9MARCH - APRIL 2026knowledge base, allowing AI to query specific information beyond its original training. This prevents hallucinations and ensures that agents work with data that is updated, reliable and context-rich.With this foundation, it becomes possible to move from a simple thematic assistant, such as one specialized in finance or customers, to collaborative agent architecture. Each agent is enriched with the context of the data products from its domain and can interact with other agents to execute more complex tasks: a finance agent coordinating with a risk agent to analyze operating margins or an operations agent collaborating with a customer agent to access validated transactional data.In this way, data products stop being just analytical inputs and become the catalyst for ecosystems of agents that operate autonomously, working together with context and precision to optimize processes, accelerate decision-making and unlock new value streams for the organization.The Future in This New ContextThis approach redefines the role of CIOs and data leaders. It is no longer only about managing infrastructure or producing reports but about designing ecosystems of domain-based data products that feed intelligent agents and accelerate business impact.Organizations that successfully make this transition will be better prepared to optimize operations through specialized agents with deep business context, accelerate innovation by reusing data products across multiple use cases and reduce structural costs thanks to more efficient and scalable architectures. In this model, data products are the foundation and agentic AI is the engine that transforms them into a competitive advantage. Each agent, enriched by the context of domain data products, can collaborate with others to solve more complex tasks. The result is an orchestration of autonomous agents working together guided by high-quality data to optimize processes, improve decisions and accelerate value creation for the company. Data products transform the natural entropy of information into organized, governed assets prepared to be consumed by machine learning and AI processes.
< Page 8 | Page 10 >