Can AI Replace India’s $30 Billion Customer Support Sector?

Companies around the world are leveraging AI (artificial intelligence) to interact with customers. This inclination indicates that customer support significantly depends on AI.

Recent research indicated that India’s call centre customer support market is $33 billion as of December 2024. Additionally, AI-powered systems will directly handle over 50% of customer communications. This will help companies significantly reduce operational costs by more than $400 million per year.

In an interview, K Kirthivasan, CEO of Tata Consultancy Services said “In an ideal phase, there should be minimal incoming call centres. At present, the technology should be able to predict a call and proactively address the customer’s pain point.” He believes AI could significantly impact the traditional call centre model.

The Indian AI-powered customer service market has seen significant growth, with eighteen startups collectively raising over $600 million in funding in the past four years. Gupshup, a conversational messaging platform founded in 2004 has been a major contributor, securing over $400 million in investments.

Several leading payment platforms and e-commerce companies have adopted AI customer support. Meesho, one of the leading e-commerce platforms have launched its gen AI-powered voice bot that handles up to 60,000 calls daily, 95% queries and observed a 50% improvement in response time.

AI-driven chatbots handle 90% of PhonePe’s customer service. This leading payment company has cut its customer support team by 60% in the past five years.

However, an EY report earlier this year indicated that 78% of consumers still prefer human customer support over chatbots. Additionally, 60% of people are not comfortable sharing their personal information with AI-enabled systems as they prefer human interaction more.

While the considerable inclination towards AI suggests that customer support in India is likely to be transformed, these reports indicate this technology will not replace human agents completely.

Source: https://analyticsindiamag.com/ai-features/will-ai-end-indias-30-billion-customer-support-industry/

This entry was posted on December 31, 2024 by Prasenjit Das.

AI is a Game-changer For Disabled Students, Schools Are Still Learning to Utilise It

Recent research and expert opinions suggest that AI (artificial intelligence) has the potential to transform education for students with different disabilities including visual, speech, language, and hearing impairments. However, schools are still in the stage of understanding and implementing AI-powered technologies.

For Makenzie Gilkison, a student in the National Junior Honor Society spelling is such a struggle that a word like rhinoceros might come out as “rineanswsaurs” or sarcastic as “sarcastic. Reading is a significant challenge for this 14-year-old from suburban Indianapolis. Although she can verbalise words, dyslexia makes the process very exhausting for her as it impacts her ability to understand what she reads.

Gilkison, while recalling her early childhood years, said “I just assumed I was stupid,”. She thanked AI-powered assistive technology, a word prediction program and other tools for enabling her to succeed academically.

“I would have just probably given up if I didn’t have them,” she added.

AI has the potential to significantly assist students with various disabilities in performing tasks that may be challenging for them. While schools in the United States are still exploring the best methods to integrate AI, many are prioritising its use to support students with disabilities.

US Education Department is prioritising accessibility of the latest tools like text-to-speech and alternative communication devices for students with disabilities.

Overall, AI has the potential to revolutionise education for disabled students. In India, if schools overcome the challenges and embrace AI benefits, it can also create an unbiased and inclusive learning environment for all students including those with disabilities.

Source: https://www.thehindu.com/sci-tech/technology/ai-is-a-game-changer-for-students-with-disabilities-but-schools-are-still-learning-to-harness-it/article69032098.ece

This entry was posted on December 30, 2024 by Prasenjit Das.

Why Learn MEAN and MERN Stack: Benefits and Career Opportunities!

Want to know how learning MEAN and MERN stacks can be a game-changer for your full-stack development career? We have the answer! In this blog, we will explore the advantages of learning MEAN and MERN stacks, compare them and understand how this promising endeavour positions you as a highly sought-after developer in today’s competitive job market.

Let’s dive in!

This digital revolution is fueled by AI (artificial intelligence), IoT (Internet of Things) and cloud computing. These advancements have reshaped industries and transformed the way we interact with technology.

As web development has immensely evolved with time, so have the tools and frameworks used to build complex applications. MEAN and MERN, built upon versatile JavaScript ecosystems have emerged as major players in the industry.

