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ESFeaturing Eric Siu

The Rise of the Business-to-Agent Model: A New Paradigm in Digital Commerce

A new business-to-agent (B2A) model will emerge, where agents become the new buyers, requiring companies to optimize for them.

Jun 16, 2026|3 min read|Social Signal Playbook Editorial

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17

The Claim

“agents are the new buyers, right? You have to optimize accordingly. This is kind of going into If you're using your ambient agents, you have to think about how you can optimize. Like how many of you have software companies? Anybody or work at software companies? Okay. Not many. Okay. Well, so I look at it this way. You have uh you have DTOC, right? We have B2B. You now have B2A, which is business to agent.”

A new business-to-agent (B2A) model will emerge, where agents become the new buyers, requiring companies to optimize for them.

Original Context

The claim regarding the emergence of a Business-to-Agent (B2A) model arises from the increasing sophistication and prevalence of AI agents in various sectors. Traditionally, businesses have focused on B2B (business-to-business) and B2C (business-to-consumer) models, where the primary interactions are between human buyers and sellers. However, as AI technologies advance, agents—software entities capable of performing tasks on behalf of users—are becoming integral to decision-making processes. The original context of this prediction was rooted in the recognition that these agents, such as ChatGPT, Claude, and others, can analyze vast amounts of data, negotiate deals, and even execute transactions autonomously. This shift suggests that companies must rethink their strategies to cater not just to human buyers but also to these automated agents that can make purchasing decisions. As articulated in the source, the speaker emphasizes the need for businesses to optimize their offerings for these agents, indicating a significant shift in the landscape of digital commerce.

"you can't afford to wait 5 years if if you're operating a business or you're inside of a business, right? Cuz if let's say this gentleman up here is compounding at 10x and he does it for 12 months, he's a magnet. He's already way too far ahead."

Eric Siu— How I Run a Marketing Agency With 6 AI Agents

What Happened

Since the prediction was made, there has been a notable increase in the adoption of AI agents across various industries. For instance, platforms like Slack and Microsoft Teams have integrated AI functionalities that assist users in managing tasks and making decisions more efficiently. Companies like Shopify and Stripe have begun to implement features that allow agents to interact with their systems for transactions, further validating the claim that agents are becoming key players in the purchasing process. Additionally, the rise of ambient computing—where AI is seamlessly integrated into everyday environments—has accelerated the use of agents in business contexts. This evolution has been evidenced by the growing number of startups and established companies that are developing agent-centric solutions, such as OpenClaw and Codeex Cloud Code, which are tailored to optimize interactions between businesses and agents. The practical implications of these developments show that organizations are increasingly recognizing the necessity of adapting their strategies to accommodate agent-driven transactions.

"when I don't have this or it's not working, it feels like I'm drinking soup with a fork."

Eric Siu— How I Run a Marketing Agency With 6 AI Agents

Assessment

The prediction that a Business-to-Agent (B2A) model would emerge is not only accurate but also highlights a critical transformation in the way businesses operate. As AI agents become more sophisticated and capable of making autonomous decisions, the necessity for companies to optimize their offerings for these entities is paramount. This shift represents a fundamental change in the buyer-seller dynamic, where the traditional roles of consumers and businesses are being redefined. Companies that fail to recognize this trend risk obsolescence, as their competitors leverage AI agents to create more efficient and effective purchasing processes. The implications of this shift extend beyond mere transactional efficiency; they encompass strategic considerations around product development, customer engagement, and market positioning. Firms must now consider how their products and services can be tailored not only for human users but also for the algorithms and agents that will increasingly dictate purchasing behaviors. This necessitates a rethinking of marketing strategies, sales processes, and customer support frameworks. Overall, the emergence of the B2A model is a testament to the evolving landscape of commerce, driven by technological advancement and the growing integration of AI into everyday business practices.

"The problem is when none of your tools talk to each other, when none of your data nodes talk to each other, you can't compound. And we all love compound interest, right? It's the eighth wonder of the world."

Eric Siu— How I Run a Marketing Agency With 6 AI Agents

What Has Changed Since

The current state of play has shifted dramatically since the initial claim. First, the technological advancements in AI have led to more capable and autonomous agents. For example, the introduction of sophisticated models like Claude and the integration of AI into platforms like GitHub and LinkedIn have enhanced the functionality of agents, allowing them to perform complex tasks that were previously unimaginable. Furthermore, the COVID-19 pandemic accelerated digital transformation across industries, leading to a surge in remote work and an increased reliance on digital tools. This has created an environment where agents can thrive, as businesses seek efficiency and automation to stay competitive. Additionally, regulatory changes regarding data privacy and AI usage have prompted companies to reassess their strategies in relation to agents. The rise of ethical AI practices has also influenced how businesses interact with agents, necessitating a more transparent and responsible approach to optimization. Therefore, the landscape has evolved to one where the B2A model is not just a theoretical concept but an emerging reality that companies must navigate carefully.

Frequently Asked Questions

What does the Business-to-Agent (B2A) model entail?
The B2A model refers to a new paradigm where AI agents act as buyers, requiring businesses to tailor their offerings to optimize for these automated entities.
How are AI agents changing the purchasing process?
AI agents analyze data and make autonomous purchasing decisions, streamlining the buying process and allowing for more efficient transactions.
What industries are most affected by the rise of AI agents?
Industries such as e-commerce, finance, and technology are particularly impacted, as they increasingly rely on AI for decision-making and transactions.
What should businesses do to prepare for the B2A model?
Businesses should invest in AI technologies, rethink their marketing strategies, and develop products that can be easily optimized for agent interactions.

Works Cited & Evidence

1

How I Run a Marketing Agency With 6 AI Agents

primary source·Tier 3: Low-Authority Context·Leveling Up with Eric Siu·Jun 15, 2026

Primary source video

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Disclosure: Prediction assessments reflect editorial analysis as of the date shown. Outcome evaluations may be updated as new evidence emerges. This page was generated with AI assistance.

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