The Four Phases of AI Integration

Phase 1: Discovery

Start experimenting and exploring the potential.

• Try out tools like ChatGPT or Copilot in low-risk areas
• Learn prompt engineering and basic capabilities
• Educate your team on how to use AI tools securely and effectively
• Identify early wins and clarify your AI direction

Phase 2: Integration

Connect AI into your systems and workflows.

• Begin embedding AI into your daily tools (email, CRM, dashboards)
• Use agents and natural language commands to streamline work
• Pull in external systems like Optic for deeper application
• Establish initial governance and process controls to manage usage, access, and data flows

Phase 3: Amplification

Expand AI’s impact across teams and data.

• Centralize and unify business data to reduce errors and redundancy
• Enable predictive analytics and AI-triggered automations
• Formalize governance frameworks and AI usage policies across departments
• Build processes for review, auditing, and responsible scaling

Phase 4: Transformation

AI becomes a core part of how your business operates.

• End-to-end workflows include autonomous analysis and recommendations
• Your data strategy, team structure, and tools evolve in sync
• Introduce new AI “team members” and bots that operate alongside humans
• AI augments decision-making, operations, and strategic growth