This framework is developed by a team of former McKinsey and Big 4 consultants. The presentation follows the headline-body-bumper slide format used by global consulting firms.
This product (Responsible AI [RAI] Maturity Model: Team Approach) is a 31-slide PPT PowerPoint presentation slide deck (PPTX), which you can download immediately upon purchase.
Responsible AI (RAI) addresses the challenge of aligning AI innovation with ethical principles, organizational trust, and long-term resilience. It reduces risks by embedding fairness, accountability, and transparency into AI systems, while ensuring that AI-driven growth remains sustainable and trustworthy.
In practice, Responsible AI depends not only on leadership vision or team priorities, but on how practices are executed across the AI lifecycle. Embedding responsibility into governance, risk management, development processes, and oversight ensures that responsibility is repeatable, auditable, and scalable.
The Responsible AI Maturity Model guides organizations in advancing across 3 dimensions of maturity:
1. Organizational Foundations
2. Team Approach
3. RAI Practice
Within each dimension, there are critical enablers, which evolve over 5 stages of maturity—from Latent, Emerging, Developing, Realizing, and ultimately, Leading.
The RAI Maturity Model ensures Responsible AI is not just a leadership goal, but a lived practice within every team. This PPT presentation focuses on the second dimension, Team Approach, which is defined by 10 critical enablers:
1. Teams Valuing RAI
2. Timing of RAI
3. Motivation for RAI Products
4. Sociotechnical Approach
5. Common Language
6. Collaboration within Teams
7. Non-UX Disciplines' Perception of UX
8. UX Practitioners' AI Readiness
9. RAI Specialists Working with Product Teams
10. Teams Working with RAI Specialists
Each of these enablers is discussed in depth, including its progress across the 5 stages of maturity.
This deck on the RAI Maturity Model also includes slide templates for you to use in your own business presentations.
This PPT slide presents a framework for understanding why teams pursue AI development based on their perception of AI as either a burden or a value driver. It categorizes AI maturity into 5 levels—Latent, Emerging, Developing, Realizing, and Leading—each associated with different team motivations and behaviors. The focus is on how motivation shifts from technical or competitive reasons at early stages to strategic and responsible AI practices at advanced stages.
The left side highlights the importance of motivation in shaping AI projects. At the Latent stage, teams pursue AI mainly for novelty or efficiency, often without considering broader impacts. As teams progress to Emerging and Developing levels, they recognize regulatory risks and start aligning AI initiatives with market opportunities,, but still face internal challenges. At the higher levels—Realizing and Leading—teams are more consistent in linking AI to trust, safety, and long-term resilience, emphasizing responsible AI principles. These stages reflect a transition from external compliance to internalized responsibility, driven by a desire for sustainable business success.
The diagram underscores that responsible AI is not just a compliance issue, but a strategic imperative. Teams at the top of the maturity scale integrate ethical considerations into their core value propositions, project trustworthiness, accountability, and impact. The slide suggests that the motivation behind AI efforts influences the approach and outcomes, with responsible AI practices becoming central as teams mature. For executives, understanding this progression helps in designing strategies that accelerate responsible AI adoption, aligning team incentives with long-term value creation rather than short-term gains. This model offers a clear view of how AI maturity correlates with responsible behavior and strategic focus across teams.
This PPT slide discusses how empowering UX practitioners with AI literacy can shift their role from reactive support to a proactive force for Responsible AI. It emphasizes a team approach, focusing on increasing AI readiness among UX teams. The content is structured around a maturity model with 5 levels, from Latent to Leading, illustrating the progression of AI understanding and integration within UX practices. Each level describes the current state of UX practitioners' awareness and involvement with AI, highlighting the need for self-learning, structured programs, and active collaboration with engineers and data scientists.
The first 2 levels, Latent and Emerging, depict a stage where UX practitioners have limited or informal awareness of AI concepts. They are disconnected from AI decision-making processes, which hampers their ability to contribute meaningfully to Responsible AI initiatives. As teams move into the Developing and Realizing stages, organizations introduce formal learning programs and start influencing AI design and evaluation discussions. This marks a shift toward more active engagement and shared responsibility for AI outcomes.
At the highest level, Leading, UX and AI disciplines operate seamlessly, with practitioners defining standards, metrics, and best practices for ethical design at scale. The slide underscores that as UX teams deepen their AI literacy, design becomes more responsible and aligned with ethical principles. The overall message is that AI literacy is a critical enabler for UX teams to drive Responsible AI, transforming their role from support to strategic partners in AI governance. The slide positions this evolution as essential for organizations committed to ethical AI deployment and responsible innovation.
This framework is developed by a team of former McKinsey and Big 4 consultants. The presentation follows the headline-body-bumper slide format used by global consulting firms.
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