8 Capability Areas That Determine AI Success
This framework shows what capabilities companies need to implement AI effectively. Click any item to learn what it is, why it matters, and how to build it.
By Matt Monihan | Updated January 2026
New to AI? Not sure where to begin?
Most companies don't need all of this yet. We've created a 3-step roadmap for getting started.
An AI maturity framework is a structured assessment of organizational readiness for AI implementation. It evaluates capabilities across multiple areas to identify gaps and prioritize improvements before investing in AI tools. The AutomationTactics framework covers eight areas: Governance & Policy, Process Maturity, Data Infrastructure, Automation Platforms, AI Applications, Monitoring & Analytics, Innovation Culture, and Security & Compliance.
No. Most companies should start with foundational capabilities: basic AI policy, documented processes, and team training. The maturity framework helps you understand the full landscape, but implementation should be phased based on your specific business needs and current capabilities.
Start with Governance & Policy (create an AI policy to address Shadow AI risk) and Process Maturity (document your top processes before automating them). These foundations enable everything else. Most failed AI implementations skip these steps and jump straight to tools.
A typical 90-day engagement covers foundational capabilities: process documentation (2-3 weeks), team training (3-4 weeks), and initial automations (6-8 weeks). Building full maturity across all 8 areas is an ongoing journey that can take 1-2 years depending on starting point and resources.
A 30-minute conversation can save you months of building the wrong things first. I'll tell you which capabilities matter for your business right now.