If you are thinking of starting your career as a full-stack developer, you should consider learning these two powerful stacks. Not only MEAN/MERN are in-demand skills, but they also lead to a high salary package and rapid career growth.

While learning any stack (MEAN or MERN) can give you a great starting point, mastering both will set you apart from others. By investing in the MEAN and MERN course, you can acquire a comprehensive understanding of both fields, making you a highly sought-after developer in the industry.

Let’s understand every nitty gritty detail of both stacks and make the right decision for your career!

MERN Stack vs. MEAN Stack: What You Should Learn?

Before comparing MEAN and MERN, let’s understand both stacks in detail and break down the components of each.

What is MERN Stack?

MERN stands for:

M: MongoDB (a flexible database for storing all types of data).

E: Express.js (a framework to build web applications and APIs).

R: React (a library to build user interfaces).

N: Node.js (a JavaScript runtime environment).

MERN stack is a collection of JavaScript-based technologies which is used to create dynamic web applications. By leveraging a single JavaScript language across the whole stack, MERN simplifies the development process and enables faster and more efficient development of web applications.

Not only this technology is easier to master because its components are based on JavaScript but also learning the MERN stack can boost your career. Mastering the MERN stack opens up numerous opportunities due to its increased adoption across industries.

The popularity of MERN and JavaScript has contributed to the soaring demand for skilled developers, resulting in skyrocketed MERN stack jobs. As many companies are adopting this technology, this expanding usage has created a range of job opportunities for MERN developers.

The average salary of a mean full stack developer ranges from ₹3,00,000 to ₹7,00,000 per annum in India. This payscale can go beyond this range when you start gaining experience in the field.

What is MEAN Stack?

MEAN stands for:

M: MongoDB (a flexible database for storing all types of data).

E: Express.js (a framework to build web applications and APIs).

A: Angular (a framework to create complex web applications).

N: Node.js (a JavaScript runtime environment).

MEAN stack is a collection of JavaScript-based technologies used to develop dynamic web applications. As all components are based on JavaScript, the MEAN stack development is easy to learn and use for developers. Using a single language, you can develop both the front-end and back-end of your application.

Using MEAN, developers can handle everything from database interactions to UI design. This technology is widely adopted across industries due to its versatility and efficiency. MEAN stack jobs have exploded in recent years. Undeniably, learning the MEAN stack can boost your career prospects.

Talking about earrings, the average salary of a mean stack developer in India ranges from ₹3,00,000 to ₹6,00,000 per annum. This pay scale can go beyond the average once you start gaining experience in this field.

Key Differences and Similarities Between MEAN and MERN

Although MEAN and MERN stacks are JavaScript-based technologies and share common components, they have some key differences. Let’s thoroughly understand the differences and similarities of both the stacks.

Key Similarities Between MEAN and MERN

JavaScript-Based: Both stacks rely on JavaScript for front-end and back-end web development.
Node.js as the Server-Side Runtime: MEAN and MERN leverage Node.js to execute Javascript on the server side.
MongoDB as the NoSQL Database: Both MEAN and MERN stacks employ MongoDB to store and manage databases.
Express.js as the Web Framework: Both stacks use Express.js to build efficient and robust APIs and web apps.

Key Differences Between MEAN and MERN

The primary difference between both MEAN and MERN stacks is their front-end frameworks. While MEAN leverages React to build dynamic user interfaces, MERN uses Angular to create complex web applications.

Why Learn MEAN and MERN Stack Both?

It is not a surprise that the job market is too competitive. To stay ahead of the curve, it is essential to master both the front-end and back-end aspects of web development. By investing in the full-stack web development (MEAN + MERN) course, you can acquire a comprehensive understanding of both fields.

By mastering both MEAN and MERN stacks, you can position yourself as a sought-after developer and boost your career prospects to a great level. Here is why you should consider learning both MEAN and MERN stacks.

Versatile Skillset: While the MERN stack is ideal for large-scale enterprise applications, MEAN is perfect for building dynamic and user-friendly apps. If you gain expertise in both stacks, you equip yourself with skills to handle a wide range of projects.

Stronger Problem-Solving Skills: Mastering both stacks exposes you to varied architectural patterns and problem-solving techniques. You can smoothly switch between frameworks. This makes you a valuable asset to any development team, boosting job opportunities.

