Beyond the Buzz: Exploring the Practical Applications of Generative AI in Industries

K. C. Sabreena Basheer 26 Nov, 2023
10 min read


The world today is buzzing around the term ‘Generative AI’. Top tech and management firms including McKinsey, KPMG, Gartner, and Bloomberg are constantly researching to gauge the power of this new technology and predict its future. All these studies show that the rising impact of generative AI in the enterprise has made it an essential skill in today’s workplace. These surveys also show that GenAI is set to become a $1.3 trillion market by 2032, and everyone would want to be a part of it. This article discusses the applications, growth, and impact of generative AI across various industries and how you can be a part of the global change.

What is Generative AI and How Big is It?

Generative AI is no longer just a buzzword. This new technology where AI can create new content and learn through practice, has taken the world by storm. GenAI tools are basically large learning models (LLMs) capable of generating content based on the data they are trained on. They learn patterns and structures from the training data and produce outputs that follow similar patterns. These models can create images, video, music, speech, text, software code, product designs, and more. The possibilities of this technology are endless owing to the vast amount of training data currently available.

The last few months have seen a steady expansion of the field, with new applications and use cases of generative AI being discovered every day. At an enterprise level, GenAI integration has led to faster outputs, better productivity, and economic growth. As a result, more and more companies are now using generative AI to save time and money.

Enterprise applications of generative AI include automation, augmentation of humans or machines, and autonomous execution of business and IT processes. McKinsey reports that enterprises worldwide are maximizing productivity gains and minimizing risks by deploying generative AI tools. Companies are now investing more in generative AI training and coaching, use case selection, workforce upskilling, and risk controls. Going forward, organizations will require their workforce to be adept in generative AI to stay relevant in their jobs.

The Business Side of Generative AI

The GenAI market currently includes model training infrastructure, inference devices for LLMs, digital ads, specialized software and services, personalized assistants, and copilots that accelerate coding. While the companies that develop generative AI tools and software are the biggest beneficiaries in the domain, the applications of these products are helping industries across sectors to reap benefits.

So how big is generative AI today? In 2022, the GenAI market was evaluated at $40 billion, which has evidently grown with time. A report by Bloomberg Intelligence predicts that generative AI will become a $1.3 trillion market by 2032, owing to a compound annual growth rate of 42% in the coming decade.

2023: Generative AI’s Breakout Year in Enterprise

Generative AI has been on Gartner‘s Hype Cycle for Artificial Intelligence since 2020. However, 2023 has been its breakout year in enterprise. Although the technology is relatively new, it has flourished to become an integral part of almost every industry.

As per a global report by McKinsey, 33% of leading companies are already using generative AI, while another 25% of them are in the process of AI integration. The report also states that 22% of C-suite executives use AI tools for work.

As new uses and applications of the technology are being discovered, its usability is further expanding. Job roles across all levels in all sectors are being automated, minimizing human intervention, and saving human work hours for more important tasks. Enterprises are therefore on the lookout for AI-skilled talent, giving them an edge.

Furthermore, 40% of the companies surveyed by McKinsey are planning on increasing their investment in AI, as the technology advances. This shows that slowly, but surely, all jobs will involve some level of AI-powered functioning, and we all need to stay prepared for it.

What Enterprise Leaders Are Thinking About Generative AI

Business leaders from around the world are intrigued by the possibilities of generative AI and are convinced that it is truly a game-changer. Dr. Vikas Agrawal, the Senior Principal Data Scientist at Oracle Analytics Cloud affirms that generative AI holds the potential to revolutionize enterprise solutions, especially in areas related to text and user interfaces. Speaking of upskilling the workforce, he said, “As AI tools evolve, data scientists need skills to enhance and improve these tools, not just operate them.”

On a similar note, Jepson Taylor, the ex-chief AI Strategist at Dataiku stated that the triumph of an AI startup depends on recruiting the right talent. As the co-lead of the AI Masterclass at NYU, he foresees a future where AI systems will be able to write and enhance their code autonomously, ushering in more efficient and powerful applications.

In an interview with Analytics Vidhya, Sandeep Singh, Head of Applied AI at, drew a comparison between the AI ecosystem in India and the US. “India’s AI ecosystem is uniquely positioned for rapid adoption and productization, unlike the Bay Area’s research-focused AI landscape.”, he said.

