how to build an AI company!
I put together a framework or mental model to think about AI business models straightforwardly, with a four-layered approach.
What makes up an AI business model?
I put together a framework or mental model to think about AI business models straightforwardly, with a four-layered approach.
AI becomes the "connector" between value and distribution, enhancing both so that we can speed up valuable feedback loops, increase product velocity, and expand distribution!
This I called the Exponential Startup!
You can click on the image below to get the dynamic visualization of the framework.
Foundational Layer
What's the underlying technological paradigm of the business?
Open-Source: Utilizing a set of open-source generative AI models to enhance products.
Closed Source/Proprietary: Using closed-source generative AI models to enhance products.
Agnostic: Combining closed-source, open-source, or both generative AI models to enhance products via AI.
Value Layer
How does the AI underlying tech stack enhance value for the user/customer?
Perception: Changing the perception of the product through the underlying AI layer.
Utility: Significantly improving the product through the underlying AI layer.
New Paradigm: Transforming the current value paradigm through the underlying technological layer.
Distribution Layer
What key channels is the business leveraging, and how is the company building distribution into the product?
Growth Strategy: Combining technology and value to make products appealing to customers.
Distribution Channels: Leveraging various distribution channels to reach customers.
Proprietary Distribution: Utilizing proprietary distribution channels for product delivery.
Financial Layer
Can the company sustain its cost structure and generate enough profits and cash flows to sustain continuous innovation?
Revenue Generation: Generating revenue through AI-enhanced products.
Cost Structure: Assessing the cost structure of the AI business model.
Profitability: Evaluating profitability and cash flow of the AI business model.
Cash generation: Assessing the ability of the AI business to generate cash flow to sustain its continuous development.
AI Business Models Framework: Real-World Case Studies
DeepMind (Acquired by Google)
Foundational Layer: Closed Source/Proprietary - DeepMind's algorithms are proprietary and highly specialized.
Value Layer: New Paradigm - At the forefront of AI research, especially in deep learning.
Distribution Layer: Proprietary Distribution - Google uses DeepMind's technology for various applications. Right now DeepMind has been re-organized within Google to tackle the Generative AI race.
Financial Layer: Revenue Generation - DeepMind monetizes through collaborations and integrations within Google's services.
OpenAI
Foundational Layer: Open-Source - Initially, OpenAI provided various AI models openly. Then it closed its algorithims, to become a for-profit organization, launching its API access, and tools like ChatGPT and DALL-E.
Value Layer: Utility - They offer powerful AI solutions that serve multiple industries.
Distribution Layer: Growth Strategy - API integration, consumer-facing business (ChatGPT), enteprise services (ChatGPT Enterprise), partnerships (Microsoft), developers' community.
Financial Layer: Freemium Model, Enterpise Model, API (Pay-as-you-go).
Tesla
Foundational Layer: Closed Source/Proprietary - Tesla's Autopilot system is proprietary.
Value Layer: Utility - Improving car safety and driving experience.
Distribution Layer: Proprietary Distribution - Tesla cars are the primary distribution channel.
Financial Layer: Profitability - Autopilot adds significant value to Tesla's cars, enhancing profitability.
ChatGPT (by OpenAI)
Foundational Layer: Open-Source - Built upon the GPT architecture which was initially open.
Value Layer: Perception - Changing the way people interact with machines.
Distribution Layer: Growth Strategy - By offering a conversational AI.
Financial Layer: Revenue Generation - Subscription models for enhanced versions.
Neuralink
Foundational Layer: Closed Source/Proprietary - Their brain-machine interface technology is proprietary.
Value Layer: New Paradigm - Aiming to revolutionize human-computer interaction.
Distribution Layer: Proprietary Distribution - Directly through their medical devices.
Financial Layer: Revenue Generation - Through the potential sale and use of their devices.
NVIDIA
Foundational Layer: Closed Source/Proprietary - Their hardware and some software are proprietary.
Value Layer: Utility - Providing powerful GPUs essential for AI computations.
Distribution Layer: Proprietary Distribution - Direct sales and partnerships.
Financial Layer: Profitability - Sales of GPUs and AI-related hardware drive their profits.
Baidu
Foundational Layer: Closed Source/Proprietary - Their deep learning platform is proprietary.
Value Layer: New Paradigm - Leading AI research in China.
Distribution Layer: Proprietary Distribution - Integration within their services.
Financial Layer: Profitability - They drive revenue through AI-enhanced services.
Key Takeaways
Foundational Layer: Utilizes open-source, closed-source, or a combination of generative AI models to enhance products.
Value Layer: Changes product perception, significantly improves utility, and introduces a new value paradigm through AI.
Distribution Layer: Combines technology and value, leverages various distribution channels, and utilizes proprietary distribution channels.
Financial Layer: Generates revenue, assesses cost structure, and measures profitability and cash flow.
Over the years, I've been developing a few mental models to grasp the underlying structure of various business models.
So, if you want to tap into them, you can find them below:
These are just some of the mental models you find within Business Engineering, which is the whole discipline that combines business modeling, analysis, design thinking, and business acumen in a single subject to make sense of the business world.
You also get a first introduction to Business Engineering here.
Ciao!
With ♥️ Gennaro, FourWeekMBA