCS, Infosys, Cognizant, IBM, Microsoft, Accenture, Amazon, Cap Gemini and HCL technologies. In addition, there is an increase of about 30% year-on-year in the number of companies setting up dedicated AI teams in India. Majority of the companies have setup in house AI Laboratory in their organization and providing training to their staff to upgrade their skill set. 

In addition, these organizations are recruiting computer science, electronics and IT graduates and providing training on AI & ML for 3 to 6 months before deploying them onto the projects.  

Job Opportunities in Generative AI

Recent research by Pearson revealed that AI and automation will require 16.2 million workers in India to reskill and upskill, while also creating 4.7 million new tech jobs.

NASSCOM predicts that India alone is expected to have nearly one million data annotations worker by 2030.

According to Wheebox National Employability Test (WNET), demand for AI Jobs expected to surge to 1 million by 2026. 

According to COO Simplilearn, the demand for Gen AI courses in India increased 195% year-on-year in the first quarter of 2024.

Most popularly offered job titles include Machine Learning Engineer, Generative AI Engineer, Generative AI Developer, Robotics Engineer, Data Scientist, Data & Analytics Manager, NLP Engineer, Data Engineer etc.  

Summary

In summary, Generative AI is going to stay and will only get better with future versions. Unlike previous technologies, AI can make increasingly complex decisions enabling new business opportunities. The use of Generative AI across Organizations is becoming more and more widespread, possibly even trending toward industrialization.

Generative AI is an opportunity and not our competition. It won’t replace humans, however, assist in business success of next generation.

This is the right time for the beginner to start a career with AI and ML. In addition, the right time to up-skill in AI and ML by the veteran techies in the industry and become an early mover in the sector. 

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