Generative & Agentic AI are Transforming our World
When historians look back on our day, they will conclude that November 30, 2022, was the day that human beings kicked off the creation of new forms of Artificial Intelligence (AI) that launched the most consequential transformation of our world in human history. If humanity learns how to use these new tools for the benefit of all we can create a post-scarcity world of global abundance.
As we saw in the last chapter the intelligence explosion has been talked about for 75 years. Now it is here!!! This will be our very last chance to guide this Technology Tsunami and direct it in a way that ensures it works for the benefit of humanity.
For a long time and to this day, most analysts and futurists have been trying to predict exactly when we will achieve Artificial General Intelligence followed by Artificial Super Intelligence. While these are still critical concepts to understand, they are not critical to understanding the economic impact of the Chat GPT moment nor does the AGI/ASI discussion help us understand the intermediary forms of AI that seem to have appeared out of nowhere. We will therefore take-up the AGI, ASI debate in the next chapter.
In this chapter, our goal is to explain where we are today with AI following the launch of ChatGPT. We will attempt to explain the impact and features of the relatively new forms of AI. We will explain Generative Intelligence, introduce Agentic AI and Robotic AI, and assess the economic impact of these forms of AI that are still human-directed.
In the next chapter, we will evaluate the near future where many are predicting the advent of all-powerful AGI and ASI is imminent. For us the fundamental feature of AGI and ASI is that they mark the point where humanity cedes autonomy to the AIs we are creating.
When Ray Kurzweil first predicted a rupture in the fabric of human history we were four decades away from that momentous event. Today that event is two decades away and for many, it will happen far sooner than even Kurzweil is predicting.
The Future is Here but Are We Ready for it?
We have created an intelligence explosion that will very likely bring about a rupture in the fabric of human history in the next two decades, if not sooner. The big question for educators and our global society is, are we ready for that rupture? Are we prepared for the massive transition that will take place in the coming decades as we develop new tools of unprecedented and unimaginable power?
How will we use these new tools? If these tools are used for the good of humanity, we can create a post-scarcity world of global, sustainable abundance, a world without poverty, hunger, and the need to work, a world of high universal income.
How often have you had a conversation relative to the potential for Sustainable Super Abundance with your classrooms, colleagues, or neighbors? We believe there is no more important conversation to be had in today’s world. However, before we can understand the potential for Sustainable Super Abundance it is critical to understand how the new forms of intelligence coming our way will impact our world.
Creating a New Digital Species
As Eric Schmidt the former CEO of Google, asserts in numerous interviews, AI is not overhyped it is underhyped when compared with its potential to transform our world.
The reason the transformation will be so profound is because we are creating a new form of intelligence. For the first time in human history human beings will begin to be rivaled by the new forms of intelligence we are creating, Moreover, the intelligence we create will continue to grow at an exponential rate if not a double exponential rate.
Moore’s Law saw computing capacity double every two years or 32x over a decade. AI Computing is now doubling every six months which means we will witness a million-fold increase over the next decade and this calculation does not take into account the impact of Quantum Computing.
Evolutionary biologist Bret Weinstein asserts that “we have created a digital species and no one on planet Earth can tell you what is going to happen.” We believe he is right on both counts.
The goal of this chapter is to paint as clear a picture as possible of where we are and where we are headed as it relates to the intelligence explosion and what the explosion of AI means for us. To get a handle on that we need to understand artificial intelligence.Mustafa Suleyman the co-founder of DeepMind and now CEO of Microsoft AI came to the same conclusion as Brett Weinstein following a candid conversation with his 6-year-old nephew that he relates in this Ted Talk, What is AI Anyway?
He explains that humanity is at an inflection point, suggesting that we cannot control what we don’t understand and therefore the mental models and metaphors we use to describe AI are all important. He explains that it is important that we be able to easily describe what it is we are building.
He goes on to say, “I think that AI can best be understood as something like a new digital species.” He predicts that we will come to see AI “as digital companions, new partners in the journeys of our lives.” He believes that this is the “most accurate way and fundamentally honest way of describing what is actually coming. And above all it enables everybody to prepare for and shape what comes next.”
We highly recommend watching the full 22 minutes of this Ted Talk. The above quotes start in minute 2:15.
For background info on this issue click here: A New Digital Species
Intelligence on Demand can Amplify Our Capabilities and IQ!!
