The B2AI Revolution

Optimizing for AI Decision-Makers

In 2021 here at Matters2, we started talking about a powerful idea: Business to Algorithm (B2A) where firms interact with automated systems to trigger actions without human intervention. Machines that detects wear and orders its own replacement part exemplified this logic-based automation.

Today, this model is materially evolving. Artificial intelligence systems do not merely follow predefined triggers. They now interpret, decide, and act autonomously, profoundly altering how decisions occur in business and commerce. We call this the era of Business to Artificial Intelligence (B2AI).

This shift is not just technological, it has strategic, economic, and competitive consequences: businesses will need to target AI systems to leverage their contact points with consumers.

Intelligent Recommendation Engines: The New Decision Middleware

AI-powered recommender systems have transformed how choices are navigated: they operate across multiple domains, interpreting data collected through various channels, analyzing user behavior, understanding preferences, and tailoring campaigns to each individual user.

Corporate AI systems can now move from a few customer personas to individualized action. But that's not what we want to discuss: the most significant change happening right under our noses is how everyone uses simple tools every day. Google is evolving, and new generations are increasingly turning to chatbots for their answers. In fact, Google itself is increasingly becoming a chatbot with search results at the bottom.

These AI tools aren't just providing information: they're fundamentally changing the relationship between users and choices. Most importantly, they answer our questions and recommend solutions. I repeat: they recommend solutions. That means that an AI system might decide to recommend you, or your competitor.

This will be particularly central, as leading AI platforms transition from free or research-oriented models toward monetised services that embed commercial incentives into knowledge and recommendation pathways.

Monetisation and Market Incentives: The Coming Structural Shift

A crucial dimension of B2AI, still emerging but inevitable, is the monetization of AI outputs. Leading AI platforms, including ChatGPT (OpenAI), Gemini (Google), and Claude (Anthropic), offer advanced language and reasoning services for free or through subscription models. But subscriptions aren't the game they're playing. They haven't even started monetizing their services yet.

According to the Wall Street Journal, Anthropic and OpenAI don't plan to turn a profit until 2028-2030. 

Subscription prices will inevitably rise, similar to what we saw with services like Uber or Deliveroo once they stopped being subsidized by VC money. When the market is fully penetrated by a few dominant incumbents, big tech will close the taps and subscriptions will climb. But that's just the tip of the iceberg. The real money lies elsewhere.

Monetisation strategies will increasingly include advertising, sponsored recommendations, revenue-sharing with commerce platforms, and prioritisation of paid business partners.

AI recommendations will increasingly be shaped by economic incentives. When users rely on AI for decisions about which software to purchase, which vendor to contract, or which healthcare provider to choose, the system's business model will influence which options are recommended and how they're presented.

We've seen this before. Search engine results shifted from relevance rankings to monetized placements with Google Ads. AI responses are heading the same direction, embedding sponsored prioritization that places advertisers before users' interests.

And what about organic visibility? How will companies create relevant content that gets picked up by these models? The race for "GEO" (Generative Engine Optimization), the successor to SEO, has already begun. 

The Strategic Imperative: Preparing for the B2AI Era

As AI becomes the new buyer interface, the competitive frontier is shifting fundamentally. Success no longer depends solely on optimizing for human attention: it requires optimizing for AI decision ecosystems that evaluate, prioritize, and recommend on behalf of users and enterprises. 

Just as search engines required businesses to master SEO, the B2AI era demands new competencies: understanding how AI systems interpret value, weigh commercial signals, and position offerings within their recommendation logic. The firms that recognize this shift early and begin treating AI platforms as critical stakeholders in the customer journey will establish compounding competitive advantages. 

The transition to B2AI isn't coming. It's already here. The only question is whether your business is ready to compete in it.