Generating Content and Profit: Examining Potential Business Models of Generative AI


by Pedro Palandrani

Generative Artificial Intelligence (AI) has the potential to transform many industries and revolutionize the way we live and work. As this technology continues to develop and mature, there are many different business models that are emerging to take advantage of its capabilities. In this piece, we’ll explore what we believe are the three most important business models for generative AI: models-as-a-service, built-in apps, and vertical integration.

This piece is part of our Generative AI series of research. To access all our research on the topic, Click here,

key takeaways

  • The model as a service (MaaS) provides low-cost, low-risk access to generative AI with limited upfront investment and a high degree of flexibility.
  • Built-in apps provide highly customizable and specialized solutions with a high degree of scalability.
  • Vertical integration leverages existing systems and apps to enhance their offerings with Generative AI capabilities.

Generative AI Model-as-a-Service

Model-as-a-Service (MaaS) is one of the most popular business models for generative AI developers. That’s what we’re seeing today with OpenAI, which licenses its GPT-3 AI model (the platform behind its popular ChatGPT product) to Microsoft for use in its Bing search engine. OpenAI is also expected to charge consumers $20 per month for the premium version of ChatGPT.1

With MaaS, companies can access generative AI models through the cloud and use them to create new and innovative content. This business model is similar to the subscription-based model that exists for most software today. These subscriptions can be monthly, semi-annual or annual, thereby generating recurring revenue for the developers offering these services. One of the biggest benefits of MaaS is that it allows companies to access the latest and greatest generative AI models without investing in the infrastructure and resources required to build these models from scratch. This makes it easier and more cost-effective for companies to leverage generative AI to create new and innovative experiences. Additionally, MaaS offerings such as OpenAI’s GPT-3 and Google’s BERT are highly customizable, allowing customers to tailor these models to their specific needs and use cases.

Of note, it’s likely that we’ll eventually see an incremental fee based on the model’s usage. This is similar to what we see today from public cloud providers, or hyperscalers, such as Amazon’s AWS or Microsoft’s Azure. This is known as the pay as you go model, where customers pay only for the services they use. This model is flexible and allows customers to scale up or down their usage based on their needs, and pay only for what they use. This model will also allow providers to manage their cost structure, as each query run through an AI model has an associated cost, which is currently estimated to be around two or three cents. OpenAI’s DALL-E platform, a text-to-image AI model, currently implements this type of pricing structure.

For example, companies can use generative AI to build virtual customer service agents that can assist customers with their inquiries or use AI to generate news articles, product descriptions and marketing materials. Some of the most popular MaaS offerings for generative AI include OpenAI’s GPT-3 and Google’s BERT. These platforms can also create original work, such as social media content, video games, computer code, graphic design, and more. As the models get better, they are starting to produce human-scale results and, soon, they may start to produce extraterrestrial-level results.2

built-in apps

Another important business model for generative AI is built-in apps. With this model, companies can build new apps on top of generative AI models to create new and innovative experiences. For example, companies can use generative AI to create unique and engaging gaming experiences or generate music, art, and other forms of creative expression.

A good example of this use case is Jasper, an AI content platform founded in 2021 that aims to enable growing businesses to leverage AI to scale their content strategies.3 The company has its roots in content manufacturing. Its founders saw the huge difference generative AI could make for their clients, allowing them to quickly and efficiently create and test ad variations to discover which insights would have the biggest impact. When given a prompt, the platform automatically selects the language model best suited to the particular use case. It aims, inter alia, to improve professional output by adding context, reliable source citations and more current data.4

vertical integration

With a vertical integration business model, companies can leverage generative AI to enhance their existing offerings and create new value for their customers. For example, companies can use generative AI to improve the accuracy and efficiency of their language translation services, or to analyze large amounts of data and make predictions about stock prices and other financial metrics. By leveraging generative AI to enhance their existing offerings, companies can create new and valuable experiences for their customers and improve their competitiveness in their respective markets.

Search engines are a great example. Generative AI could lead to the development of search engines that can generate more accurate and personalized results for users, rather than simply relying on pre-existing web pages. It is already working with Microsoft to integrate ChatGPT into Bing in an effort to challenge Google’s dominant position in the search market. Google search makes up about 60% of the company’s total revenue, which is why Google responded quickly with the announcement of plans to launch its own version of ChatGPT and integrate it into Google Search. Microsoft, on the other hand, has a more diverse set of revenue streams, of which search is only a small part of it.

Google and Microsoft Revenue Analysis

Conclusion: There Are Many Ways To Leverage And Monetize Generative AI

It’s worth noting that these business models are not mutually exclusive, and many companies are using a combination of them in an effort to maximize the value they can create with generative AI. For example, a company can use MaaS to access generative AI models, build new apps on top of these models to create new experiences, and then use vertical integration to enhance its existing offerings. Is. In short, generative AI offers the potential for a variety of monetization strategies, many of which promise to be quite lucrative.

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1. Clarke, M. (2023, February 1). OpenAI announces ChatGPT Plus at $20 per month. The edge
2. Global X ETF. (2022, December 12). Thematic Outlook for ‘Charting Disruption’ 2023 and Beyond.
3. Y Jasper is a leader in content creation using Artificial Intelligence. Accessed February 13, 2023.
4. Same.

Originally published on Global X ETFs,

The views and opinions expressed here are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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