AI Agents Need Context to Sell

The marketing technology landscape is undergoing a seismic shift. As reported by Snowflake, the distinct categories of martech are becoming irrelevant, with the only benchmark for success being whether the delivered consumer experience is timely and valuable.

This convergence is accelerating thanks to AI agents, which can optimize for relevance far beyond what static rules could achieve. However, these agents have a critical dependency: context. An AI agent without context is merely automation; with rich, governed, real-time context, it approaches genuine intelligence.

"Marketers have been told for years that personalization was solved, but the reality has been static segments, brittle workflows and missed customer moments," notes Matt Walker, Co-Founder and CTO of Simon AI. "Simon has changed that by bringing reasoning, context and execution directly into the Snowflake data layer for marketing to use."

Two Sides of the Context Coin

This essential context originates from two distinct, non-substitutable sources. The first is brand-specific context, proprietary insights like purchase history, real-time behavior, service transcripts, product catalogs, brand voice, and creative assets. Brands own this data; marketing solutions merely leverage it.

The second source is domain-specific context. This comprises the accumulated knowledge and specialized approaches developed by marketing solutions over years of focus. An engagement platform might possess proprietary expertise in send-time optimization, while an attribution solution offers advanced measurement methodologies. This is domain expertise encoded into software, not derived from any single brand's data.

When these two context sources converge on a governed foundation, intelligence amplifies. Proprietary optimization techniques become more potent when paired with a brand's unique customer data.

The underutilization of this combined context stems from significant structural constraints. Brand context is often fragmented and inconsistently defined across disparate systems. Domain context, being proprietary intellectual property, requires robust protection that many existing architectures cannot provide.

These gaps prevent AI agents from performing optimally, leading them to act on incomplete or incorrect definitions with misplaced confidence. The solution isn't better AI models but a flexible data and AI foundation. This foundation must unify context from all systems, enrich it with consistent business definitions, and allow both brand and solution AI models to access trusted logic without data duplication.

An open, neutral foundation accelerates development, keeps data in place, and enforces IP isolation through policy boundaries without inter-account data movement. "Our AI models run on the data where it lives, in Snowflake," states Eric Miao, Chief Strategy Officer at Attentive. "The models that select the right channel, message and moment for every subscriber can access a brand's first-party data in real time, without requiring exports or copies. And the performance difference is immediate."

Snowflake's new Horizon Context is a native, governed context layer designed to address this need. It collects metadata, enriches it with business definitions, and activates it for AI agents, enforcing governance at the semantic level.

"Our thesis has always been that data should never leave your data platform," says Kashish Gupta, Co-CEO of Hightouch. "Marketers need intelligent context, but they also need trust and control. Snowflake gives them a governed, AI-ready platform for data, semantics and IP protection. Hightouch's AI extends that intelligence and composes agentic marketing experiences on top."

The Snowflake Partner Network, with over 10,000 organizations, includes CDPs, agentic marketing platforms, and identity solutions built natively on Snowflake. This ecosystem reflects a long-term investment in the infrastructure layer.

"Thanks to Snowflake, we've reduced complexity and can focus more on new products and tackling the problems that our customers want us to solve," shares John Adams, VP of Architecture at VideoAmp.

Ultimately, the marketing technology ecosystem strives for one outcome: delivering consumer experiences worth attention. Success hinges on harmonizing broad domain expertise with deep consumer context.

"We're focused on helping businesses make better decisions with access to their data in natural language," says Ben Dutter, Chief Strategy Officer at Power Digital.

Snowflake aims to ensure this context is governed, trusted, and accessible within an open ecosystem where customers and partners can compose optimal solutions.