By Tom Chavez and Adrien Le Gouvello
Today, 70% of U.S. stock trades are executed by algorithms, not humans. In digital advertising, real-time bidding systems make billions of ad placement decisions daily, with autonomous software determining what to buy, when, and at what price—all within milliseconds.
These aren’t isolated examples. They signal the early arrival of a broader shift: the Agent-to-Agent (A2A) economy—a world where AI-powered software agents transact, negotiate, and collaborate directly with one another, increasingly taking over the work humans once did. From B2B procurement to consumer travel planning, the future of digital interaction is being shaped not just by humans using tools, but by agents autonomously coordinating outcomes on our behalf.
The implications are profound: faster decisions, 24/7 operations, new types of marketplaces, and a redefinition of how businesses and consumers engage with each other. The A2A economy isn’t a concept for the future. In many ways, it’s already here.
What Is the A2A Economy?
In the A2A model, artificial intelligence agents—autonomous systems capable of decision-making and action—interact directly with one another. These agents can perform tasks, negotiate terms, and settle transactions with little or no human involvement. Their ability to learn, adapt, and act at scale enables a new layer of economic activity, one marked by speed, precision, and efficiency.
Picture a retail brand deploying an AI agent that automatically assesses ad performance and adjusts spend across multiple platforms. This agent could negotiate with other agents representing ad networks or media outlets in real time. Or imagine a procurement agent in a manufacturing company that sources materials by negotiating directly with supplier agents, comparing options, and locking in optimal terms—all while the team is offline.
A Familiar Pattern: Disruption Before Productivity
The emergence of A2A echoes historical transitions tied to General Purpose Technologies (GPTs)—innovations like electricity, the internet, or the personal computer that fundamentally reshape how business operates.
Economists such as Erik Brynjolfsson and Paul Krugman have emphasized that GPTs often produce visible disruption before measurable productivity. For example, desktop computing became commercially available in the early 1980s, but GDP data didn’t reflect substantial gains until the mid-1990s, when businesses adapted their operations and software infrastructure.
AI appears to be following this same arc. While foundational technologies like Siri and IBM’s Watson emerged more than a decade ago, it’s only now—with the proliferation of large language models, open-source agent frameworks, and API-accessible cloud services—that autonomous agents are beginning to scale meaningfully across business functions.
A New Kind of Marketplace
One of the most transformative aspects of the A2A economy is the rise of AI agent marketplaces—platforms where developers publish agents trained to handle specific business tasks such as data analysis, content generation, marketing automation, or QA testing. Companies can subscribe to these agents or integrate them into their workflows without needing to develop solutions from scratch.
This model has the potential to democratize access to enterprise-grade capabilities, enabling startups and small businesses to compete with far larger players. Just as cloud computing leveled the playing field by removing the need for in-house infrastructure, agent marketplaces could allow any organization to tap into specialized expertise instantly.
Major tech platforms like AWS, Microsoft, and Salesforce are already developing agent marketplaces within their ecosystems, but many early innovations are also coming from startups building tools for content creation, development infrastructure, and sales operations.
The Open-Source Acceleration
Another reason the A2A economy is gaining momentum is the availability of open-source agent frameworks that simplify the deployment of autonomous systems. Tools like AutoGPT, BabyAGI, and LangChain make it possible to break down complex tasks into subtasks and chain them together using large language models.
These systems can autonomously research, draft, summarize, and even take action—by sending emails, submitting forms, or calling APIs. As these frameworks become more robust, they will enable a wider range of businesses to implement agentic workflows with relatively little technical overhead.
What Leaders Should Focus On Now
Business leaders navigating this shift don’t need to adopt fully autonomous workflows overnight. But now is the time to start preparing:
– Start with the problem. Let pain points and inefficiencies guide your adoption of agentic solutions, rather than chasing novelty.
– Think holistically. Avoid fragmented experimentation with AI tools; instead, foster a team-wide culture of testing, iteration, and learning.
– Integrate incrementally. Identify specific workflows—like customer onboarding, A/B testing, or report generation—that can be automated with minimal risk.
– Prioritize governance. Ensure your AI tools respect privacy, compliance, and organizational standards. Many agents act fast—but not always transparently.
A2A and the Future of Work
As AI agents take on more of the tasks that previously required human coordination, new questions will arise around oversight, accountability, and strategic direction. Humans won’t disappear from the picture—but their roles will shift.
Rather than managing every transaction or workflow, professionals will increasingly orchestrate networks of agents, ensuring alignment with business objectives while focusing their time on creativity, judgment, and interpersonal collaboration.
In this way, the A2A economy doesn’t replace people. It redefines what they do—and how value is created across the enterprise.
Final Thought
The idea of autonomous agents transacting with one another might still sound futuristic to some. But as algorithmic trading, programmatic advertising, and open-source AI frameworks have shown, this future is unfolding rapidly—and in plain sight.
The organizations that prepare for it today will be the ones best positioned to thrive in a world where your next business deal might not involve a human at all—just two agents that know what to do.
About the authors
Tom Chavez is a serial tech entrepreneur and Co-Founder of super{set}, a venture studio that founds, funds, and builds technology companies.
Adrien Le Gouvello is a Partner at super{set} AI Advisors, bringing over 12 years of experience driving growth and transformation at the intersection of business strategy and AI.