Rise of the A2A economy: How AI agent-to-agent interactions will reshape the world

1. Defining A2A: The new economic paradigm of AI agents

At its core, an A2A (Agent-to-Agent) economy represents a world where most interactions and transactions occur between AI agents rather than humans. Where businesses once negotiated directly with each other (B2B), and consumers engaged with trusted brands (B2C), these interactions will become largely automated.

Businesses will deploy teams of specialized AI agents with domain-specific intelligence that understand their product lines, inventory, pricing, delivery status, and even legal constraints. Consumers will have personal AI agents that function as everyday assistants, or even multiple agents for different facets of their lives—finances, entertainment, healthcare, travel—that manage day-to-day life in the context of personal preferences, affiliations, dietary restrictions, purchase history, and budget. These consumer-facing agents (A2C) will communicate with business-facing agents (A2B) that offer relevant services, and, eventually, most transactions will be AI to AI. It’s a pure A2A play.

The A2A world already exists in financial markets. Estimates suggest that 70% of stock trades are executed through algorithmic or AI-driven trading systems. These agentic AI algorithms analyze vast amounts of real-time market data, price signals, and even news events to execute split-second trades, capitalizing on opportunities humans are too slow to realize. In other words, global finance is already a microcosm of A2A, operating smoothly at a speed and scale that far exceed human capabilities.

2. A2C and A2B: Bridging the gap between AI agents

A2C (Agent-to-Consumer)

We can think of consumer-facing AI agents as an extension of the customer service chatbots and virtual assistants we see today. They improve the end-user experience by instantly reducing wait times, responding to queries, and providing personalized information. These AI agents are the next phase in the evolution, able to handle complex tasks independently, such as booking appointments, negotiating service contracts, and even managing insurance claims on behalf of the humans they represent.

A2B (Agent-to-Business)

On the other side of the equation, we have business-facing AI agents. These software entities embody an organization's commercial policies, pricing algorithms, supply constraints, and brand identity. They will interface not just with consumers' AI agents but also with other companies' agents.

For instance, the AI of a manufacturing firm could negotiate with the AI of a part supplier to source raw materials at the best price, while also considering quality and logistical constraints. These A2B agents can handle contract negotiations, perform risk assessments, and propose flexible payment schedules based on real-time operational data.

The culmination of these interactions—A2C and A2B—ultimately leads to full-blown A2A (Agent-to-Agent) ecosystems, where agents coordinate, validate, settle payments, and handle the minutiae of transactions automatically.

3. How A2A will transform everyday life

Let’s return to the example of the time-consuming and recurring task of planning a family vacation. Currently, you would have to research flights, hotels, car rentals, restaurants, events, and activities. This might involve comparing prices on different websites, reading reviews, and emailing or calling various vendors to confirm details. It’s a labor-intensive process that can easily consume hours or even days of your time, sometimes sparking heated debates with your spouse and causing huge anxiety as you juggle multiple responsibilities at once.

In an A2A future, your personal AI agent already knows your travel preferences, from lodging type, dietary restrictions, bed configurations, desired activities, vacation duration, and budget. You simply say: "Plan a one-week vacation to a warm beach destination in early August and incorporate our quarterly family rituals." Your AI agent then proceeds to communicate with hundreds of other agents representing airlines, hotel chains, boutique rental properties, restaurant reservation systems, and local tour operators on your behalf. It negotiates prices, checks availability, factors in dietary preferences against local cuisines, and coordinates with the AI agents of your children's schools or your workplace to avoid scheduling conflicts.

Once your agent has gathered all possible configurations, it narrows them down to three or five highly curated travel packages, each with optional add-ons. You glance at the offers, maybe tweak a detail or two, and hit "approve." The entire booking and payment process is executed in seconds. You, the human, only spend a few minutes reviewing the top suggestions, and discussing with your spouse becomes a pleasant experience as if a high-end concierge were serving you. Who wouldn’t want to win the partner-of-the-year award? 🙂

4. The economic infrastructure of A2A: Fees, audits, and proof of transaction

Transaction fees: Parallels with crypto "gas"

As these AI agents interact at scale, a high volume of data will emerge and grow over time across the internet. Negotiation requests, quotes, clarifications, confirmations, cancellations—each of these messages can carry value. Much like "gas fees" in blockchain networks, where every transaction on the chain incurs a small fee, there will likely be an analogous cost structure for A2A transactions that ensures the network remains viable and mitigates spam. These fees could fund the underlying infrastructure that routes messages between agents, authenticates them, and logs their interactions securely.

In practice, you might see micro-fees for:

1. Information requests: If your AI agent requests a pricing algorithm from a premium data provider, it might pay a small fee.

2. Negotiation steps: Each round of bidding or negotiation might incur a cost, ensuring that only serious offers persist.

3. Transaction settlement: Once you decide on a purchase, a slightly higher fee might cover record-keeping, dispute resolution, and contract signing.

VISA-like infrastructures for AI agents

In addition to fees, robust networks will be needed to serve as clearinghouses for these billions of daily transactions between agents. Think of it as a "VISA for A2A." This infrastructure would provide:

1. Identity verification: Confirming that an AI agent represents a particular business or individual.

2. Reputation and credit scoring: Assigning trust scores to AI agents based on historical performance, default rates, and complaints, much like credit bureaus do for individuals and businesses today.

