What must be in place in tech stack and data before AI agents create real impact?
By Matilda Rydow
Categories: Tech Stack & Data, AI Agents, Measurement, Attribution & MMM
Agents are nothing without a stable foundation. That means tracking and instrumentation, product data, CRM structure, BI and reporting, consent and PII, and integration capability. Without this, agents optimize on the wrong signals and the organisation cannot judge whether productivity and quality actually improve. This is where many get stuck. They implement agents but lose focus on improving the foundation. Then agentification becomes a new layer of complexity rather than an enabler. A good rule of thumb: if the team cannot agree on which numbers are correct, or if data quality varies across functions, it is too early to scale agent work broadly.
What must be in place in tech stack and data before AI agents create real impact?
Agents are nothing without a stable foundation. That means tracking and instrumentation, product data, CRM structure, BI and reporting, consent and PII, and integration capability. Without this, agents optimize on the wrong signals and the organisation cannot judge whether productivity and quality actually improve.
This is where many get stuck. They implement agents but lose focus on improving the foundation. Then agentification becomes a new layer of complexity rather than an enabler.
A good rule of thumb: if the team cannot agree on which numbers are correct, or if data quality varies across functions, it is too early to scale agent work broadly.