Bad data used to break dashboards.
Now it can trigger bad decisions.
That is what worries me as Fractional Head Of Marketing Analytics about AI agents.
A messy dashboard is annoying. Someone opens it, spots something weird, asks a question, checks the source.
But an AI agent does not just show you a number. It can act on it.
Send the wrong email.
Score the wrong lead.
Summarize the wrong deal.
Recommend the wrong budget move.
Explain a revenue drop using broken tracking.
That is a different level of risk.
AI can make it easier to query data.
It can help with joins.
It can find patterns faster than a person.
But if your events are broken, your CRM is messy, or your teams use different definitions for the same metric, AI will not magically fix that.
It will just inherit the mess. MRR is a simple example.
Finance may define it one way.
Sales may define it another way.
Customer Success may need a different version because they care about churn and expansion.
None of them are necessarily wrong.
But before an agent uses that number, someone has to decide which definition fits the decision.
That is the work many teams want to skip.
Clean events.
Clear metric definitions.
Consistent labels.
One source of truth for important decisions.
Not very sexy.
But probably the difference between AI helping your business and AI scaling your analytics mess. Because bad data used to break dashboards. Now it can trigger bad decisions.
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