This post was originally published on LinkedIn.

Trust-the-model AI approach

• AI analyzes all your data and spits out prioritized accounts
• The reasoning is complex (a bit hard to audit)
• Could be seen as a black box
• Hard to report on why it worked
• But maybe the model is so good we don't need to know

vs.

AI sourced Signal-based plays

• Specific triggers (funding, hiring, custom signals, etc.)
• You know exactly why you're reaching out and how to reach out
• AI is setup to orchestrate (find signals, find contacts, write emails)
• Can report on signal by signal performance
• But is this Controlfreak-mode?

There is probably space for them both, but here is what we are focused on to validate this for clients:

>> Efficacy (and ability to validate with data): we want to be able to see if either of these options converts higher into pipeline and revenue than the other. Or vs. non-AI related pipeline.

>> Efficiency: what is actually saving the team time?

>> Controlfreak-mode vs. Trust me-mode: with AI at 2026 quality can we just let it loose? Or will it just pick Accounts at random and then justify the choice after the fact?

I don't think there's an easy answer here, which is why making sure you have the reporting infrastructure in place is so important to validate the option for yourself