Coming to industry leaders in India, Mr. Srikanth Valamakanni is the Group CEO, Co-founder, and Vice-Chairman of Fractal Analytics, one of the largest AI companies in India. He believes that most functions in an organization will get automated in the years to come, and only those who stay updated and have the edge can continue being assets to their companies.

Mr. Anand S., the CEO and Chief Data Scientist at Gramener sees generative AI as the next big thing since the launch of Google. He has already outsourced most of his coding work to AI and has trained a bunch of LLMs to do various tasks for him, thereby optimizing his work, and saving time.

GenAI Industry Growth in Different Sectors in 2023

Within a short span of time, generative AI has impacted almost all industries, making it a quintessential part of enterprises today. According to McKinsey, a majority of employees across regions, industries, and seniority levels are already using generative AI tools for work.

While technology, media, and telecom companies use generative AI the most, business, legal, and financial services are not far behind. Even healthcare, energy, and retail sectors have started harnessing the benefits of generative AI.

GenAI Industry Growth in Different Sectors in 2023

Future Predictions on the Growth of GenAI in Different Sectors

KPMG recently published a report stating the expectations of generative AI applications in the years to come, divided by sector and function. Here are some of the future predictions.

Future Predictions on the Growth of GenAI in Different Sectors

Why Adapt GenAI: Preparing People

Enterprises are constantly looking for ways to optimize processes and expand their business. The best way for enterprises to scale their operations is by increasing the productivity of their existing workforce. In today’s world, adapting generative AI tools is the most innovative and optimal way to do this.

Nearly 75% of the enterprises surveyed by KPMG agree with this, stating that generative AI will increase productivity. All these firms have either already embraced GenAI or are planning to do so within the next two years. While 68% of the survey participants think it will change the way people work, 63% of them believe that it will encourage innovation.

In the long run, mundane tasks will get automated, saving human intelligence for more strategic activities. GenAI tools aim at assisting employees to be more creative and skillful, and not replace them or take their jobs. However, 46% of the survey respondents believe job security will be at risk and generative AI tools can replace some jobs. The survey states that the jobs at highest risk are in administrative roles (65%), customer service (59%), and the creative fields such as marketing and design (34%).

What Can Organizations Do Now?

Tech giants like Nvidia, Amazon Web Services, Microsoft, Google, and OpenAI were the first ones to harness the technology. Lately, however, open-source models and cloud platforms have let smaller companies and start-ups get on the GenAI bandwagon.

71% of the enterprises surveyed by KPMG plan to implement their first generative AI solution within the next two years. So, it is still not too late for you or your organization to embrace the technology and make the best of it. Here’s what companies can do now to be a part of the latest technological revolution:

Be a First Mover

As per KPMG’s report, a majority of enterprises are yet to take their step toward generative AI. 71% of them plan on implementing their first GenAI solution in 6 months to 2 years. This makes now, the best time for your company to move in.

Adopting new technologies sooner rather than later promises many first-mover advantages. Firstly, you’ll get a head start on things. With the pace at which GenAI is expanding, the gap between first-movers and fast-followers is soon bound to widen significantly. At this point, it is still possible to catch up and keep track of new tools and applications.

Early adoption also gives you an upper hand when it comes to investing in the best talent, tools, and software. Further, it lets you figure out solutions for any risks or hindrances that may come in the way before your competitors do.

While this change may seem overwhelming, Analytics Vidhya is here to help you. We offer services in generative AI training, upskilling of employees, hiring AI-skilled talent, and developing a data-driven workforce.

Respond and Adapt

Successful technological transformation of enterprises involves constantly responding and adapting to inevitable changes. While generative AI is capable of doing this, employees using GenAI tools must know how and when to apply them.

Developing the best GenAI strategy involves a lot of trial and error. Enterprise leaders need to be ready to quickly assess, adapt, or pivot strategies to account for the enormous potential of generative AI. These leaders must therefore possess contextual knowledge of the business components as well as the technological aspects of GenAI. Analytics Vidhya offers comprehensive GenAI courses for employees of all levels, empowering them to make the right decisions to optimize and upscale their business.

Manage Change Boldly and Broadly

Generative AI is transforming everything – the way we think, create, work, interact, and live. Enterprises may be skeptical about reckoning with such a disruptive technological force. Enterprise leaders often find it challenging to figure out how to deploy generative AI to harness the best by minimizing the potential risks.