Career Advancement: Many companies including tech giants seek developers with expertise in both MEAN and MERN stacks. With a strong foundation in these two technologies, you can command high salaries and acquire top-tier positions in big companies.

In-demand Skills: Both MEAN and MERN stacks are highly demanded skills in today’s job market. Developers with expertise in both MEAN and MERN are in high demand and are preferred over those with skills in either stacks.

High-earning Potential: If you acquire expertise in both stacks, it increases your earning potential. As you become a valuable asset to employers, you get better job opportunities with a high salary package ranging from ₹6,00,000 to ₹25,00,000 per annum or more.

Abundant Resources: Both MEAN & MERN stacks offer extensive online resources, tutorials, and a large community that supports you in the entire learning journey.

What Are the Career Opportunities Like After Mastering MEAN and MERN Stacks?

Mastering these technologies can open up a wide range of exciting job opportunities. Here are some of the career paths you can pursue after mastering MEAN and MERN:

Core Roles:

Full-Stack Developer: You can become a full-stack developer after mastering MEAN/MERN stacks. As a full-stack developer, you will be responsible for both front-end and back-end web application development.

Front-end Developer: As a front-end developer, you will focus more on designing and developing user interfaces and user experience of web applications.

Back-end Developer: As a back-end developer, you will focus on server-side development, API development, and database management.

Specialised Roles:

JavaScript Developer: As JavaScript developer has a deep understanding of the entire JavaScript ecosystem, they can work with various JavaScript libraries and frameworks efficiently. From front-end development to optimising website performances, you can handle all.

MERN/MEAN Stack Specialist: A MEAN/MERN specialist is a highly skilled developer who has deep expertise in the respective or both stacks. From designing and implementing the whole application architecture and optimising performance and scalability to ensuring code quality and maintainability, MEAN/MERN specialists are responsible for all.

Web Application Developer: As a web application developer, you will focus more on building interactive and dynamic web applications. You can combine both front-end and back-end technologies to build web apps capable of handling complex functionalities.

To Conclude

We have entered into an era where technology is evolving at a rapid pace. The demand for individuals with expertise in full-stack development is skyrocketing and expected to grow in the coming future.

As both MEAN and MERN stacks offer ease and an efficient approach to full-stack development, these technologies have become very popular skills to acquire. If you master both stacks, you can position yourself as a valuable asset to big companies across industries and command top salaries.

In essence, by mastering MEAN/MERN stacks, you can build a strong foundation for a successful career in web development.

Whether you want to work with a tech giant, freelance, or start your own company, acquiring these in-demand skills will open up innumerable opportunities in the ever-evolving tech industry.

This entry was posted on December 27, 2024 by Prasenjit Das.

Data Science in India: Top Trends, Scope, and Challenges!

From tech giants to startups, organisations across India are striving to leverage the power of data. But what are the latest trends in data science? What opportunities and challenges aspiring data scientists can expect? Let’s dive in and find out!

We have stepped into an era which is super-dominated by data. With numerous large and small players entering the Big Data and AI ecosystem, India is expected to become the largest Big Data Analytics market in the world.

Data science has become a big thing in India–be it a profession, driving innovation, enthusiasm, or just a matter of interest. The data science industry in the country has seen humongous growth in recent years. The Big Data technology and service market size in India is $2.17 billion in 2024 and is projected to reach $3.38 billion by 2029.

The country’s large population and varied demography provide rich data sources, making it a highly potential ground for data-driven innovation. This also indicates significant career opportunities for data scientists in the country.

Whether you are a data scientist enthusiast, a student, a professional, or just interested in this fastest-growing technology, staying abreast with data science trends in India is worthwhile.

In this blog, we will examine the data science trends, understand the scope of this technology, and learn about associated challenges to build a perspective on what lies in future.

Discover the top data science trends in India, let’s first start with a quick overview!

Data Science: Overview and Its Impact

The data is pulled from multiple sources including social media, mobile, internet searches, surveys, websites, and more. This enormous data has created a new field of study i.e. Big Data. As the amount of data is massive and unstructured, it needs to be examined to make effective decisions. The entire process of extracting meaningful insights from data is not only time-consuming but also quite complex for companies. This need contributed to the advent of data science.

