Each time a new business ecosystem is forming, we got to ask a simple question: where's value created?

And once we are able to classify the ecosystem based on where value is created we can ask: how's value captured?

From the above we understand the business models building on top of that ecosystem.

Since the release of ChatGPT at the end of November, one thing is clear AI commercial viability is accelerating, this giving us a glimpse about how the AI ecosystem is building up.

Let me explain.

The foundational layer

That might be comprised of general purpose engines like GPT-3, DALL-E, StableDiffusion and so on.

This layer might have the following key features:

General-Purpose: it will be built to provide more generalized solutions to any specific need.

This layer might be mostly an B2B/Enterprise layer, on the one hand, powering up a plethora of businesses.

Just like AWS in the 2010s, powered by the applications that made of Web 2.0 (Netflix, Slack, Uber and many others).

The AI foundational layer (still based on centralized cloud infrastructures) might power up the next wave of consumer applications.

That will be a commercial Cambrian explosion..

Multimodal: these general-purpose engines will be multi-modal.

Meaning they might be able to handle any sort of interaction, be it text-to-text, text-to-image, text-to-video, and viceversa.

Thus it might move in two directions.

On the one hand, the UX might be primarily driven by natural language instructions.

On the other hand, the built-in AI into the plethora of tools on the web will be able to read, classify and learn patterns from all formats availanle on the web.

This two-way system might bring to the next evolution of foundational model, to become general-purpose engines able to do many things.

Natural Language Interface: the main interface for those general-purpose engines might be natural language.

Today, this is expressed in the form of a prompt (or a natural language instruction).

Prompting though might remain a key feature of the foundational layer, but it might instead disappear in the apps' layer, where those AI engines might primarily work as push-based discovery engines (the AI will serve what it thinks it's relevant to users).

Real-time: these engines might be able to adapt in real-time, with the ability to read patterns as we navigate the real-world.

This - I argue - will be a key feature to enable these general purpose interfaces to be integrated into Augmented Reality!

A middle layer

That might be comprised of vertical engines (imagine here you find your AI Lawyer, Accountant, AI HR Assistant or AI Marketer).

This middle layer might be built on top of foundational layer, combines other "middle layer" engines able to become great at very specific tasks.

This middle layer might:

Replicate corporate functions: thus a first step in this direction might be an AI that might be able to replicate each of the relevant corporate functions.

From accounting, to HR, marketing and sales.

This middle layer will enhance a company, making it possible to run departments that are a combination of humans and machines.

Data moats: here differentiation might be build on top of data moats.

Meaning that by continuously fine-tuning foundational layer engines, to be adapted to middle layer functions, these AI specialized will become relevant for specific tasks.

AI engines: these middle layer players might also have the ability to add other engines on top of existing foundational layer, in the creation of specific data pipelines to train the models for specific tasks.

And the ability to have those models adapted to make them more and more relevant to the specialized functions.

And the apps' layer

That might see the rise of a plethora of smaller and much more specialized applications built on top of the middle layer.

These will evolve based on:

Network effects: here scaling up the user base will be critical to build network effects.

Feedback loops: users' feedback loops might become critical to enforce network effects.

What business models will we see?

In my opinion, the Foundational Layer might be together the new App Store and AWS!

Meaning, on the one hand, it will work as the underlying infrastructure to build new apps.

On the other hand, it might be the marketplace where these apps are build!

The Middle Layer might initially primarily work as an Enterprise Business Model.

Thus, providing organizations with very customized solutions that will fit to the company's goals.

Thus, companies might have those AI Engines on the pay-checks, almost as if this is the new employer's force.

The Apps' Layer might follow three main kind of business models: Ad-based, Subscription-based, Consumption-based.

That's it for today.

Should I write a short book about AI business ecosystems?

Ciao!

With ♥️ Gennaro, FourWeekMBA

P.S. I'm playing with the AI to see the kind of interesting tools we can provide you for business productivity. So we released the Article Summarizer and Rephraser Chrome Extension. It's a simple, AI powered tool, which will give you - with a right click - the ability to summarise or rephrase any article you're reading...Check it out!​

We also built an AI detector, to give you the chance to understand if the content was written by the machine! Of course, take into account that 1. the detector does a better job on longer content (must contain at least 2 paragraphs), and 2. that is an intelligent guess, but use also your judgement!

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