The fact that AI chatbots have made our lives so convenient by answering every question, is already such a big achievement for the AI Industry. Another major step up to the internet now is AI Agents. With Agentic Internet, AI agents are going to do every task in your schedule and once you set everything up you wouldn’t even have to lift a finger. This isn’t future tech, it’s already happening today. Tech giants like Google and OpenAI are building the infrastructure right now. We’re already seeing impact at scale, with AI agents transforming workflows inside the Big Four consulting firms, proof that this shift is happening fast.
The Numbers Are Staggering
The agentic internet market is massively exploding, the numbers tell prove that:
- Market Size: $3.93 billion in 2022, with an annual growth rate of 42.8% till 2030, as per Grand View Research
- Economic Value: Approximately $450 billion by 2028 in the countries surveyed as per Capgemini 2025
- Productivity Gains: $4.4 trillion gradually made available, with enterprise productivity increasing by 40% as reported by McKinsey
- Business Adoption: 93% of leaders think that the large-scale use of AI agents within the next 12 months will provide them a strategic advantage
Gartner predicts by 2028:
- One-third of enterprise software will have agentic AI (compared to less than 1% in 2024)
- 15% of daily work decisions being made autonomously by AI agents (currently 0%)
- AI interactions resulting in the use of autonomous agents will account for one-third
What Makes the Agentic Internet Different
Conventional AI is traditional and has to be commanded. The agentic internet, on the other hand, doesn’t need a command.
Old AI: “Tell me the weather?” Answer: “It’s 72 degrees.”
Agentic internet: “Get me a flight to Chicago next Tuesday.” Operation: Finds flights, compares prices, buys ticket, adds to calendar, sends confirmation.
Additionally, there is something called PRAL loops which the agents’ refer to: Perceive, Reason, Act, Learn. They see the environment, decide what to do, execute the action, and advance over time. It’s mind blowing where the tech is headed towards. We’re already seeing real adoption too, with PwC launching Agent OS to coordinate AI agents across enterprise workflows.
How Agents Talk to Each Other
Google released the Agent2Agent (A2A) protocol in April 2025. This is a new standard language that AI agents can use to communicate, find each other, and work together. More than 50 technology partners were onboard, among them were Atlassian, Datadog, Elastic, UiPath, Capgemini, KPMG, and Accenture, all the big players. And in August 2025, IBM’s Agent Communications Protocol combined with Google’s A2A to form a single standard under the Linux Foundation. Now this standard is endorsed by Microsoft, AWS, Cisco, and 150+ other organizations.
Why this matters: The agentic internet would be impossible without a common protocol. In fact, agents must be capable of cooperating without any interruption even if different manufacturers have produced them.
The Risk Nobody’s Talking About
The agentic internet brings a whole new set of problems to the table that traditional AI has never had to deal with.
- Emergent behaviour: Single agents have limited behaviour. But the interaction of numerous agents leads to unforeseen consequences. The overbooking of all the meetings by the scheduling assistant might be a side effect that the company is not aware of. A trading bot might be the cause of a market crash. These are not faults. They are failures of the whole system resulting from the influence of agents on each other.
- Feedback loops: Agents are able to make decisions at a much faster rate than humans. The one mistake is therefore magnified as it spreads through a myriad of decisions, henceforth the failure cascades and take control of entire organizations.
- Over-optimization: Agents could be optimizing for goals that are not desirable. They meet their targets but fail to accomplish the broader mission. They lose the habit of adapting to new situations and subsequently become increasingly less flexible.
- Skill gap: Just because you are capable of managing one agent, it doesn’t imply that you are capable of managing another. Different agents require fundamentally different approaches at the core, so the deployment of different types of agents in an organization will create vulnerabilities.
Moreover, it is estimated that by 2028, there will be more than 1.3 billion AI agents working simultaneously. The situation will be very risky if this scale is not accompanied by proper monitoring.
The Trust Problem
Traditionally safety-checked AI outputs: Were the answers correct? Ethical? Safe to publish?
The agentic web requires behavioural trust. Just checking outputs is no longer enough. One has to see how agents interact in the long run. Current safety models cannot be scaled up. The manual approval and isolated testing methods cannot produce the required level of trust for systems that are continuously learning and evolving.
What is necessary:
- Human intervention hierarchies with clearly defined roles
- Non-stop surveillance of the agent’s conduct
- Immediate understanding of the decision routes
- Unintentional safety provisions being integrated in the work processes
- Complete audit trails and alerts
What Comes Next
Gartner sees the change unfolding over different phases:
- At present: AI agents of a simple kind to individually manage tasks
- Shortly after: Collaborative agents interacting with humans and other agents, sharing knowledge and coordinating activities
- After that: AI agent ecosystems tackling complex problems, changing as needed, and being able to skilfully manage the total performance
Furthermore, collaborative agents will be the first to be seen in supply chains, coordinating demand forecasting, production planning, inventory management, and logistics. Agent ecosystems will be in large-scale challenges such as natural disasters, where there will be a need for handling the complexity that no single agent could manage. And if you’re curious about how these agents are already showing up in real products and tools, here’s a guide on some of the best AI agents available today, giving a glimpse of how fast this shift is accelerating.
