GPT Natives: What Will They Be Like?

Are you also sensing that the media is much less focused on expounding the influence of millennials and centennials on tomorrow’s businesses, or is it only me? Were millennials and centennials the construct of analysts who needed new topics to dissect at seminars? Did the pandemic force all of us—behaviour-wise—to quickly become millennials and centennials so that the chatter on the subject has subsided over the past year or so? I think it is a combination of both. 

Today, the real question that stands before an enterprise is: How will generation AI, born between 2010 and 2025, the first to arrive in an algorithmic age, reshape our business? We can be moderately confident of being able to understand this generation. It is growing up with relatively simple AI-driven applications like Siri, Fortnite, TikTok, and your everyday banking and ride-hailing apps. 

However, it is the generative pre-trained transformer natives (GPT natives) that we need to turn our attention to. GPT natives will be the highly advanced turbo-charged versions of generation AI. They are going to shake the world.  

Those born between 2017 and 2032 will qualify as GPT Natives. 2017 was the year Google introduced the first transformer, which at the time was a “novel neural network architecture based on a self-attention mechanism” designed to understand the relationship between words in a sentence. 

The initiative was similar to GPT in theory and intent, but no one called it that until OpenAI came along. So, 2017 marks the arrival of the first GPT natives and it will bring more change than dreamt of by millennials and centennials.  

GPT natives will reinvent our institutions of learning and recast our ideas of society and leadership. They will reshape businesses and launch new revolutions, not with the help of autonomous cars and drones (although there is no denying these will help), as we once speculated, but with generative AI as their key tool.  

They will use the technology to look deep and sharpen their creativity. This is in stark contrast to the history of industry in the last two centuries. Most processes and inventions have been focused on improving productivity. Peter Drucker, whose understanding of the modern business corporation is widely acknowledged, says that the productivity of manual workers grew 50-fold during the last century alone. 

However, we rarely, if ever, hear of businesses investing as much into improving the creativity of workers. They try, but most fail. We do not hear of creativity in business at scale, the same way we hear about productivity. Creativity in business has remained limited to a few people like Edison, who invented the light bulb; Steve Jobs in consumer electronics; Walt Disney in entertainment; and David Ogilvy in advertising.  

The pursuit of creativity is time-consuming, expensive, and fraught with uncertainty. Improving productivity has been easier. The reason is that most of us are geared to using the thoughts and ideas we have come across recently. We live in the now. That’s where we look for the best ideas. If we could study history, we would have access to the best ideas ever. Generative AI will make that possible. It will make the process of sifting through history- known experiences and ideas- faster, cheaper and with predictable outcomes.  

The Harvard Business review, in an article titled 'AI Can Help You Ask Better Questions— and Solve Bigger Problems' by researchers Hal Gregersen and Nicola Morini Bianzino, said that their research showed that 94 per cent of the time, AI-led respondents had questions that were different than they would have otherwise asked. 

Gregersen, who is an author and a Senior Lecturer in Leadership and Innovation at the MIT Sloan School of Management, and  Bianzino, who is the global chief technology officer (CTO) of EY and holds a master’s degree in artificial intelligence and economics from the University of Florence, found that the technology allows “us to engage in more abstract questioning and shifting our focus from identification to ideation.” 

How does this translate into real-life innovation? Gregersen and  Bianzino provide an eye-opening example. They explain how the director of predictive analytics at Colgate-Palmolive used AI to figure out how charcoal became a popular ingredient in products. Charcoal in toothpaste, soap, shampoo, shaving cream, and pet care products has become extremely popular, providing a sharp differentiator in a market of me-too products. 

The Colgate-Palmolive algorithm generated thousands of less apparent questions that helped the company search for data and trace the 20-year history of charcoal from South Korea to the sourdough loaf at your breakfast table. The director of predictive analytics says that looking back into history has put them ahead of the curve by a decade. 

As a result, they now have the confidence to follow a path that will lead to identifying the next charcoal in cosmetics. That is just one example of how GPT natives will be able to create new ideas faster by moving out of the clutches of “now” and looking deeper into history.  

I will not be hasty in imagining that business will give up the pursuit of productivity overnight. But I am willing to bet that GPT technology is moving fast enough and becoming accessible enough to bring that change in our lifetime, making it possible for us to pursue creativity with the same single-mindedness as we pursue productivity.