From Individual Research to Organizational Impact

Agentic AI refers to AI systems that plan and execute multi-step tasks on their own, rather than responding to a single prompt. In competitive and market intelligence, an agent can monitor sources, flag relevant developments, trigger further research, and deliver a packaged output as part of a configured workflow without someone manually starting each step.

Valona connects to Microsoft Copilot via MCP (Model Context Protocol), making structured competitive intelligence available directly inside Copilot. Rather than asking Copilot to search the web for competitive analysis each time, users can access continuously updated intelligence that has already been built, verified, and curated on the Valona platform. Custom AI analysis runs automatically on Valona’s source base and updates regularly. Copilot becomes the delivery point, not the research engine — and because the analysis is already built, there is no need to recompute or revalidate it each time someone asks a question.

AI can automate the work that benefits from scale and consistency: continuous monitoring, searching large source sets, structuring incoming signals, drafting first-pass summaries, and distributing outputs on a set cadence.

What it cannot do is judge what a signal means for your specific strategy, decide what matters most for which decision maker, validate outputs before they reach an executive, or build the stakeholder relationships that determine whether intelligence actually gets used. Those remain human responsibilities — and they are increasingly where the strategic value of a CMI function concentrates.

An intelligence agenda is a defined set of questions, topics, and signals an organization monitors on a continuous basis — which competitors to track, which markets, which regulatory areas, which technologies. As AI makes it easier to generate analysis on demand, the intelligence agenda becomes more important rather than less. It determines what gets monitored continuously, what structured analyses run automatically, and what intelligence assets get built and maintained over time. Without a defined agenda, AI tools tend to generate reactive, one-off research rather than the shared organizational intelligence that informs decisions.

No. MCP (Model Context Protocol) is a connectivity standard that lets AI systems access external data sources in a standardized way — for example, inside Microsoft Copilot, Claude, or ChatGPT. It determines how data moves, not whether that data is accurate, verified, or safe to use.