The DRI Framework
Deploy, Reshape, Invent - BCG's proven methodology for AI transformation at scale
1. Deploy
Quick Wins with Off-the-Shelf Tools
Start your AI journey by deploying ready-made tools like ChatGPT Enterprise, Microsoft Copilot, and Adobe Firefly. This phase generates immediate value and builds organizational excitement.
10-15% productivity boost
Low risk, high visibility
Rapid implementation (weeks)
Build AI literacy across teams
60% of companies have active deploy plays
2. Reshape
Transform Critical Functions
Reimagine core business functions end-to-end with AI integration. This involves process redesign, workflow automation, and strategic upskilling of your workforce.
72% of AI value in core functions
End-to-end process optimization
Workforce transformation
Sustainable competitive advantage
68% of companies have reshape plays in motion
3. Invent
Create New Business Models
Develop innovative products, services, and experiences by connecting GenAI to your proprietary data and expertise. This phase creates new revenue streams and market differentiation.
New revenue opportunities
Competitive differentiation
Proprietary AI capabilities
Market leadership position
46% of AI-mature companies executing invent plays
The 10-20-70 Principle
Success in AI transformation is 70% about people and processes, not just technology
10%
Algorithms
AI models, machine learning algorithms, and technical capabilities
Model selection
Training data quality
Performance optimization
Technical architecture
20%
Technology & Data
Infrastructure, platforms, data pipelines, and integration
Cloud infrastructure
Data engineering
Integration platforms
Security & compliance
70%
People & Processes
Organizational change, workforce transformation, and process redesign
Change management
Skills development
Process redesign
Cultural transformation
Key Insight
Organizations that focus primarily on technology without addressing people and processes typically fail to scale AI effectively. The 70% emphasis on organizational change is what separates successful AI transformations from failed pilots.
Hybrid Intelligence Approach
McKinsey's framework for combining AI technology with human expertise
AI Capabilities
Leverage machine intelligence for scale, speed, and pattern recognition
Data processing at scale
Pattern recognition
Predictive analytics
Automation of repetitive tasks
24/7 availability
Human Expertise
Apply human judgment, creativity, and contextual understanding
Strategic thinking
Creative problem-solving
Ethical judgment
Contextual interpretation
Relationship building
Implementation Stages
A phased approach to minimize risk and maximize value
Stage 1
2-4 weeks
Assessment & Strategy
AI readiness assessment
Opportunity identification
Business case development
Stakeholder alignment
Stage 2
1-3 months
Pilot Projects
Select high-impact use cases
Deploy off-the-shelf tools
Measure initial results
Build internal capability
Stage 3
6-12 months
Scale & Transform
Expand successful pilots
Redesign core processes
Workforce upskilling
Governance establishment
Stage 4
12+ months
Innovation & Leadership
Develop custom AI solutions
Create new business models
Establish AI center of excellence
Drive industry innovation
Measuring Success
Key metrics to track your AI transformation progress
ROI
Return on AI investment
3-5X within 2 years
Productivity
Efficiency gains
10-30% improvement
Adoption
Employee engagement
80%+ active users
Governance
Risk management
100% compliance