What Enterprises Get Wrong About AI Adoption - Crawl, Walk, Run, Fly
AI Summary
Summary of AI Adoption and Deployment Strategies
Core Thesis
- Centralized AI management (AI Center of Excellence) is not effective in early stages.
- Empower product teams to explore AI organically and decentralize AI deployment.
Crawl, Walk, Run, Fly Model
- Crawl Phase:
- Adopt an exploratory mindset without expecting immediate value.
- Encourage curiosity and familiarity with AI without pressure.
- Transition to the next phase when exploration leads to boredom.
- Walk Phase:
- Begin to seek value from AI by finding specific tools or uses that improve efficiency.
- Focus on measurable gains in terms of better, faster, cheaper, or safer outcomes.
- Example: Using AI for book cover art instead of human artists, which proved to be more effective and cost-efficient.
- Run Phase:
- Operationalize AI by expanding the use of tools that have proven valuable.
- Systematize AI integration and measure its impact on processes and business.
- Example: Automating IT backlogs or using AI for marketing materials and A/B testing.
- Fly Phase:
- Establish a Center of Excellence with in-house AI experts who understand both the business and AI.
- Centralize best practices and authority on AI once maturity and expertise are developed internally.
Conclusion
- The goal is to accelerate AI adoption in industry to enhance economic and scientific progress.