Generative AI Gold Rush: Get in on the $7T Bonanza before It’s Too Late!


Generative AI Gold Rush: Get in on the $7T Bonanza before It’s Too Late!

The Generative AI Revolution: Unleashing a $7 Trillion Economic Paradigm Shift

Generative AI is all the rage — particularly since May 24, when chip maker Nvidia forecast mind-blowing revenue growth driven by demand for its chips

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Generative AI is all the rage — particularly since May 24, when chip maker Nvidia forecast mind-blowing revenue growth driven by demand for its chips from consumer internet companies like Microsoft, Google, and Meta Networks.

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After decades of unrealized hype, the promise of artificial intelligence seems to be finally coming true. Generative AI, in particular, has captured the attention of the media, investors, and business leaders. It is predicted to have a significant economic impact, creating wealth and transforming industries. To capitalize on this opportunity, it is crucial to understand the entire Generative AI ecosystem and identify the stocks and markets with the most potential.

Generative AI’s Economic Impact

Generative AI, which refers to machines that can generate text or create photorealistic images in response to natural language prompts, has the potential to drive major economic change. According to Goldman Sachs, it could raise global GDP by nearly $7 trillion, representing almost 7% growth, and boost productivity growth by 1.5 percentage points. The impact of Generative AI could be felt across various industries, creating markets worth hundreds of billions of dollars.

Furthermore, Generative AI has the potential to automate around 300 million full-time jobs. While there is a concern about job displacement, Goldman Sachs economists estimate that only 25% to 50% of jobs exposed to AI-induced automation would be replaced entirely. Instead, AI technology is expected to complement most jobs, leading to the creation of new roles and increased demand for workers in sectors such as webpage design, software development, digital marketing, healthcare, education, and food services.

Creating Demand in Supplier Industries

To harness the power of generative AI, developers need to build and train AI models. This process presents significant growth opportunities for technology and service providers. Developing AI models involves representing various elements, such as words, images, sounds, and designs, as “vectors” to analyze patterns and generate meaningful output. Companies in the technology sector are using generative AI to enhance productivity, expedite drug discovery, and accelerate software development.

The market for generative AI software is estimated to reach a total addressable market of $150 billion, representing 22% of the global software industry. As software providers integrate AI into their applications, they can charge higher prices, driving the growth of this market. Additionally, cloud services providers such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure require technology to design, train, and operate generative AI models. The capital expenditure for hardware, including graphics processing units and tensor processing units, presents a significant market opportunity.

Mapping The Generative AI Value Network

To fully comprehend the generative AI ecosystem and identify the best investment opportunities, it is essential to map out the value network. This network consists of various industries involved in the creation, deployment, and utilization of generative AI technologies. Each link in the chain represents distinct profit potential, customer criteria, capabilities, and return on investment.

The generative AI value network comprises five clearly-defined links: semiconductors, network technology suppliers, cloud services providers, applications, and consumers. However, it is worth noting that management consultants and capital providers could emerge as independent publicly traded companies, similar to the dot-com boom.

Industry Participants


Semiconductors play a vital role in training generative AI models as they require computing networks capable of handling numerous computations simultaneously. Graphics chips, specifically, are crucial for this process. Nvidia, a leader in this category, has experienced remarkable growth due to high demand for its GPUs. The company’s stock market capitalization has surged significantly, with Tesla’s CEO Elon Musk estimating that an updated version of generative AI models would require three to five times as many of Nvidia’s advanced processors.

Another semiconductor company, Advanced Micro Devices (AMD), is also competing in this growing market. AMD’s CEO, Lisa Su, is reorganizing the company to prioritize AI chips, such as the forthcoming MI300 CPU/GPU, which aims to reduce the time required to train and operate generative AI models.