In keeping with this thinking many futurists suggest we need to treat this new intelligence like a supergenius child providing it with humanist values carefully guiding its steps.
As we saw in the last chapter, the intelligence explosion has been talked about for 75 years. However, it took until November 2022 and the launch of Chat GPT to get people to begin to pay attention and understand the potential for AI to transform our lives.
ChatGPT effectively launched a new form of intelligence, a new form of “Thinking AI” that everyone with access to the internet can use. This form of AI has come to be known as Generative Intelligence. Unlike traditional AI, generative intelligence produces novel outputs that mimic or extend human creativity.
In his new serialized book Alive, former Google employee, Mo Gawdat provides an excellent definition of Generative Intelligence.
He explains that “True intelligence doesn’t just memorize knowledge. It grasps its essence and as a result, becomes able to create new forms of it. This is the biggest difference between a “generative” AI and, say, a search engine. For decades, Google memorized and organized the internet. When you prompted Google with a search term, it presented what if found and exactly how and where it found it. Gemini, and other language models on the other hand, respond to your prompt with its own interpretation of the core knowledge you seek. It does not show you what it reads, but instead generates a new representation each time you ask.”
Gawdat goes on to explain that with Generative AI (GI) we are “moving from cognition to creativity.”
Gawdat concludes that for the average human today, “I would say we’re borrowing 40 to 50 IQ points on top of our base intelligence. If you’ve ever worked with someone who has a greater IQ than you, as I have, you would appreciate how significant a lead for humanity that is. Even 10 IQ points can make all the difference…
As AI’s abilities continue to grow, we have access to more and more intelligence on demand and when I see it that way, I can’t help but view my AI infant children as some of the greatest blessings to have ever been given.”
Bill Gates: The Age of AI has Begun
In this March 2023 essay, Bill Gates declared that with the launch of ChatGPT The Age of AI has begun. He wrote:
“In my lifetime, I’ve seen two demonstrations of technology that struck me as revolutionary. The first time was in 1980, when I was introduced to a graphical user interface—the forerunner of every modern operating system, including Windows…
The second big surprise came just last year. I’d been meeting with the team from Open AI since 2016 and was impressed by their steady progress. In mid-2022, I was so excited about their work that I gave them a challenge: train an artificial intelligence to pass an Advanced Placement biology exam…If you can do that, I said, then you’ll have made a true breakthrough.
I thought the challenge would keep them busy for two or three years. They finished it in just a few months.
In September, when I met with them again, I watched in awe as they asked GPT, their AI model, 60 multiple-choice questions from the AP Bio exam— and it got 59 of them right. Then it wrote outstanding answers to six open- ended questions from the exam. We had an outside expert score the test, and GPT got a 5—the highest possible score, and the equivalent to getting an A or A+ in a college-level biology course…
…I knew I had just seen the most important advance in technology since the graphical user interface.
This inspired me to think about all the things that AI can achieve in the next five to 10 years.
The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.”
You can access the full essay here: https://www.linkedin.com/pulse/ age-ai-has-begun-bill-gates/
ChatGPT the Fastest Commercial Rollout in History
Every AI thinker on the planet Earth including the team at Open AI, who viewed the release as a low-key research preview, was shocked by the speed with which ChatGPT was taken up. The chatbot gained 1 million users in 5 days, reaching 100 million monthly active users within two months.
Source: ChatGPT’s Surprise at Launch Source: Perplexity AI https://www. chatbase.co/blog/chatgpt-adoptio
The speed with which Chat GPT and generative intelligence have been adopted makes clear how the pace of technological change is accelerating. It took 35 years for 25% of the US population to adopt telephones, 30 years to adopt electricity, 25 years for automobiles, 16 years for computers, 7 years for the internet, 4 years for Smartphones, and 6 months for ChatGPT. The pace of change is clearly accelerating, particularly as there is no great need to build out new infrastructure to deliver new products and services associated with generative intelligence. Something like generative intelligence can go global overnight.
