Artificial intelligence (AI) is radically redefining how we interact with the digital world. It’s not just about improving existing tools; it’s an emerging phenomenon consolidating the functions of various platforms into a single interface: Platform Shifting. This monumental change is already underway and, experts predict, will explode in the coming months.
This article will explore how AI is consolidating the functions of various platforms into a single conversational interface and what this means for developers, IT decision-makers, and the future of digital business.
What is Platform Shifting and its crucial role
We’re accustomed to a fragmented digital landscape: e-commerce for purchases, social media for interactions, search engines for information. Platform Shifting describes the phenomenon where all these functions are migrating into a limited number of major artificial intelligence players.
Let’s take conversational AI assistants as a prime example. Initially, we used them for simple queries. But the vision of Platform Shifting goes further: imagine being able to ask an AI assistant to make a bank transfer, buy a pair of glasses after receiving personalized advice, or browse a product catalog without navigating a dedicated e-commerce website. This will be a reality for all major AI assistants like Google Gemini, Claude, Anthropic, and various Copilot systems.
The advantage of this shift is twofold: simplification and personalization. It will no longer be necessary to switch between apps; a single, conversation-based interface will allow for multiple actions. This interaction model is much closer to human dialogue, reducing the mediation of traditional graphical interfaces and making technology more intuitive and accessible.
MCP and A2A: The Protocols Enabling the Conversational Revolution
Behind this vision are technical protocols and standards. Two acronyms are particularly relevant: MCP and A2A.
The Model Context Protocol (MCP) is an emerging standard that facilitates communication between AI agents and third-party enterprise systems. If a company currently has an e-commerce website, in the near future it will need to equip itself with an MCP server. This system will be able to directly communicate with AI assistants, providing them with all the necessary information about products and services.
This means that companies will need to expose their data and functionalities in a format that AI agents can understand and utilize.
While MCP handles the dialogue between AI and enterprise systems, Agent-to-Agent (A2A) communication concerns the ability of AI agents to communicate and collaborate with each other to perform more complex tasks. Imagine an ecosystem where your AI assistant not only interacts with your bank for a transfer (via MCP) but also with another AI agent specialized in travel to book a flight.
This interconnectedness means that tasks that today require navigating various apps and websites will tomorrow be managed with a single voice request. This scenario, while requiring careful consideration of security and privacy, promises an unprecedented level of efficiency and convenience.
Business Impact and the Future of Digital
Platform Shifting is not just a convenience for the end consumer; it’s a profound redefinition of business strategies and the digital landscape. If users migrate to AI interfaces for their needs, companies will have to follow them.
- Evolving User Interfaces: The role of traditional graphical interfaces will change. It will be crucial to make systems “AI-friendly,” exposing data and functionalities so that AI agents can easily access and interpret them.
- New Interaction Channels: Companies will need to rethink how they interact with their audience. Instead of relying solely on websites or social media, they will need to consider how to make their products or services appear within the conversational recommendations of AI assistants, creating a new paradigm of visibility.
- Transforming Skillsets: Developers, experts, and IT decision-makers will need to acquire new skills in integrating AI systems, managing data for conversational agents, and understanding the dynamics of an AI-driven economy.
Conclusions
Platform Shifting represents the next phase in the history of technological disintermediation. We’ve moved from machine languages to visual interfaces, and now we’re entering the era of conversational interfaces. AI is creating a bridge between humans and machines that increasingly resembles natural conversation.
The opportunities are immense: greater efficiency for users, new frontiers for businesses, and the ability to automate complex processes. The challenges, however, are not to be underestimated: the need for standardization, data security, user privacy, and the need for rapid adaptation by businesses.
