Most companies struggle with AI adoption for one reason: they start with tools instead of workflows. A better path is to identify where teams repeat decisions, create repetitive documents, or spend time searching for answers.
Step 1: Pick Two Practical Use Cases
Start in departments with measurable output such as operations, customer support, or sales. Choose one low-risk and one medium-impact use case.
Step 2: Define Guardrails
Create simple rules for approved tools, data usage, output review, and documentation. This prevents ad-hoc use and reduces risk quickly.
Step 3: Train by Role
Executives need strategic understanding. Managers need workflow design. Team members need prompt and review practices tied to their actual tasks.
Step 4: Measure and Scale
Track time saved, quality consistency, and throughput. Use results to prioritize additional use cases and expand with confidence.
Need help putting this into practice? Book an AI strategy call.