The B2C2B osmosis fueling AI's Cambrian moment

Distinct from prior AI waves where enterprises had front-row access, consumers are at the frontlines playing an outsized role in defining today's AI frontier.

There were several exciting announcements from key players in the AI ecosystem yesterday, including Hugging Face’s launch of open-source HuggingChat and OpenAI’s preview of ChatGPT Business. Inspired by these developments, I discuss the power of the business-to-consumer-to-business (B2C2B) osmosis that has been the undercurrent of the recent AI wave.

Source: Bloomberg, “Forget Chatbots, This Is How Corporate America Is Really Using AI” (3/1/23)

AI is by no means a new concept. Society has been enamored by the concept of AI since the first half of the 20th Century. As seen in the chart above, corporations have been talking about the promise of AI in transforming businesses for many years now.

Source: TechTarget, “Generative AI Primer” (March 2023)

Well, then what is so special the latest AI Cambrian explosion that is resulting in so much palpable hype, and causing AI to seemingly penetrate every facet of our lives in previously unimaginable ways? Immense technological progress, resulting in advances in unsupervised learning, model architecture, and LLMs (timeline above), is certainly a core catalyst. In particular, generative capabilities from AI are now nearing human baselines.

While technological progress is a key factor, this is perhaps only one part of the equation as to why the latest AI revolution is seemingly more powerful than prior iterations. For one, the unprecedented democratization of AI research is a notable “why now” driver. Unlike in previous AI paradigms where innovations were confined to organizations that had sizable in-house R&D teams or a dedicated AI focus, there is now increased access to APIs and open-source models at the foundational layer, with contributions from non-profit institutions, big tech incumbents, and startups alike:

Source: Bessemer Venture Partners, “Rise of Synthetic Media” (7/21/22)

Such democratization has lowered barriers to entry and unlocked flows of knowledge such that more builders (both consumers and enterprises) can embed cutting-edge developments and participate in the movement even if they are not “AI-native”. This has led to a burgeoning startup ecosystem, competition driving increased product development, as well as an accelerated pace of innovation. There seem to be years of advancements happening in the span of mere days now:

Source: @AlphaSignalAI Tweet Thread

But perhaps the most effective “why now” driver that has been less discussed is the B2C2B adoption osmosis that has been highly unique compared to previous AI chapters. Distinct from their predecessors who prioritized enterprise distribution such that corporations could capitalize on new breakthroughs first, today’s AI businesses are granting first-hand exposure of the latest technology directly to consumers, and this adoption is consequently driving an unparalleled level of enterprise readiness:

My colleagues and I observed this inflection point approximately 10 months ago during OpenAI’s DALL-E 2 beta, but the floodgates truly opened in November 2022 when OpenAI built a very simple “chatbot” UI on top of GPT-3 and released ChatGPT directly to the masses. ChatGPT hit 100MM monthly active users in two months, making it the fastest-growing consumer application in history (chart below). GPT-3 had been around for 2+ years prior (and mind you OpenAI was founded ~8 years ago in 2015) but only corporations were able to take advantage of its capabilities up until ChatGPT was unleashed to the world.

Source: Bessemer Venture Partners, “State of the Cloud 2023” (4/10/23)

As individuals get increasingly comfortable with AI applications in their personal lives, they are subsequently questioning how they can bring these capabilities into the workplace with tangible enterprise use cases:

• If I can use ChatGPT to obtain answers quickly and easily, why not leverage AI to run intelligent searches or queries on company datasets?

• If I’m accustomed to ChatGPT summarizing my personal notes, why not apply the same workflow in the office to unlock productivity gains?

• If I rely on ChatGPT to generate tweets or write cover letters, why not use AI for copywriting or to create tailored content for my job?

Additionally, consumers have proven themselves to be influential participants who are actively shaping the direction of innovation, rather than simply being passive bystanders. The rise of autonomous AI agents is a great example where Auto-GPT and BabyAGI were conceived by individuals who were tinkering with the AI stack. These “experiments” have now left an indelible mark and sparked an innovation flywheel .

Source: @SigGravitas Tweet Thread

Consumer excitement is fueling enterprise readiness at rapid speed, and this pull is so powerful that it can no longer be ignored by corporations. Just yesterday, OpenAI announced a new ChatGPT Business subscription, on top of its existing enterprise offerings such as its API product and integration partnerships. Also yesterday, Microsoft reported better than expected earnings, pointing to AI as a key area for optimism where the company ascribed 1% point of Azure growth to AI services (this roughly translates to $400-$500MM annualized run rate according to Morgan Stanley), and also noted favorable feedback on its AI-powered business applications. Microsoft was one of the earliest tech giants to invest ahead of the recent GenAI ramp:

Source: Morgan Stanley, “Mapping the Generative AI Opportunity" (March 2023)

Within Corporate America, references to AI and related terms during investor calls are already up 77% from a year earlier. In Morgan Stanley’s latest 1Q23 CIO survey, AI/ML rose to become the 4th largest area of enterprise IT spend increase, and more CIOs are in the process of evaluating GenAI technology within this very year:

Source: Morgan Stanley, “1Q23 CIO Conference Call” (4/21/23)

In some sense, this B2C2B motion is reminiscent of a few other iconic platform and go-to-market shifts that were jump-started by consumers/end-users, such as the “bring your own tools” movement in the developer economy which formed the foundations for the product-led growth model. Another analogy is the consumer saturation of social media networks and proliferation of user-generated content leading to mainstream adoption of new platforms for modern brands. The gig economy permeating into organizations also shared similar patterns stemming from normalization of consumer behavior.

Since consumers are playing an outsized role in the recent AI tsunami, it is fitting that consumers also capture the most value during this Cambrian moment. As my colleague Talia Goldberg recently wrote, consumers are poised to be prime beneficiaries of the current AI revolution as all of us are positioned to accrue surplus. Today’s AI frontier is being directly defined by consumers at the frontlines, and this AI wave will go down in history accordingly as a movement of the people . Viva la AI revolution!

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