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 truly buzzworthy technologies in recent times to have captured the whole world's imagination. What sets Gen AI apart is its practical usage – the potential for rapid adoption at scale. As a result, 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). 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 Generative AI Is and How It Differs from Other Trends
Before we delve deeper into this subject, it’s important to understand some of 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 which is similar to the training data but has 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 – also known as chatbots - provides a curated interaction with an information source. Chatbots allow interactions through a seemingly intelligent conversational manner. Typically pre-trained, they are used by enterprises to handle simple, repetitive tasks and to provide accurate responses to common customer queries. GPTs, on the other hand, 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 name now making the rounds, ChatGPT, is just a specific use case of GPT - one where the chatbot is used to interact with a GPT information source. In this instance, the GPT information source is trained for a specific domain by OpenAI, and this training data used on the model determines how questions will be answered.
It is therefore noteworthy that ChatGPT is a small subset of Gen AI technology, whose 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 (a 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 output – 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-user mark within two months. This fast-paced proliferation in Gen AI technologies seems 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 - thereby redefining 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 With that in mind, the need of the hour is a solution with a transformative effect on the whole world. The last time we received this sort of push with technology was when personal computers first became ubiquitous in the workplace. Generative AI holds the potential to provide a similar impetus for faster economic growth, and in an equitable manner. But this time, the growth will not be limited to certain parts of the developed world but will extend to smaller countries and businesses, in the private and 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 generative AI? The simple answer is that it promises to revolutionize the way work is done, opening new opportunities for businesses and verticals including programming, content management, customer experience, product engineering and design. Since this could mean a complete transformation of entire business models and industries as soon as 5 to 10 years from now, it is imperative that enterprises identify a compelling generative AI strategy and relevant use cases without delay.
Generative AI is set to make a huge impact in the following business areas going forward:
Increased Efficiency: Generative 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: Generative AI enables 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 — including videos, images, songs, stories, and code — can be created and the output can be fine-tuned through an 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 and other information. For example, search engines and browsers can be trained to produce personalized, richer customer experiences based on users’ patterns of behavior.
The bottom line is that generative AI presents a massive opportunity for businesses to drive innovation, reduce costs, and boost productivity — enabling 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 generative 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 organizations and preparing for the coming wave of generative AI, businesses can capitalize on this revolution and gain a competitive edge. That’s why it’s so important to stay informed and be ready for what is to come. The future of generative AI is happening now — are you ready to embrace it?