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Embracing the Wave

Generative AI, or Gen AI, is no longer a concept just for science fiction. The frenzy is here, it’s real and it shows no signs of abating. It is among the very few buzzworthy technologies in recent times that have captured the imagination of the whole world. What sets Gen AI apart is its practical usage – the ability to rapidly get adopted at scale. Organizations around the world are scrambling to decide how much money to spend on Gen AI products, which solution is worth the investment, when to get started, and how to alleviate the risks that come with this emerging technology.

According to a Gartner poll 1 conducted in March 2023, the buzz surrounding ChatGPT has prompted 45% of executive leaders to increase their investments in artificial intelligence (AI). The funding for Gen AI technologies in 2022 had reached nearly $2.6B, with 110 deals across the globe. Interestingly, 70% of the enterprises are already in investigation and exploration mode with Gen AI. In short, if you are an enterprise, you need to understand what this AI revolution means for you and your team.

What is Generative AI and How It Differs from other Trending Buzzwords

Before we delve deeper into this subject, it’s important to understand the basic concepts that are making news in the tech industry today. Forrester defines Generative AI as “a set of technologies and techniques that leverage massive corpora of data, including large language models, to generate new content in the form of text, video, images, audio, code, etc.2 Inputs may be natural language prompts or other non-code and non-traditional inputs.” Generative models learn the patterns and structure of the input data and then generate new content that is similar to the training data but with some degree of novelty. Generative AI, which includes chatbots and GPT (Generative Pre-trained Transformer) models, offers a range of use cases for enterprises, from customer service to problem-solving assistance for technicians.

At a high level, conversational AI, or chatbot, provides a curated interaction with an information source. They allow interactions in a seemingly intelligent conversational manner and are typically pre-trained. They are used by enterprises to handle simple, repetitive tasks and to provide accurate responses to common customer queries. On the other hand, GPTs are large language models that use machine learning (ML) and natural language processing (NLP) algorithms to produce output that ‘appears to have understood’ the question, the content, and the context.

The most popular word doing the rounds these days – ChatGPT, is nothing but a specific chatbot use case of GPT where the chatbot is used to interact with a GPT information source. In this case, the GPT information source is trained for a specific domain by OpenAI and this training data used on the model determines the way questions will be answered.

It is, therefore, noteworthy that ChatGPT is a small subset of Gen AI technology, and the market and practical applications are much broader. Large-scale language models were first used in 2011 by Google in Brain and later in BERT (applied to search results). Meta came up with OPT-175B (GPT equivalent), while OpenAI launched DallE (text-to-image) and Whisper (speech-to-text). All these are examples of how large language models can be used to handle a variety of tasks, catering to a wide range of scenarios, by managing different types of outputs – image, text, video, and speech.

The Promise and Potential

With the recent breakthroughs in technology, it is safe to say that the world is entering a Golden Age of AI. This revolution is unlike anything we have seen in history because of how rapidly it is being adopted. The ChatGPT platform blazed past the 100 million users mark within 2 months. This fast-paced proliferation in Gen AI technologies is set to bring forth exciting possibilities for all of us. It will enable humans to learn, create, and accomplish a variety of tasks in ways not seen before that will redefine productivity and the future of work.

Many experts believe that the economic growth in the world has frozen in the last few years. According to the World Bank Group, the worldwide economic output is projected to be around 1.7% in 2023.3 The need of the hour is a solution that has a transformative effect on the whole world. The last time we received this push with technology was back when personal computers became ubiquitous in the workplace. Gen AI holds massive potential to provide a similar impetus for faster economic growth, in an equitable manner. And this time, the growth will not be limited to certain parts of the developed world but will travel to smaller countries and businesses, both in the private as well as public sectors, with hardly any delay, ushering in a new era of better jobs, salaries, and quality of life.

Why Should Enterprises Care?

So why should enterprises care about Gen AI? The simple answer is that it promises to revolutionize the way work is done, opening new opportunities for businesses and verticals within like programming, content management, customer experience, product engineering and design. Since this could mean a complete transformation of entire business models and industries 5 - 10 years from now, enterprises need to identify a compelling generative AI strategy and relevant use cases starting today.

Gen AI is set to make a huge impact in the following categories in the future for businesses:

Increased Efficiency: Gen AI can automate tedious, time-consuming tasks, allowing employees to focus on more meaningful work. By leveraging AI-powered technologies such as natural language processing, neural networks, and automated decision-making, enterprises can improve the speed of their operations, which is very difficult to achieve through manual human effort.

Improved Accuracy: Gen AI allows machines to generate data with high accuracy. With a generative AI system in place, enterprises can process huge amounts of complex data quickly and accurately. This makes it possible to identify inherent patterns much more easily than ever before.

Optimized Costs: Enterprises can now streamline processes by eliminating the need for manual labor. By reducing the need for human involvement in certain tasks, businesses can save money on labor costs while ensuring consistency of output across all departments.

Generating Ideas: New content across a range of modalities, such as videos, images, songs, stories, code, etc. can be created and the output can be fine-tuned through a unique iterative process driven by user feedback.

Personalized Experiences: AI models are capable of generating information or creating content tailored to a specific audience based on their preferences. For example, search engines and browsers can be trained to produce personalized, richer customer experiences based on users' behavioral patterns.

The bottom line is that Gen AI presents a massive opportunity for businesses to drive innovation, reduce costs, and boost productivity—allowing them to enhance customer satisfaction and retention, augment revenue growth, and build an increasingly agile organization.

While ignoring its powerful impact on business could prove to be a costly mistake, the ethical and responsible implementation of Gen AI remains a puzzle for many companies as they continue to grapple with choosing appropriate applications to drive meaningful results.


Generative AI is revolutionizing the way businesses work and is set to become an invaluable tool for those who embrace it. With its potential to unlock unseen potential and data previously thought to be untouchable, organizations of all sizes stand to benefit from its adoption. By understanding the impact, it has on their organization and preparing for the coming wave of Gen AI, businesses can capitalize on this revolution and gain a competitive edge. That's why it’s important to stay informed and be ready for what’s to come. The future of generative AI is happening now - are you ready to embrace it?

Up Next: Any new technology comes with a host of implementation challenges and risks that organizations must address before fully committing to the investment. In the next blog, we will understand this emerging technology in greater detail, the challenges it brings, how HCL DRYiCE can help address those challenges with its own conversational AI platform, the ways in which generative AI can be incorporated into existing enterprise technology environments, and how businesses can responsibly and efficiently leverage generative AI”.

Reach out to us at to learn more.

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