How do you avoid marketing AI initiatives becoming too fragmented?
By Matilda Rydow
Categories: AI Agents, Organisation & Operating Model
Fragmentation happens when each initiative has its own data, tools, KPIs, and no shared follow‑up. It looks like innovation, but it does not scale. Three minimum requirements make a big difference: - Agent inventory. Which agents exist, who owns them, and which systems do they touch? - Process map. Where does the agent sit in the flow, what is human work versus agent work, and where does review happen? - Measurement. What does “better” mean, time, quality, or business effect, and how is it tracked? This matters especially when AI employee systems are bought per function from different providers without connection to each other or the rest of the team. Then AI becomes a new silo layer.
How do you avoid marketing AI initiatives becoming too fragmented?
Fragmentation happens when each initiative has its own data, tools, KPIs, and no shared follow‑up. It looks like innovation, but it does not scale.
Three minimum requirements make a big difference:
- Agent inventory. Which agents exist, who owns them, and which systems do they touch?
- Process map. Where does the agent sit in the flow, what is human work versus agent work, and where does review happen?
- Measurement. What does “better” mean, time, quality, or business effect, and how is it tracked?
This matters especially when AI employee systems are bought per function from different providers without connection to each other or the rest of the team. Then AI becomes a new silo layer.