In just a few years, artificial intelligence has evolved from a supporting tool to a driving force in digital transformation. But in 2025, we’re witnessing a new frontier: the rise of the agentic web, where AI will not only respond, but also act. Where assistants evolve into agents. And where the internet becomes less about clicks and searches, and more about delegation, autonomy, and intelligent collaboration.
At events such as Google I/O 2025, this shift was impossible to ignore. With announcements about WebXR, spatial computing and multi-agent collaboration protocols, it became clear that the next generation of user experience would be powered by agentic AI: systems capable of planning, reasoning and executing tasks independently across platforms and services.
The internet as we know it is changing. Let’s explore how.
What is the agentic web?
The agentic web refers to an emerging digital ecosystem powered by autonomous AI agents. Unlike traditional AI assistants which wait for commands, agentic systems proactively identify goals, make decisions, and execute tasks with minimal human input.
Imagine an AI agent that helps you book a trip and does more besides, such as:
- scanning your calendar for availability;
- comparing prices across platforms,
- booking the optimal itinerary based on your preferences.
It would also send you reminders, updates and documents without you having to lift a finger.
This is no longer just theory. Tools powered by OpenAI’s Assistant API, Microsoft’s AutoGen, and frameworks like LangGraph or CrewAI are already enabling these capabilities, laying the groundwork for a new kind of web interaction that is autonomous, goal-oriented, and cross-platform.
How Agentic AI actually works
At a technical level, Agentic AI is built on a smart combination of tools that allow it to think, act, and improve over time. It typically starts with a Large Language Model (LLM), like GPT-4 or similar, which handles reasoning, planning, and natural language tasks. But an agent needs more than just language: it needs memory, tools, and feedback.
That’s where vector databases come in. These databases store and retrieve relevant knowledge, documents, or previous interactions in a format the AI can understand, enabling the agent to maintain context and personalize its actions.
The agent also connects to external tools or APIs to perform real-world actions: sending emails, booking meetings, fetching data, or launching web tasks. Each time it acts, it evaluates the results and refines its plan through a feedback loop, improving performance based on success or failure.
Some agents are customized with fine-tuned models or plugins tailored to specific industries, like legal, healthcare, or HR. Others operate as multi-agent systems, collaborating with other agents to solve complex tasks, each with its own role, memory, and skills.
Agents in action: what they can actually do
So what does this look like in practice?
- Personal productivity: agentic systems can manage your inbox, schedule meetings, summarize documents, and prepare reports. You set the goal and the system takes care of the workflow.
- Enterprise use: in business environments, agents can automate customer support, financial analysis, legal research, and procurement processes, often operating 24/7 with minimal oversight.
- Web interactions: when combined with technologies such as WebXR, agentic interfaces can operate within browser-based 3D environments. This makes task execution more intuitive and immersive, whether the task involves onboarding a new employee, navigating a training simulation, or managing digital storefronts.
Unlike static software automations, agents can adapt and learn from context, collaborating with other agents to solve more complex problems.
Why it matters
This evolution isn’t just a technical upgrade: it’s a paradigm shift.
For users, the agentic web represents a new relationship with the internet. No longer a place where we actively search and sift, but one where we delegate goals and receive personalized outcomes.
For businesses, this opens massive potential:
- Reduced operational load
- Faster decision-making
- Improved customer experience
- New models of service delivery
Just like mobile transformed access, and the cloud transformed scale, Agentic AI is set to transform action itself.
Strategy, not hype
However, as with any transformative shift, the value lies in intentional implementation.
The most successful use cases, whether in finance, healthcare, legal services or consumer technology, stem from organizations that recognize the value of agentic AI. They align these systems with clear business goals, such as automating internal workflows, reducing human error, enhancing personalization and increasing speed to market.
Agents are most impactful when they:
- Operate within defined scopes
- Have access to relevant, real-time data
- Are monitored for accountability and trustworthiness
This isn’t about replacing humans. It’s about enhancing human potential.
What’s next?
The next months will likely bring:
- Broader integration of agentic APIs across consumer and enterprise software
- Improved agent-to-agent communication protocols
- Advances in contextual memory, allowing long-term personalized behavior
- The rise of Agent UX: a new design paradigm in which users guide outcomes rather than clicks.
As OpenAI, Google, Microsoft, and open-source communities push forward, they are laying the foundations for a new kind of internet: goal-driven, personalized, and intelligent.
We’re on the verge of something transformative. The agentic web isn’t about replacing human interaction: it’s about enhancing it. It’s about freeing people from repetitive digital tasks so they can focus on creativity, decision-making, and making an impact.
In this new era, websites, apps and platforms won’t just respond to users: they’ll collaborate with them.
Do you want to discover more about AI immersive experience? Let’s talk!