Data science has emerged as one of the most transformative forces which is rapidly reshaping industries and societies across the globe. By 2030, the data analytics market in India is projected to reach a revenue of $21,286.4 million.

Data science involves extracting invaluable insights from big data or huge amounts of complex data. By applying machine learning algorithms, statistical methods, and data mining techniques, data science experts identify hidden patterns, make predictions, and drive innovation.

Let’s learn about the impact of data science in various industries.

Healthcare

Data science is revolutionising healthcare. The size of AI in the healthcare market in India hit $374.7 million in 2023 and is projected to reach $6.9 billion by 2032. AI-powered data science enables personalised treatment plans, precise diagnosis, and efficient resource allocation.

By analysing patients’ data including medical records and genetic information, data scientists can predict diseases and come up with innovative treatments. This not only reduces healthcare costs but also improves clinical outcomes and speed-up drug discovery.

Finance: India’s finance and banking sector revenue rose from $575 million in 2016 to $756 million in 2017. In the finance industry, data science aids in risk assessment, investment strategies, and fraud detection.

By analysing historical data, economic indicators, and social media sentiments; data scientists create models to forecast market trends and examine creditworthiness, and future investment opportunities.

Retail: In 2023, retail analytics in India was worth $411 million and it’s expected to be a whopping $2.6 billion by 2032 which is a rapid growth of 21.4% each year.

Data science helps retailers to understand customer behaviour, personalise marketing campaigns, and optimise inventory management. It helps retailers to forecast demand and improve supply chain efficiency.

Marketing: Today, more and more businesses are using AI to improve their marketing methodologies and outcomes. Companies are expected to spend $8.51 billion, on marketing technology with AI by 2024.

By enabling targeted advertising and data-driven decision-making, data science is reshaping the entire marketing ecosystem. It helps marketers to identify potential customers, optimise marketing strategies, and measure the effectiveness of overall campaigns.

Transportation: With a massive 87% of passenger traffic and 60% of freight movement, road transport is the lifeblood of India’s transportation network. Here, data science greatly helps in improving traffic management, route planning, and logistics.

By analysing weather conditions, historical patterns, and real-time traffic, data scientists develop smart transportation systems that minimise travel time, reduce congestion, and improve fuel efficiency.

Top 5 Data Science Trends in India Reshaping the Industries

Here are the top 5 data science trends that are rapidly shaping the industries in India.

Trend 1: Generative AI and Its Applications

Generative AI, a specialised artificial intelligence technique is revolutionising industries by creating various types of content including text, images, and music. Generative AI is powered by advanced machine learning models that generate creative and realistic outcomes.

Key applications of generative AI include content creation, image and video generation, customer service, drug discovery, and product design.

Trend 2: MLOps and Its Benefits

MLOps or machine learning operations is a process that aims to deploy and maintain machine learning models efficiently and reliably. This approach involves a combination of ML best practices and software engineering.

Key benefits of machine learning operations include

Faster time to market.
Automation of repetitive tasks.
Improvement of model performance to ensure optimal production.
Enhanced collaboration between data scientists and engineers.
Optimisation of resource utilisation.

Trend 3: More Python-powered Apps

Python has become a go-to language for data science and machine learning due to its simplicity, versatility, and extensive libraries. This has resulted in a high surge in Python-powered applications across multiple industries.

Python is a popular programming language because it has beginner-friendly syntax. It boasts an extensive library for data analysis, web development, and machine learning. It runs seamlessly on Windows, macOS, and Linux. Plus, it has a large and active community of developers.

Trend 4: Companies Hire More Data Analysts

As more and more businesses & companies are realising the value of data-driven decision-making, it has led to a rising demand for skilled data analysts who can extract valuable insights from large sets of data. By 2025, there will be 137,630 data science job openings.

Data analysts are essential for:

Data cleaning and preparation.
Discovering hidden patterns and trends.
Applying statistical techniques to pull meaningful conclusions from data.
Communicating extracted insights to stakeholders.

Trend 5: Data Science is Evolving From a Craft to an Industry

Data science is shifting from individual work to a more formalised, structured, and industry-wide approach. This evolvement is driven by the need for scalable, efficient, and reproducible data science processes.

