Data Analytics and AI Strategy Toolkit (PowerPoint PPTX Slide Deck)

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BENEFITS OF THIS POWERPOINT DOCUMENT

1. Domont Consulting is trusted by 200,000+ executives, consultants and entrepreneurs from small & large organizations.
2. Includes 700 PowerPoint slides + 40 Excel sheets + 65 minutes of video training.
3. Includes frameworks, tools, templates, tutorials, real-life examples, best practices, and video training.

ARTIFICIAL INTELLIGENCE PPT DESCRIPTION

This product (Data Analytics and AI Strategy Toolkit) is a 700-slide PPT PowerPoint presentation slide deck (PPTX) with a supplemental Zip archive file document, which you can download immediately upon purchase.

This Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants. It is considered the world's best & most comprehensive Data Analytics and AI Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to design and implement a robust data analytics & AI strategy.

The Toolkit includes: 700 PowerPoint slides + 40 Excel sheets + 65 minutes of video training.

This Toolkit includes frameworks, tools, templates, tutorials, real-life examples, best practices, and video training to help you:
• Define and implement your Data Analytics Strategy: (1) Summary of the Corporate & Business Strategy, (2) Current & Target Data Analytics Maturity Levels, (3) Data Analytics Vision, Mission & Values, (4) Strategic Objectives and KPIs to reach our Vision, (5) Team & Budget, (6) Guiding Principles
• Define and implement your AI Strategy: (1) Summary of the Corporate & Business Strategy, (2) AI Essentials, (3) Current & Target AI Maturity Levels, (4) AI Vision, Mission & Values, (5) Strategic Objectives and KPIs to reach our Vision, (6) Team & Budget, (7) Guiding Principles
• Build your 4 pillars to reach your Data Analytics Strategic Objectives: (1) Data Management & Infrastructure, (2) Data Governance & Compliance, (3) Analytics Tools & Techniques, (4) Data-driven Organization
• Identify the key Technologies to enable your AI Strategy: (1) AI data center, (2) Machine Learning, (3) Deep Learning, (4) Generative AI Chatbots, NLP & Prompt Engineering, (5) Artificial General Intelligence, (6) Cloud Computing
• Identify Use Cases and Potential Initiatives in Data Analytics and AI
• List your potential initiatives in Data Analytics and AI
• Create your business cases and financial models to assess potential initiatives
• Prioritize, plan and implement your projects: (1) Project prioritization, (2) Business roadmap, (3) Governance, (4) Dashboards, (5) Project implementation: agile methodology, design thinking and traditional methodology, (6) Continuous improvement (7) Post program/projects evaluation and lessons learnt
• Define and implement your change management strategy, internal communication strategy, and stakeholder engagement strategy: (1) Change management strategy, (2) Change management plans, (3) Implementation, tracking and progress management, (4) Effective communication

Source: Best Practices in Artificial Intelligence, Analytics PowerPoint Slides: Data Analytics and AI Strategy Toolkit PowerPoint (PPTX) Presentation Slide Deck, Domont Consulting

ARTIFICIAL INTELLIGENCE PPT SLIDES

Six-Phase Framework for AI Strategy Development and Implementation

This PPT slide outlines a structured approach to developing an AI strategy, emphasizing a six-phase process refined over a decade through iterative testing. The first section summarizes the strategic foundation, including key elements like the corporate and business strategy, AI essentials, current and target AI maturity levels, vision and mission, strategic objectives with KPIs, team and budget considerations, and guiding principles. These components establish a clear understanding of the company's overarching goals and the role AI will play.

The second section highlights critical technological enablers, listing core AI technologies such as data centers, machine learning, deep learning, generative AI (including chatbots, NLP, prompt engineering), general AI, and cloud computing. These are the tools that support the execution of the AI strategy, indicating a comprehensive technological ecosystem.

The third section focuses on practical application, identifying potential use cases and initiatives aligned with strategic objectives. It covers functions across the organization—sales, marketing, supply chain, customer service, HR, data analytics, finance, IT, legal, and compliance—showing the broad scope of AI integration. This part underscores the importance of mapping specific business functions to AI initiatives to realize tangible benefits.

Further down, the slide references the importance of assessing business cases and financial models to evaluate potential initiatives, followed by project prioritization and business roadmap development. The structure suggests a disciplined, phased approach to implementation, ensuring alignment with strategic goals and resource allocation.

Overall, this slide offers a detailed blueprint for organizations aiming to embed AI into their operations systematically. It underscores the need for a clear strategy, technological readiness, targeted use cases, and disciplined execution, making it a valuable reference for senior leaders planning AI-driven transformation.

Six-Phase Data Analytics Strategy Framework for Organizational Maturity

This PPT slide outlines a comprehensive framework for a data analytics strategy, emphasizing a structured, six-phase approach refined over 2 decades. The opening statement highlights the evolution and robustness of this methodology, built through extensive trial and error. The top section summarizes key strategic elements, including the corporate and business strategy overview, data maturity levels, vision and values, strategic objectives, team and budget considerations, and guiding principles. These components set the foundation for aligning data initiatives with overarching corporate goals.

The core of the slide presents 4 pillars necessary to achieve strategic objectives. These pillars are: Data Management & Infrastructure, Data Governance & Compliance, Analytics Tools & Techniques, and Data-driven Organization. Each pillar contains specific focus areas. For example, Data Management emphasizes sources, storage, integration, quality, and emerging technologies. Data Governance covers frameworks, privacy, compliance, and trends. Analytics Tools focus on visualization, statistical methods, machine learning, and data preparation. The Data-driven Organization pillar addresses characteristics, culture, skills, infrastructure, and innovation.

Below the pillars, the slide hints at use cases and initiatives tailored to each pillar, suggesting a practical application of the framework. The overall message is that this multi-faceted approach has been tested and refined, making it a reliable blueprint for organizations seeking to embed data analytics deeply into their operations.

Potential buyers should see this as a strategic roadmap that combines technical, organizational, and procedural elements. It offers a clear, phased path to develop a mature data analytics capability aligned with business needs. The detailed breakdown signals a thorough, proven methodology suitable for organizations aiming to transform their data practices systematically.