Network Technology Suppliers

To accelerate communication among servers involved in generative AI model processing, networking hardware is essential. This segment has the potential to become a multibillion-dollar market in the coming years. Arista Networks stands out as a provider of computer network switches designed to speed up communications in hyperscale data centers operated by Meta Networks, Microsoft, and others. Arista is in the early stages of developing technology for generative AI and is starting to envision future demand from larger hyperscale customers.

Cloud Services Providers

Cloud services providers, including Amazon AWS, Google Cloud, and Microsoft Azure, operate the computing networks that deploy GPUs, network hardware, and servers for generative AI models. The worldwide cloud revenue is expected to experience a surge driven by the growing demand for generative AI from hyperscalers like these providers.


Ultimately, the investment in generative AI technology must result in applications that people are willing to pay for. Microsoft is a prominent player in this space, thanks to its ChatGPT, which has attracted millions of users since its launch. Adobe has also entered the market with its AI models called Firefly, focusing on generating media content. The market for enterprise generative AI applications is projected to grow rapidly, offering significant opportunities for revenue generation.


Generative AI applications offer numerous possibilities for businesses and individuals alike. These applications can include building chatbots for customer service, creating deep fakes, improving dubbing quality in movies and educational content, writing emails, creating artwork, enhancing product demonstration videos, recommending new drug compounds, designing physical products and buildings, improving chip designs, and composing music in specific styles or tones.

Management Consultants and Capital Providers

As generative AI continues to evolve, the need for management consultants who specialize in advising companies on deploying generative AI, managing associated risks, and building high-impact applications will increase. Similar to the dot-com boom, there may also be opportunities for capital providers, including venture capital firms, to fund generative AI startups that go public, creating investment opportunities for interested stakeholders.

Investing and Competing in the Real World of Generative AI

To capitalize on the opportunities presented by generative AI, investors should focus on companies that build the best products to address significant customer pain points, capture market share across multiple large markets, and have the capabilities to keep customers satisfied by offering new and desirable products. Entrepreneurs interested in this field should assess their strengths and weaknesses and build a team capable of transforming their ideas into fast-growing publicly traded companies.


Generative AI has the potential to reshape industries, drive economic growth, and create significant wealth. As the ecosystem continues to evolve, understanding the various industry participants and their roles becomes crucial for investors and business leaders alike. By recognizing the value network and identifying the right investment opportunities, stakeholders can position themselves for success in the rapidly expanding world of generative AI.


  1. What is generative AI? Generative AI refers to machines that can generate text or create images in response to natural language prompts.
  2. How does generative AI impact the economy? Generative AI has the potential to raise global GDP, boost productivity growth, automate jobs, and create new employment opportunities.
  3. What are the job implications of generative AI? While some jobs may be replaced by AI, most jobs are expected to be complemented rather than fully automated. Generative AI is likely to create new roles and increase demand for workers in various sectors.
  4. Which industries can benefit from generative AI technology? Generative AI technology can benefit industries such as technology, healthcare, education, software development, digital marketing, and many others.
  5. How can investors and entrepreneurs capitalize on generative AI opportunities? Investors should look for companies that build excellent products, capture market share, and have the capabilities to satisfy customers’ evolving needs. Entrepreneurs should assess their strengths, build competent teams, and identify high-potential markets for their generative AI solutions.


  • comment-avatar
    Amanda B. 12 months ago

    Curious to see how things go with Adobe’s Firefly. I think it should go well but there are certain hurdles to surpass to make it a worthwhile AI model.

  • comment-avatar
    Charles 12 months ago

    Like it or not, AI is here to stay and thrive. And we need to learn to use it to our advantage. AI should be a tool that helps propel humanity to the next level. And yes, those that learn to work with AI and help this industry grow should be making lots of money soon.

  • comment-avatar

    AI technology is here to complement most jobs, not to replace them entirely. If we fear AI we won’t use it wisely and to its full potential. If we embrace it and see how it can help improve our lives, we will make it work. What if instead of working 8 hours on a project we could work 2? And then have the other 6 to spend with loved ones? This is what AI can help with.