At CCL, we view leadership as a social process that enables individuals to work together to achieve results they could never achieve working alone. We believe that leadership happens when a group of people are producing shared Direction, Alignment, and Commitment (DAC):
- Direction is agreement within your organization on overall goals
- Alignment means coordinated work in your organization
- Commitment is a feeling of mutual responsibility in your organization
Together, these 3 elements are the outcomes of leadership, and they’re essential to tackling any challenge — including the one of integrating AI (artificial intelligence) into organizational workflows and culture.
Strengthening DAC isn’t optional — it’s an imperative for individuals, teams, and organizations to be able to thrive amid complexity, uncertainty, and change.
And our research suggests a strong correlation between high levels of DAC in an organization and high levels of AI maturity or adoption.
The 4 Stages of AI Maturity
To better understand the potential connections between AI maturity and leadership, we turned to MIT’s CISR Enterprise AI Maturity model, which depicts 4 stages of organizational AI maturity:
Stage 1: Discovering (Experiment & Prepare)
At this stage, organizations are curious about AI and have started to reflect on the human implications on AI. Organizations in this stage focus on educating the workforce on AI, establishing acceptable use policies, improving data accessibility, ensuring data-driven decision-making, and identifying where human input is necessary in processes.
Stage 2: Adopting (Build Pilots & Capability)
At this stage, organizations recognize AI’s relevance to their strategy and are starting to experiment and integrate. This includes simplifying and automating processes, creating use cases, sharing data via APIs, leveraging a coaching and communicative management style, and using both traditional and generative AI models to enhance work.
Stage 3: Transforming (Develop AI Ways of Working)
At this stage, organizations are fully aware of how AI impacts their work and are building new workflows and process for effective AI integration. This involves expanding process automation efforts, adopting a test-and-learn approach, designing for reuse, incorporating pre-trained models and exploring proprietary AI models, and investigating the use of autonomous agents.
Stage 4: Differentiating (Become AI Future-Ready)
At this stage, organizations are recognized as leading the way in AI transformation and are imagining and prototyping new methods of using AI. This involves embedding AI into decision-making and processes; developing and offering AI-augmented business services; and integrating traditional, generative, agentic, and robotic AI.
AI Maturity & Leadership: Our Research Findings
For our research, we created a survey based on MIT’s AI Maturity model to create a survey that measures AI adoption /AI maturity and leadership outcomes (levels of DAC) within an organization. We hoped to learn:
- What do organizations seek to gain by using / integrating AI? (This gets at shared Direction.)
- How will organizations and teams work together to effectively leverage AI? (This suggests group Alignment.)
- And how will organizations foster the trust and psychological safety required to achieve the buy-in to integrate AI? (This signals shared Commitment.)
After surveying 406 respondents based in APAC, EMEA, and the Americas, we found that DAC was a strong and significant predictor of higher levels of AI maturity. In other words, it’s fair to suggest that organizations need high levels of shared leadership to progress along their AI maturity journey, from Stage 1 to Stage 4.
Recommendations for Building Stronger AI Maturity With DAC
While the research doesn’t show causation (we can’t say for certain that increasing your organization’s DAC will automatically make AI integration easier), we can say that without high levels of shared Direction, Alignment, and Commitment at your organization, your chances of successfully moving up the stages of AI maturity are much lower.
So, how can leaders help their organizations foster strong DAC, particularly as it relates to improving their organization’s AI maturity?
- To increase shared Direction: Clearly communicate how AI will empower the business strategy through value creation, innovation, and impact across the organization. Seek out ways to help teams leverage both AI and soft skills to help them thrive.
- To facilitate more Alignment: Ensure leaders, teams, and systems coordinate in how to leverage AI, creating shared priorities and eliminating silos. To do this, explore what method of governance would work best for your organization. For instance, you could explore a shared decision-making model where overall AI usage across your organization is governed by a cross-functional team. Or, you could have shared policies but a decentralized AI governance structure, where individual functions oversee their own AI usage but align to shared organizational policies.
- To support greater Commitment: Foster psychological safety, continuous learning, and a growth mindset to empower your organization to embrace AI-driven change. Consider how AI and culture impact each other. By helping your organization embrace a culture that prioritizes continuous learning, you can help shift your organization to one that can best embrace and leverage what AI can enable.
Embracing Leadership for Greater AI Maturity
Leveraging AI within organizations requires more than just technological adoption; it demands robust leadership, characterized by our Direction – Alignment – Commitment (DAC)™ framework. Our research underscores the critical role DAC plays in progressing through the stages of AI maturity, revealing that high levels of DAC are strongly correlated with advanced AI integration.
Furthermore, MIT found that financial performance generally improves as an organization moves through the 4 stages of AI maturity as well, which further emphasizes the value of strong shared Direction, Alignment, and Commitment in navigating AI transformation.
By clearly communicating AI’s value, ensuring coordinated efforts across teams, and fostering a culture of psychological safety and continuous learning, your organization can not only enhance DAC levels and strengthen the outcomes of leadership, but increase in AI maturity — and thrive in an era of complexity and uncertainty.
Ready to Take the Next Step?
Ready to help leaders at your organization understand how to become more effective in setting direction, building commitment, and creating alignment to support greater AI maturity? Partner with us to craft a customized learning journey using our research-based modules. Available leadership topics include Boundary Spanning, Communication, Conflict Resolution, the DAC Framework for Effective Leadership, Emotional Intelligence, Listening to Understand, Psychological Safety, and more.
