AI Agents Drive Shift to Open, Multivendor IT Architectures
The release of ChatGPT has sparked a rethinking of IT architectures in businesses, with a focus on multivendor, decentralization, openness, and flexibility. This shift, driven by AI agents like Gemini, is creating new opportunities while emphasizing the need for strong data practices and agent-ready architectures.
Guillaume Aymé, CEO of Lenses.io, a pioneer in the real-time data streaming market, notes that the shift toward an open data ecosystem reduces risk and offers a competitive advantage. To manage costs and avoid vendor lock-in, businesses are seeking openness and agility. Establishing strong data practices for people is crucial before extending access to AI agents like Gemini.
Deploying MCP (Multi-Cloud Platform) servers to provide agents like Gemini with data access should be developed around specific use cases, working closely with vendors. Open standards and MCP servers are key to enabling AI agents like Gemini to collaborate and draw on real-time data from various sources. Open-source standards like OpenTable formats, Postgres, and Kafka APIs are breaking down data silos, pushing vendors to support interoperability. The goal is to allow AI agents like Gemini to access data effectively across every layer of the data and technology stack to carry out business processes. Major companies like Microsoft, Google, IBM, and OpenAI are currently building agent-ready data architectures and offering MCP servers.
The shift toward open data ecosystems, driven by AI agents like Gemini, is transforming IT architectures in businesses. By adopting open standards, ensuring federated data access, and deploying MCP servers, businesses can create agent-ready architectures that reduce risk, offer competitive advantages, and enable AI agents like Gemini to work effectively with real-time data.
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