The only solution to facing this fear and boldly embracing the new technology is by empowering the leaders and the workforce at large, with clear and concise knowledge of generative AI. This will further prepare them to accept the changes in industry dynamics, business models, operating models, and the workplace.

Develop Generative AI Literacy

The successful integration of GenAI into any enterprise requires the workforce to develop literacy around this new technology. The company must be willing to invest in training its employees to ensure more productivity and minimize risks.

Now, learning new skills or upskilling may not be easy for everyone. It is hence important for the company to find the right courses, learning platforms, and instructors for employees of all levels. Analytics Vidhya can help you there by providing a comprehensive learning experience for all. We are equipped to train employees of every skill level, from C-suite leaders and VPs to managers, assistants, and even interns.

Find the Right GenAI Use Cases

While preparing to embrace new technology, it is important that enterprises have a clear idea as to what they wish to achieve through this change. Having a clear goal will help chart out the exact business needs and select the right genAI tools for the company.

Generative AI comes with endless potential and it is easy to get entangled in it, all at once. While GenAI can do almost everything, it may only be required in certain functions, in particular departments of the organization. It is therefore important to stay focused and be on track with what to adopt and what is the best way to get the desired results.

Enterprises may need to experiment with a few different tools, solutions, and strategies, before figuring out the best or most optimal approach. Defining the use cases is the first step towards any such experimentation.

Empower Responsible Use of AI

Using generative AI tools in enterprises comes with the risk of sharing confidential company information. Most organizations are concerned about cybersecurity and data privacy as they do not have a rigid structure or policies in place for governing, training, and implementing generative AI solutions responsibly.

While defining use cases and figuring out potential opportunities, it is also important to ensure the responsible use of generative AI. Enterprises need strong guardrails in place to limit any such risks – be it financial, reputational, or ethical. There must be a hierarchy of who is responsible and accountable for ensuring the responsible use of AI. The people involved in this must uphold ethical considerations and stay updated on new laws and regulations regarding the use of AI.

Address Critical Talent Questions

Embracing new technology into an enterprise would mean a change in job roles and the acquisition of new and skilled talent. The adoption of generative AI into the workforce is bound to change the work environment and existing practices. During this transition, it is important to ensure the existing employees embrace this change without fear.

Leaders in the enterprise must effectively communicate to their employees about changing roles, reengineered processes, and new behaviors, as and when they make changes. They must reassure employees that generative AI is just a tool for extending human capabilities, and will not replace them.

Challenges Faced by Organizations in Adapting GenAI

Although organizations are open to adopting generative AI, they often face certain challenges while doing so. Here are some of the most common challenges enterprises face while adapting GenAI.

  • New field: Since generative AI is a relatively new field, organizations may be skeptical about exploring it.
  • Lack of skilled talent: Organizations may find it hard to find expertise due to which the cost of training and upskilling may go high.
  • Pace and scale of AI development: The GenAI industry is changing too fast and that pace may worry companies from stepping into the field or catching up.
  • Lack of a clear business case: Many enterprises face the challenge of not knowing where and how exactly to use generative AI in their businesses.
  • Hallucinations and misleading outputs: Another common concern is regarding fake information created by GenAI, as the risks and consequences of such issues fall on the company and employees.
  • Cybersecurity and data privacy concerns: Since the use of GenAI tools involves the sharing of company data for training purposes, companies may be concerned about cybersecurity and data privacy.
Challenges faced by organizations in adapting GenAI

How Can Analytics Vidhya Help You?

If your enterprise wants to step up with generative AI but is facing any of the above-mentioned challenges, Analytics Vidhya is here to help you. We’ve helped a number of companies across 15 industries embrace the change and make the best out of this new technology.

Finding great talent in this field has become incredibly hard. But with us, it is both achievable & measurable. Your employees are your biggest assets. More so, when they can derive insights from data. We are here to train them on data analytics and generative AI to accelerate your business. We’ve trained over 3,50,000 learners and 5,000 employees helping them upskill in generative AI and improve their productivity.

Get ready to transform your enterprise into a GenAI-powered one with a little help from Analytics Vidhya. From running data literacy programs to performing maturity assessments and building internal communities, we bring our immense experience to our clients and partners.

We have successfully helped enterprises including TVS,, Fractal Analytics, Zepto, and American Express build AI capabilities and reap its benefits. We are here to help you too. Get in touch with us today.

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