The Human-AI Collaboration Maturity Model
A systems engineering framework designed to help Small and Medium-sized Enterprises (SMEs) adopt AI by prioritizing human-AI partnerships. The HAIC-MM provides an actionable roadmap for organizations to enhance productivity, innovation, and growth by blending technical rigor with practical business insights and responsible AI deployment.
Theoretical Foundation
The HAIC-MM integrates three theoretical domains to address the complexity of human-AI collaboration in SMEs:
Systems Engineering
- Systems Thinking: Views AI integration as a socio-technical system with emergent properties affecting both technical and human elements.
- Lifecycle Management: Guides iterative systems development from initial assessment through continuous improvement.
- Requirements Engineering: Ensures AI capabilities align with SME constraints and needs.
Human-Computer Interaction
- User Understanding: Ensures AI systems operate in ways that users can comprehend and predict, promoting confident interaction.
- Ease of Use: Focuses on creating simple, intuitive interfaces that reduce complexity and make AI tools accessible to all employees.
- Trust Building: Develops user confidence through clear communication of AI capabilities and limitations.
Organizational Behavior
- Change Readiness: Preparing leadership and employees for technological transformation to reduce resistance and increase adaptability.
- Knowledge Integration: Combining human expertise with AI capabilities through structured learning and communication for effective organizational adaptation.
- Adaptive Culture: Supporting continuous learning and adaptability to navigate the rapidly evolving demands of human-AI collaboration.
Model Structure
Core Components
7 Dimensions
Broad categories driving AI integration maturity
32 Capabilities
Focused areas of development within each dimension
Focus Areas (5 per Capability)
Focused areas of action for each capability.
Advancement Practices (4 per Focus Area)
Strategies to advance capabilities to higher maturity levels.
Components (9 per Advancement Practice)
Detailed, customized guidance for implementation.
Maturity Levels
The HAIC-MM defines five distinct maturity levels, each with specific implementation timelines and characteristics, guiding organizations from initial AI experimentation to full human-AI synergy.
The Seven Dimensions
AI-Enhanced Leadership and Strategy
Leaders who understand and champion AI initiatives, integrating them into business strategy.
Adaptive AI Culture and Empowerment
Organizations that prepare their workforce for AI collaboration and foster adaptability.
Human-Centric AI Integration and Experience
AI systems designed with human needs and experiences at the center of development.
Harmonizing AI and Human Processes
Workflows that smoothly integrate AI and human efforts for optimal productivity.
Human-Centered AI Customer Engagement
Enhanced customer experiences through combined human empathy and AI insights.
AI Ethics and Human Oversight
Ethical AI governance and human oversight ensuring responsible technology use.
Inclusive AI Governance and Learning
Diverse, inclusive AI development and continuous learning practices.
Research-Backed Development
The HAIC-MM was developed by Flavio Ortolano under the advisement of Dr. Erika Gallegos from CSU Systems Engineering, using a structured, iterative framework combining Becker et al.'s maturity model development with Hevner et al.'s design science research principles. This rigorous approach ensures the model's practical relevance and theoretical soundness.
The development process included comprehensive analysis of 30 existing frameworks across AI maturity, digital transformation, and human-machine teaming domains. The model was validated through quantitative surveys (N=100), numerous qualitative focus groups (N=10 across five initial sessions, plus additional groups), and real-world pilot tests with several organizations, ensuring its applicability to real-world SME environments.
Comprehensive research methodology combining analysis of 30 existing frameworks with validation through surveys, focus groups, and pilot testing
Key Benefits
Enhanced Productivity
Optimize workflows by blending AI's analytical power with human intuition. Organizations employing effective human-AI collaboration can achieve up to 40% productivity gains.
Improved Decision-Making
Leverage AI for data-driven insights while retaining human judgment for strategic decisions, creating more balanced and effective outcomes.
Increased Innovation
Free employees for higher-value, creative, and strategic initiatives by automating repetitive tasks through responsible AI implementation.
Sustainable Integration
Empower employees and foster long-term competitive advantages through a structured approach to human-AI collaboration adoption.
Ethical AI Practices
Guide SMEs towards AI adoption that is ethically sound, responsible, and aligned with organizational values and regulatory requirements.
Adaptive Culture
Build organizational agility and resilience to technological changes through a culture that embraces continuous learning and adaptation.
Trust & Transparency
Build confidence in AI through clear communication, reliability metrics, and systems designed for explainability and user understanding.
Structured Growth
Provide a clear roadmap for measurable progress in AI adoption with defined maturity levels and specific capabilities for improvement.
Implementation Timeline
The HAIC-MM provides a realistic timeline for SMEs to progress through maturity levels, acknowledging that AI adoption is a journey requiring incremental advancement:
Level 1: AI Exploration
3-6 months - Initial AI awareness, pilot projects, and basic applications
Level 2: AI-Enabled
6-12 months - Structured AI implementation with targeted use cases
Level 3: AI-Embedded
12-18 months - Cross-functional AI integration with mature processes
Level 4: AI-Aligned
Strategic alignment with business goals and advanced collaboration models
Level 5: Symbiotic Partnership
Full human-AI synergy with adaptive systems and optimal collaboration
Implementation Considerations
- Resource-Aware: Designed for SMEs with limited resources
- Incremental Approach: Progress at your organization's pace
- Balanced Focus: Equal emphasis on technical and human factors
- Practical Guidance: Actionable recommendations at each stage
- Ethical Consideration: Built-in governance and oversight