3. Dispute resolution and audit logging: Providing a reliable, tamper-proof ledger of each transaction, so any disputes can be traced back to specific interactions.

4. Multi-currency and cross-border payments: Agents might transact in various currencies or tokens, requiring real-time conversions and compliance with international regulations.

This ecosystem of specialized financial rails and verification services will become the backbone of the A2A economy, ensuring smooth, secure, and trusted operations. It could consist of a few major infrastructure companies or evolve to be more decentralized than traditional legacy architectures.

5. Middlemen AI agents: The new service providers and opportunity for monetization

As the A2A economy evolves, new business models and value chains will emerge. One possibility is using "middleman AI agents" specializing in aggregating or processing data for a fee, potentially with a premium charge based on the quality and access to proprietary data.

For instance, an AI agent with a unique dataset on consumer trends in a specific niche can lease access to that dataset (or even to targeted insights derived from it) to other AI agents. These middleman agents can also handle compliance and security, ensuring only authorized agents can access private or proprietary data.

Similarly, specialized AI agent services might aggregate supply chain data across multiple industries, providing real-time insights on costs, shortages, or transportation bottlenecks. Other agents might handle contract drafting and interpretation using natural language processing models trained on legal precedents, standardizing the contractual side of A2A commerce and drastically reducing friction.

6. Security, policy, and data access for AI agents

Given these AI agents' high level of autonomy, data security and policy enforcement will become ever more critical. Businesses must set clear guidelines for their agents: which data can be shared, which vendors are off-limits, maximum budget thresholds, and negotiation leeway. Compliance with regulations—GDPR for data privacy, ISO27001 & SOC 2 Type II for security-sensitive enterprises, HIPAA for healthcare confidentiality, or region-specific consumer protection laws—must be coded into the very architecture of these agents.

In this future, the boundary between who is responsible (human or AI) for a transaction blurs, raising new ethical and legal questions. If an AI agent violates a contractual agreement, who is held liable? If an AI agent accidentally leaks confidential data, who or what is penalized? As these intelligent systems become key players in the global economy, robust governance and oversight will be critical to prevent abuse and ensure fairness.

7. Scaling up: Why the AI A2A economy will explode 10-100x

Scalability is one of the biggest reasons A2A is poised to explode in the next decade. Humans are limited by time, attention span, and the speed at which they can process and act on information. AI agents, on the other hand, can handle parallel negotiations with thousands of counterparties simultaneously. By leveraging vast computing resources, they can navigate enormous data sets—monitoring fluctuations in material prices, consumer sentiments, or real-time events—to inform their negotiations.

As the cost of cloud computing and advanced AI models continues to decline, the barrier to entry for A2A participation also decreases. Businesses of all sizes will adopt AI agents for efficiency, and consumers will embrace them to save time and money. This exponential adoption creates a network effect: the more agents that exist, the more valuable it becomes for every new entrant to have an agent.

The speed and scale at which we have grown in computing power are enormous, even when viewed through the lens of the classic Moore’s Law. In the CES 2025 keynote, NVIDIA unveiled the 5090 GPU, which contains an astounding 92 billion (!) transistors—a remarkable 92-billion-fold increase over the 80-year period since the invention of the very first transistor in 1947 (which was much larger in size, too!).

It's easy to envision a near future where 10 to 100 times more online messages are sent between AI agents instead of humans. From mortgage approvals to e-commerce purchases, to supply chain management, AI agents will coordinate behind the scenes, quietly powering the global economy at speeds and volumes unfathomable today.

8. Embracing AI agents and the A2A economy future

The Agent-to-Agent (A2A) economy will fundamentally reshape how we conduct business and personal transactions daily. Humans will delegate these tasks to specialized AI agents instead of spending countless hours on price comparisons or contract negotiations. These agents will talk to one another—A2B, A2C, and ultimately A2A—exchanging information, negotiating terms, and executing contracts almost instantly.

The result? An economy that can expand and adapt at an astonishing pace, one in which higher-level strategy and oversight remain human tasks. At the same time, the heavy lifting of data processing and negotiations are relegated to tireless AI agents. This transformation will require new infrastructures, akin to the payment rails and clearinghouses we see in traditional finance or the gas fees in cryptocurrency networks, to ensure transactions are secure, auditable, and free from fraud.

Over the next 5-10 years, as AI capabilities become more sophisticated and accessible, expect to see a paradigm shift across every industry—from retail to healthcare, hospitality, finance, and beyond. A2A is not just another tech buzzword; it's an emerging economic reality that, once it matures, will become as indispensable, if not even more valuable, than the internet itself.

The foundations are laid. The benefits are clear, from faster transactions to cost savings to personalized offerings. If you're a business owner, start thinking about how to deploy AI agents to handle your routine processes. If you're a consumer, brace yourself for a future where booking a trip or choosing a health insurance plan could be as simple as clicking "approve" on your AI agent's recommendation. I would encourage you to "hire" your first personal AI agent in 2025. In this imminent landscape, the lines between B2B, B2C, and C2C will blur as more interactions are orchestrated by artificial intelligence.

Welcome to the world of A2A—where autonomous agents drive interactions and transactions, propelling the global economy to grow a hundredfold.

To learn more about the coming A2A revolution, you might enjoy these related resources:

• What is agentic AI?

• What are AI agentic workflows?

• How to build an AI agent: 8 key steps