Comparative Analysis – TABLE
|
Technology |
Time to 100M Users |
Time to 25% U.S. Population |
Key Adoption Key Barriers Drivers |
|
|
Telephone |
75 years |
35 years |
Business use, so- Infrastructure, cial connectivity cost |
|
|
Electricity |
~30–40 years* |
~30 years |
Industrial demand, Grid expansion, |
|
|
Urban lighting |
Rural access |
|||
|
Automobile |
~25–30 years* |
25–30 years |
Mass production, financing |
Roads, fuel infrastructure, cost |
|
Computer |
~15–20 years* |
16 years |
Workplace integration, software |
Cost, technical complexity |
|
Internet |
7 years |
7 years |
Connectivity, user-friendly browsers |
Access to PCs, dial-up limitations |
|
Smartphone |
2–3 years |
4 years |
Touch interfaces, apps, mobile networks |
Initial cost, learning curve |
|
ChatGPT |
2 months |
6 months |
Free access, viral appeal, versatility |
Scalability, energy costs, regulation |
Chat GPT’s growth has continued as has the competition coming from several competitors. As of February 2025, Chat GPT had reached 400 million weekly active users and hopes to reach 1 billion users by the end of 2025.
Source: Perplexity AI
https://opentools.ai/news/chatgpt-breaks-barriers-with-400-million- weekly-active-users-a-new-era-of-ai-adoption
The response from large technology companies looking to build and deliver their own brand of generative intelligence has also been unprecedented. It is hard to get good numbers on the current level of active monthly users in part because the industry is so new and in part because there is a range of definitions and categories. We have therefore used two separate sources in pulling together the numbers below.
What does seem clear from the above analysis is that there are 1.5 billion to 2 billion active monthly users of this transformative technology. That means that about one in four humans is using a technology that is less than three years old.
Indeed, this product is so new there is not really a single commonly used name to describe this segment of the AI industry. This part of the AI industry seems mostly to be described by its characteristics which include the use of large language models and natural language processing to motor tools like ChatGPT, Claude, Grok, and more.
We refer to this segment of the AI industry as the Generative Intelligence (GI) market where companies deploy activities that center on advanced LLMs that power applications such as chatbots, virtual assistants, automated content creation, translation, and task automation across industries like customer service, healthcare, education, and software development.
The ChatGPT Moment a Catalyst for Trillion Dollar Investments
While the general public may not be aware of the real and full potential of the AI revolution, the potential for dramatic transformation has not been lost on investors. The ChatGPT moment has unleashed the full fury of the global free enterprise system with investors across the globe gearing up to channel $1 trillion to $2 trillion in investments in Generative AI.
The Generative AI market has experienced explosive growth in recent years and is projected to continue expanding at a rapid pace. The current market size is estimated to range from approximately $14.6 billion to $67.18 billion, reflecting differences in definitions and scope (e.g., whether hardware, software, and services are all included) For 2025, projections suggest the market will reach between $37.89 billion and $66.89 billion.
Source: https://www.statista.com/outlook/tmo/artificial-intelligence/generative-ai/worldwide
The market is expected to continue to grow at compound annual growth rates of about 40% which means the AI market will reach somewhere from $960 billion to $1.3 trillion by 2032.
Source: https://www.abiresearch.com/news-resources/chart-data/generative-ai-market-size-worldwide
This growth is being driven by unprecedented levels of capital investment which went from $2.4 billion in 2020 to over $100 billion in 2024.
Summary Table
|
Year |
Capital Investment ($B) |
|
2020 |
2.4 |
|
2021 |
3–4 |
|
2022 |
4.3–5 |
|
2023 |
21.8–25 |
|
2024 |
48–131.5 |
Looking forward, the expectation is that investment in Generative AI will accelerate to $100–300 billion annually by 2027, stabilizing at $300–500 billion by 2030, with cumulative investments of $1–2 trillion from 2025–2030.
Beyond 2030, funding could reach $1 –- 1.5 trillion annually (2.5 -– 4% of U.S. GDP), driven by enterprise scaling, agentic AI, and global adoption, though energy and regulatory risks loom.
For background info on this issue click here: Generative Intelligence
Today’s AI: From Perception AI to Generative AI to Agentic AI to Robotic AI
While futurists and policymakers focus on when AGI will become sentient, business entrepreneurs like Jensen Huang are seizing the economic opportunity created by the ChatGPT moment. A moment that has seen Generative Intelligence, followed by Agentic AI which will soon be followed by Robotic AI.