Industrialised data science characteristics include:

Using clear and standardised processes for collecting, cleaning, analysing, and modelling data.
Leveraging technology to automate pipelines.
Model deployment and monitoring to ensure it performs optimally.
Fostering collaboration between data scientists, engineers, and other team members.
Leveraging cloud-based infrastructure for flexibility and scalability.

What is the Scope of Data Science in India?

Data science is rapidly expanding in India. Today, AI is the cornerstone of innovations across industries and even society. AI is a specific application of data science focusing on creating smart agents capable of doing various tasks requiring human intelligence such as reasoning, learning, and problem-solving.

With AI integration, data scientists can uncover deeper patterns, make accurate predictions, and automate many complex tasks. Here is the breakdown of key aspects.

Rise in the Demand for Data-Driven Insights

From healthcare, finance, retail, and transportation, to government sectors; almost every industry is relying on data-driven insights to make strategic decisions. This has massively contributed to the exploding demand for data scientists to help companies, startups, and government organisations make data-driven decisions.

Government Initiatives

Digital India, a government initiative is driving the technology adoption and data-driven solutions across multiple sectors. Also, many online platforms and academic institutions like Karmick Institute offer quality data science courses to make this technology accessible to a wide audience and help fill the skill gap.

Career Opportunities & High-Paying Jobs

As the demand for data scientists is high in India, they command high salaries due to specialised skills. The average pay scale of a data scientist in India is ₹9,98,656 per year, it can go higher based on location or company one is working with.

In 2022, there were more than 18,000 data science job roles in the BFSI sector in India. This field offers a wide range of in-demand roles such as data engineers, machine learning engineers, data analysts, and data scientists.

If you have an interest in this field, you can kickstart your data science career journey and carve a flourishing career in this promising industry with our advanced full stack data science with AI and ML course.

Ethical Considerations and Social Impact

India is taking many initiatives to prioritise AI safety and responsible data usage. This has created massive opportunities for data scientists to work on a plethora of projects that have a social impact. As data privacy regulations have become more stricter, data scientists play a key role in ensuring compliance and data security.

Data Science Challenges in India

While India has emerged as one of the major data science and AI hubs globally, the following challenges hinder its full potential.

Data Quality & Accessibility

Data is difficult to consolidate and analyse as it is often fragmented across organisations and departments. The poor quality and fragmented data are one of the major hurdles in India’s data science landscape. Moreover, issues related to data quality like missing values, inaccuracies, and inconsistencies impact the insight’s reliability.

Talent Shortage & Skill Gap

While there is a huge demand for data scientists in the country, a significant shortage of skilled professionals can be seen across multiple industries. This skill gap hinders the adoption of data-driven decision-making. The industry lacks talent with essential technical skills and knowledge in the domain which limits the data science potential in India.

Ethical Considerations & Bias

Data science is becoming more powerful each day. Here, data privacy, ethical concerns, bias, and security are even more critical. Avoiding discriminatory outcomes and ensuring fairness in AI algorithms becomes a bit challenging. Addressing these issues is crucial to build trust and ensure responsible and ethical usage of data science.

Infrastructure & Computational Resources

Having a robust infrastructure and computational resources is critical for data science. India needs to invest in highly functional computing facilities, data storage solutions, and cloud infrastructure to support data processing and analysis on a large scale.

Cultural and Organisational Barriers

Cultural and organisational barriers such as traditional mindsets of people and resistance to technological changes can obstruct the adoption of data science. Overcoming these challenges requires a strong focus on data literacy and data-driven decision-making.

In Conclusion

India’s growing data science landscape is driven by its diverse population, multiple data sources, and ascending government initiatives. The country is witnessing significant growth in data science, AI technology, and demand for skilled professionals.

Data science is transforming various industries including healthcare, retail, finance, transportation, and marketing.

However, challenges such as skill gaps, ethical concerns, data quality, infrastructure limitations, and cultural barriers can hinder the full utilisation of data science.

To overcome these challenges, India needs to promote data literacy, invest in computational resources, and foster a data-driven culture.

This entry was posted on December 20, 2024 by Prasenjit Das.

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