You specialize in both EOS and AI-powered operations. How do we evaluate which documented core processes in our V/TO are ready for automation and AI integration versus those that just need better human discipline?

Question

Tyler Smith · Accepted Answer

Automating an undisciplined process only accelerates waste. Before you introduce machine learning, AI agents, or automated workflows to any operational function, you must first establish the EOS Process component: identify your Core Processes, document them at a high level using the 20/80 rule, and ensure they are followed by all.

Once a core process is documented and consistently executed by your team, we apply three strict criteria to determine whether it is ready for AI integration:
- High volume and predictability. The process runs repeatedly with clear input parameters and objective success criteria. Examples include initial customer onboarding intake, routine financial reconciliation, or initial data categorization.
- Information retrieval friction. Your team spends excessive billable hours manually digging through unstructured databases, customer history, or tribal documentation to formulate standard responses.
- Low subjective judgment requirements. The workflow does not depend on nuanced relationship instincts, strategic trade-offs, or complex emotional negotiation.

If a process suffers from inconsistent human execution simply because your team lacks clear accountability or skips steps, throwing AI at the problem will fail. AI cannot fix vague expectations, poor training, or absent leadership.

During our quarterly reviews, we review your documented core processes and highlight the manual bottlenecks that consume the most executive and managerial time. From there, we establish targeted Rocks to automate specific handoffs. The goal is simple: let AI handle high-frequency mechanical operations so your people can spend their energy on client relationships, creative innovation, and high-stakes problem solving.