GenAI Operating Model Design (PowerPoint PPTX Slide Deck)

TARGET OPERATING MODEL PPT DESCRIPTION

This product (GenAI Operating Model Design) is a 29-slide PPT PowerPoint presentation slide deck (PPTX), which you can download immediately upon purchase.

GenAI use is rising globally. Many organizations set GenAI strategies and launch pilots across functions. Yet most stall at the proof-of-concept stage and never show measurable financial or operational results.

This PPT presentation outlines the missing piece: an effective GenAI Operating Model. It defines how leaders should fund, build, deploy, govern, and measure GenAI across the organization. Without it, teams duplicate work, data stays unprepared, risks go unmanaged, and successful pilots do not scale.

To generate value from GenAI, leaders need to define a GenAI Operating Model that puts data at the heart of the organization.

A robust GenAI Operating Model includes 6 key elements:

1. Devise a Component-centric GenAI Operating Model
2. Define a Core GenAI Team
3. Manage and Govern Data
4. Select a Viable Approach to GenAI Development
5. Establish Common Infrastructure for IT Teams
6. Ensure Risk and Compliance Governance

Each of these elements is discussed in depth.

This PowerPoint presentation on GenAI Operating Model framework also includes some slide templates for you to use in your own business presentations.

Source: Best Practices in Operating Model, GenAI PowerPoint Slides: GenAI Operating Model Design PowerPoint (PPTX) Presentation Slide Deck, LearnPPT Consulting

TARGET OPERATING MODEL PPT SLIDES

Six Critical Elements for Building a GenAI Operating Model

This PPT slide outlines the 6 key elements necessary for designing a GenAI operating model within organizations. It emphasizes that GenAI is now embedded in daily work routines across many firms, with a significant portion of organizations actively using generative AI in at least one business function. The focus is on how to translate this adoption into scalable results, highlighting that the challenge lies not in the model itself, but in the operational framework around it.

The core of the slide features a circular diagram that visually breaks down the 6 elements leaders should prioritize. These include devising a component-centric GenAI operating model, defining a core GenAI team, managing and governing data, establishing common infrastructure for IT teams, ensuring risk and compliance governance, and selecting a viable approach to GenAI development. Each element appears to be interconnected, underscoring the need for a holistic approach to operationalizing GenAI.

A brief paragraph on the left provides context, noting that many organizations struggle to scale GenAI effectively. It points out that scaling is less about the technology and more about the operational and governance structures that support it. The bottom banner reinforces that organizations will not see repeatable results until they clearly define ownership, standards, and controls from start to finish. Overall, this slide offers a practical framework for senior leaders to consider when integrating GenAI into their operational models, emphasizing the importance of governance, infrastructure, and clear team roles.

Comparison of GenAI Development Models by Speed, Control, and Scalability

This PPT slide compares 3 GenAI development models—Centralized, Federated, and Decentralized—focusing on their differences in speed, control, and scalability. Each model is depicted with a diagram illustrating the placement of data sources, Gen AI teams, and core components like processing, data repositories, and data services. The diagrams highlight how these elements are organized within each model, emphasizing the structural variations.

The accompanying text explains the strengths and weaknesses of each approach. Centralized GenAI works best when speed and cost control are priorities, with a setup that consolidates teams into a single delivery unit. However, it struggles with slow decision-making due to limited domain ownership. Federated models enable domain teams to manage their data and workflows independently, promoting faster domain-specific development, but requiring strong coordination. Decentralized GenAI demands high maturity and tech capabilities, allowing direct deployment of AI agents by domains, but introduces risks like drifting standards and higher costs.

The slide concludes with guidance on choosing the appropriate model based on organizational maturity and needs. It suggests centralization for quick, cost-effective deployment, federation for balanced control and speed, and decentralization for mature organizations seeking agility. This comparison helps executives understand how to align their AI development strategy with their operational capabilities and goals. The visual and textual content together serve as a decision-making framework for selecting the right model to support scalable AI initiatives.

Component-Based Phased Deployment of GenAI Architectures

This PPT slide discusses a phased, component-based rollout approach for adopting GenAI architectures. It emphasizes that a modular, layered deployment allows leaders to implement GenAI quickly without needing to rebuild their entire infrastructure from scratch. The focus is on designing a flexible operating model that can evolve as the technology matures, avoiding the pitfalls of a one-time, monolithic overhaul that risks obsolescence or wasted resources.

The left side of the slide highlights the core element: developing a component-centric GenAI operating model. It stresses the importance of creating a blueprint that aligns with strategic goals and measurable use cases. The overview section warns against treating GenAI as a one-off project, advocating instead for a continuous, disciplined process of releasing updates and maintaining the component blueprint. This approach ensures the architecture remains relevant and adaptable to market shifts and technological advances.

On the right, detailed guidance is provided for extending mature components like cloud foundations, data pipelines, and identity access. It points out that these extensions are more capital-intensive, but necessary for scaling. The slide recommends prioritizing high-volume, clear use cases that deliver measurable outcomes, and iterating through disciplined releases rather than constant, unstructured changes. It also underscores the importance of defining ownership and maintaining a clear delivery plan, including change roadmaps and risk management, to keep the rollout on track. Overall, the slide advocates for a pragmatic, phased approach that balances speed with strategic discipline.