Why AI agents fail without the right context
The AI agent conversation has a blind spot.
Everyone is focused on which agent to deploy, which model to use, and which workflows to automate first. Almost nobody is asking the more important question: what information are these systems acting on before they decide?
An AI agent operating on incomplete or imprecise signals doesn’t underperform quietly. It makes confident, automated, expensive mistakes. And in an autonomous workflow, those mistakes scale before anyone catches them.
This white paper makes the technical and business case for why context is the variable that determines whether AI agents succeed or fail in B2B sales and marketing.
What’s inside:
The evolution of AI in sales and marketing:
From early machine learning through the rise of large language models to the autonomous agent era, and why each shift raised the stakes on data quality.
The Intentsify story:
How a deliberate bet on LLMs, made before the term entered everyday vocabulary, and a landmark acquisition in persona-level identity resolution positioned Intentsify as the context layer the agent era demands.
The cost of wrong context:
A Fortune 500 telecom backtest found that Intentsify identified three times as many close-won opportunities as the incumbent intent provider over the same historical period. Had an AI agent ingested the incumbent’s signals instead, the financial impact would have compounded in both directions, and over time, the system would have learned the wrong lessons.
The data layer:
What persona-level intent, buying stage inference, and identity resolution look like as inputs to an autonomous GTM system, and why the quality of those inputs determines the quality of every decision downstream.
About the author
Marco Lagi is Chief Technology Officer at Intentsify, with more than 15 years of expertise in machine learning and natural language processing. He founded Kemvi, an AI startup acquired by HubSpot, where he built the company’s machine learning modeling capabilities from the ground up. He has authored more than 40 academic papers, with research recognized by Forbes, The Guardian, Time Magazine, and Wired.
