How do you drive meaningful AI transformation across 150 software engineers without mandates or force? Peter Gostev, Head of AI at Moonpig, reveals the technical strategies and organizational approaches behind scaling AI adoption from 130 to 400+ users while navigating the gap between industry hype and implementation reality.
From managing complex integration challenges where building AI-powered features requires 80-90% traditional software engineering (integrations, scaffolding, deployment, UI) to implementing three-pillar strategies (tool adoption, automation workflows, experimental features), Peter shares hard-earned insights on building AI capabilities through process re-engineering rather than simple automation.
Technical insights for CTOs and engineering leaders:
- 🏗️ Portfolio approach: balancing quick wins with experimental high-impact projects
- ⚡ Prototype-first methodology for validating AI solutions before full development
- 🤖 Reality gap between agentic AI hype and production deployment complexity
- 👥 Organic adoption strategies that scale without top-down mandates
- 🔧 Custom GPT frameworks for non-technical subject matter experts
- 📊 Why most AI work is integration, scaffolding, and deployment—not just AI
- 🔄 Process re-engineering with AI: changing workflows rather than automating existing inefficiencies