Today’s AI: Perception, Generative, Agentic, Robotic = Fabulous Four
Tareq Amin & Jensen Huang on Humain–NVIDIA Partnership: Scaling AI Infrastructure https://www.youtube.com/watch?v=XaHSe33wVkY&t=4s
The CEO of Nvidia Jensen Huang took the opportunity to briefly explain the evolution of AI at the Saudi-US forum 2025 starting from minute 3:30 he explained that
“The first time you saw AI it was Perception AI. AI that can recognize cats, words, speeches, and sounds and speech. Perception AI then evolved into Generative AI where you could use words to generate words or use words to generate images or words to generate chemicals or proteins.”
While Huang’s goal in this talk was to highlight the move forward to the next levels of AI, we think it is important to pause here to fully understand how transformative the move from Perception AI to Generative AI really was. Indeed, we believe the move from Perception AI to Generative AI explains the ChatGPT moment as we effectively went from search engine to thought partner, echoing Suleyman’s comments that the new AI will become a digital companion that according to Mo Gawdat has the potential to significantly improve our IQ or our own intelligence.
For those paying attention, there was a history making event that anticipated the move to Generative Intelligence that occurred on March 10, 2016 and is now called Move 37.
Google’s DeepMind had invented a capacity to develop AI via self- learning or self-reinforcement. They channeled that capacity into a set of narrow AI goals building an “intelligence” called Alpha Go designed to play the incredibly complex, 2,500-year-old, East Asian game of Go.
After some training Alpha Go challenged the reigning world Go champion Lee Sedol to a series of matches. After winning the first game, Alpha Go shocked the world with Move 37, a move that had never before been used and a move that European Go champion Fan Hui described as “not a human move”. Alpha Go went on to win the match one decade ahead of schedule.
AlphaGo’s lead developer, David Silver, noted that the system “discovered this for itself” through introspection and analysis, hinting at a form of emergent creativity. The move underscored the effectiveness of reinforcement learning or self-learning. Click here for more on Move 37.
Perception AI is about understanding and interpreting existing information. It takes input data and extracts meaning, patterns, or insights from it. The goal of Perception AI is to understand and interpret data.
Generative AI creates new content based on learned patterns from training data. It doesn’t just analyze; it generates new information pulled together from its wealth of knowledge. Its goal is to create new original content or data.
The big ChatGPT breakthrough and insight was to make this new form of learning and creativity – generative intelligence – available to the general public for a wide range of topics.
In his talk, Huang goes on to describe the third era as being the Agentic AI era. Agentic AI surged into prominence in 2024 by leveraging Generative AI’s enhancements thereby enabling AI Agents to revolutionize industries by acting as intelligent digital agents.
“Then the third era, which is the era we are in right now, is AI technology that can reason. And the formulation and application of that capability are Agentic AI; AI that can have agency, it can use tools, it can reason, it can solve problems. Essentially a digital robot that sits inside the computer.”
Please pay attention to the words used by CEO Huang. In describing Agentic AI he tells us that this is an AI technology that can reason. He goes on to say that Agentic AI “can have agency, it can use tools, it can reason, it can solve problems.”
Huang’s characterization of Agentic AI is another huge step forward towards AGI particularly when we think of the impact of a digital robot sitting inside of a computer that now has an agency of its own.
One of the big questions we have been asking ourselves as AI dramatically grows its presence in our world, is where are we going to put all of this AI? Huang the founder of this $3.3 trillion company tells us exactly where he is going to put all of this AI, we are going to put the AI in robots.
“The next era, the era we are working on now, is AIs that understand the laws of physics, the common sense rules of the physical world…the cause and effect of the physical world. …The things that all of us humans understand about the physical world.
That next generation of physical AI along with all of the technology that has already been created could be embodied into a physical form and that physical form would be robotics.
So the era of AI is moving incredibly fast. We are in an agentic AI world today, and we are in a Robotics AI or Physical AI world shortly from now.”
Agentic AI and generative AI have significantly advanced the ability to embed AI in robots. Agentic AI enables autonomous decision-making and goal-oriented behavior, while generative AI enhances interaction and adaptability (e.g., natural language processing or generating realistic movements). These advancements make it easier to create intelligent, versatile robots compared to past limitations.
It seems clear that as we move from Perception AI to Generative AI, to Agentic AI we are moving closer and closer to AGI. And when we add Robotic AI to this list many suggest that we are starting to capture 95% of the economic benefit of these new tools that still rely on human guidance.