Five Maturity Levels of Managing AI: A Guide for Managers

Artificial intelligence (AI) has seen significant advancements, drawing attention from various sectors. Despite widespread adoption, many firms struggle with managing AI effectively and reaping its full competitive benefits. This paper introduces a framework comprising five maturity levels of AI management, ranging from Isolated Ignorance (Level 0) to Integrated Intelligence (Level 5). These levels, comparable to those in autonomous driving, provide a structured approach to assessing and improving AI management in organizations. By understanding and progressing through these levels, firms can address managerial challenges and unlock unrealized opportunities in their AI initiatives.

Framework Overview:

• Level 0: Isolated Ignorance Companies at this level largely ignore AI and its potential.
• Level 1: Initial Intent Firms show initial interest in AI, starting to experiment with AI technologies.
• Level 2: Independent Initiative Companies have multiple AI activities with limited coordination, often focusing on automation for efficiency.
• Level 3: Interactive Implementation AI activities are aligned and coordinated across organizational units, integrating AI and human intelligence.
• Level 4: Interdependent Innovation Firms emphasize growth and innovation by combining AI with other innovations, ensuring strategic alignment.
• Level 5: Integrated Intelligence AI and human knowledge are closely integrated, creating a sustainable competitive advantage.

What can Managers do:

Level 1: Initial Intent

• Managers need to raise awareness about AI and its potential benefits among relevant personnel.
• Building a foundational understanding of AI through training and small pilot projects is essential.

Level 2: Independent Initiative

• Coordination of AI projects is critical to avoid redundancy and ensure that resources are effectively utilized.
• Establishing a central AI team or committee can help in aligning various AI activities.

Level 3: Interactive Implementation

• Effective execution of AI initiatives requires cross-functional collaboration and integration.
• Managers should focus on developing AI governance frameworks to streamline AI efforts across departments.

Level 4: Interdependent Innovation

• Emphasis should be placed on strategic alignment, integrating AI with broader business objectives.
• Encouraging innovation through partnerships, collaborations, and open innovation platforms can drive growth.

Level 5: Integrated Intelligence

• Achieving a sustainable competitive advantage involves deeply integrating AI into the core operations and decision-making processes.
• Continuous learning and adaptation are vital, leveraging both AI and human intelligence to drive ongoing improvement.

Future Perspectives:

• The potential for a future Level 6 ("Intuitive Ingenuity") exists, where AI systems have self-awareness and emotional intelligence.
• The evolution of AI will see firms moving through these maturity levels over the coming decades.

Today's research paper in discussion is Authored by: Ulrich Lichtenthaler and Published in: Journal of Innovation Management, Volume 8, Issue 1, 2020.