Since the first theoretical exchanges on artificial intelligence (AI) in 1943, this technology has seen remarkable evolution, transitioning from limited use in specialized fields to omnipresence in our daily lives. One of the most notable recent developments is generative AI, which has been widely popularized by applications such as OpenAI’s ChatGPT, launched in late November 2022. This advanced form of AI can generate entirely original, human-quality content simply in response to textual prompts. According to a June 2023 report by McKinsey & Company, generative AI could contribute between $6.1 trillion and $7.9 trillion annually to the global economy by boosting worker productivity. To put these figures in perspective, the same study estimates that all AI technologies combined could increase productivity by $17.1 trillion to $25.6 trillion each year. Thus, despite its significant impact, generative AI represents only a fraction of the overall economic potential of artificial intelligence, highlighting its importance while recognizing the broader contributions of AI to the global economy.
What is Generative AI?
Generative AI (GAI) refers to a specific segment of machine learning technologies that has recently acquired the ability to quickly produce content in response to textual prompts, whether they are brief and simple or long and complex.
These tools can create new audio, visual, and video content, but it is primarily text-based conversational AI that has captured the public imagination. Users can interact with these text-based AI models, learning from them in a manner similar to human interaction.
Generative AI quickly gained popularity following the launch of ChatGPT, a chatbot developed by OpenAI based on their GPT-3.5 neural network model, on November 30, 2022. “GPT” stands for Generative Pre-trained Transformer, a term that primarily refers to the underlying neural architecture of the model. Unlike historical chatbots like MIT’s ELIZA from the 1960s, which relied heavily on predefined rules and lacked contextual understanding, modern generative AI models do not follow such rigid rules or patterns. These systems, akin to primitive brains, learn from real-world data and autonomously develop an understanding that allows them to generate relevant content in response to prompts. The exact processes by which these models adjust and develop their algorithms remain largely unknown, even among AI experts.
Both small and large businesses should be optimistic about the opportunities offered by generative AI to automate intellectual work, which has often resisted automation until now. These tools revolutionize the automation of intellectual tasks by generating writings, images, sounds, and videos that resemble those produced by humans, based on simple textual instructions in English. This ability to collaborate with humans to create practical and relevant content could radically transform workplaces.
ChatGPT: The Most Popular Generative AI
ChatGPT became the most popular generative AI shortly after its launch in late November 2022, introducing the general public to the power of generative artificial intelligences. Simply by entering text, users receive relevant responses, demonstrating the interactive capabilities of AI.
This innovation met with resounding success, surpassing expectations by reaching 100 million users in just two months — a feat that took TikTok nine months and Instagram two and a half years. As of February 2, 2023, ChatGPT had recorded the fastest growth ever observed for an application.
How Does Generative AI Work?
Generative AI primarily relies on two advanced branches of machine learning: machine learning and deep learning. The latter uses complex mathematical models to perform more sophisticated tasks. These technologies depend on neural networks, systems that allow a computer to automatically perform the tasks assigned to it.
Regarding text generation, generative AI specifically uses large language models (LLMs), which are programs designed to understand and generate human language. These models are trained on vast amounts of text to develop this capability.
Impact of Generative AI in Businesses
Generative AI pushes the boundaries of creativity in the business world, enabling the rapid creation of new content and designs. It transforms product development, marketing, and customer service, allowing companies to innovate more quickly and respond effectively to market needs.
Reflections on the Future
The future impact of generative AI on businesses and work methods remains uncertain, but investor enthusiasm for this technology is undeniable. Significant amounts are being invested in generative AI across various sectors of human activity, with venture capital firms, established companies, and numerous intermediary players rushing to fund specialized startups. The magic of large language models (LLMs) lies in their unique ability to simplify interactions between humans and big data, facilitating a quick and clear understanding of vast amounts of information. This capability heralds the integration of generative AI into a multitude of existing applications and stimulates the creation of a new generation of technologies.
According to Gartner, by 2024, 40% of enterprise applications will integrate conversational AI, and by 2025, 30% of companies will use AI to enhance their development and testing strategies, while more than 100 million workers will collaborate with “robo-colleagues” by 2026. However, the risks and limitations associated with generative AI could hinder this progression. Fine-tuning models to capture the specificities of a company can be complex, the high operating costs of intensive models, and the risks of leaking confidential data could discourage some businesses.
The adoption may occur at a slower pace than anticipated, similar to the Internet, whose full realization took a decade longer than early adopters had expected. Generative AI may follow a similar path, requiring time to develop the necessary infrastructure and for behaviors to adjust to the new possibilities offered by this technology.
Industry visionaries, such as Sean Ammirati, venture capitalist and professor at Carnegie Mellon University’s Tepper School of Business, speculate that generative AI could radically transform the structure of future companies. Using companies born in the digital age as an example, Ammirati suggests that new companies could be built from the ground up on a foundation of generative automation, eliminating the need to learn and unlearn manual processes, which could lead to a profoundly different and more efficient business model.
Generative AI offers revolutionary prospects for increasing creativity, efficiency, and personalization in the business world. Despite the challenges and uncertainties, its continued integration into business practices promises to profoundly transform how we work, innovate, and interact with technologies. Its future is largely in our hands, and the actions we take today will shape the landscape of tomorrow.
