AI Transformation Guide (Overview)

Strategy

• Prioritize AI by business outcomes, not features
• Pick one clear, measurable pain to solve first
• Define KPIs with baselines before implementation

Use-cases

• Automation: workflows, content, support, back-office
• Content: social, video, landing pages with dynamic personalization
• Analytics: dashboards, alerts, anomaly detection

ROI

• Measure impact with clear baselines and control groups
• Track cost savings, cycle-time reductions, and revenue lift
• Report monthly, iterate quarterly

Implementation

• Phases: Discovery → Pilot → Rollout → Optimize
• Risks: data quality, adoption, governance
• Governance: access control, audit, change management

Getting Started

1. Identify one process with measurable pain
2. Prototype quickly, validate with real users
3. Instrument metrics, iterate based on data
4. Scale with training, SOPs, and support