A Data & AI Strategy in 80 Days
Planning for the Successful Utilization of Data and the Use of AI
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This course is part of the certified "AI & Data Strategist" Master Class. When you enroll in the entire Master Class, you’ll save 21 percent compared to enrolling in the individual modules.
- Why Your Data and AI Projects Fail Without a Strategy (Failure Stories)
- Why a Strategy Increases Your Chances of Success (Success Stories)
- Why Companies Want a Data & AI Strategy (Trigger Points)
- Why Business, Data, and AI Strategies Go Hand in Hand
- Exercise: Why does your company need a data and AI strategy?
- Outlook: Self-Study Phase 1 & Exercises
The second part of the first webinar will take place on the same day.
Part 2 of the first webinar:
- Why Your Data and AI Projects Fail Without a Strategy (Failure Stories)
- Why a Strategy Increases Your Chances of Success (Success Stories)
- Why Companies Want a Data & AI Strategy (Trigger Points)
- Why Business, Data, and AI Strategies Go Hand in Hand
- Exercise: Why does your company need a data and AI strategy?
- Outlook: Self-Study Phase 1 & Exercises
What is a (successful) data and AI strategy?
- What Is Strategy (Product and Process)?
- What Is a Data & AI Strategy—and What Isn't It?
- What kinds of (data and AI) strategies are there (Quick Win, Lean, Domain, Enterprise, etc.)?
- What is the best strategy for finding the right strategy?
- What Kinds of Components Does a Data & AI Strategy Include?
- What Is a Defensive vs. Offensive Data & AI Strategy?
- What Makes a Successful Data & AI Strategy (TOP Framework)
- Video: Data & AI Strategy Framework Canvas
- Exercise: What do I expect from our data and AI strategy?
How do I design a (SMART) data and AI strategy?
- What is SMART (Specific, Measurable, Accepted, Realistic, Time-bound)?
- How does the classic strategy process work ("throwing a PowerPoint over the fence")?
- How Does the AI-Powered Strategy Process Work (ChatGPT, Claude, etc.)
- How does the collaborative strategy process work (Design Thinking, Co-Creation, Open Strategy)?
- How does the combined strategy process work (agent-based AI workflows and human-in-the-lead workshops)?
- How do I structure an agile strategy process from analysis to synthesis (Where to Play, Chances, Challenges, Choices, How to Win, Vision, Mission, and Milestones)?
- How Do I Design a Holistic Data & AI Strategy (BUDAr Loop: Business, User, Data & AI, Risks)
- Video: Data & AI Design Thinking Workshop Canvas
- Exercise: How do I structure our strategy kick-off workshop?
- A Look Back: Why, What, and How of a Data and AI Strategy
- Insight: Presentation and Discussion of Exercise Results (Data & AI Strategy Framework & Design Thinking Workshop Agenda)
- Insight: A Group Exercise Using the Growth Horizons Canvas
- Outlook: Self-Study Phase 2 & Exercises
The second part of the second webinar will take place on the same day.
Part 2 of the second webinar:
- A Look Back: Why, What, and How of a Data and AI Strategy
- Insight: Presentation and Discussion of Exercise Results (Data & AI Strategy Framework & Design Thinking Workshop Agenda)
- Insight: A Group Exercise Using the Growth Horizons Canvas
- Outlook: Self-Study Phase 2 & Exercises
Who are the stakeholders in a data and AI strategy?
- Who initiates a data and AI strategy?
- Who is responsible for a data and AI strategy?
- Who Is Affected by a Data & AI Strategy?
- Who should I (not) involve as a stakeholder?
- What are my duties and responsibilities as a Data & AI Strategist?
- What skills and knowledge should I already have—and which of these will I learn in these courses?
- Video: Stakeholder Analysis Canvas
- Exercise: Who are my stakeholders for our data and AI strategy?
When, where, and with what do I do what?
- What methodology do I use: Design Thinking & Lean (People, Processes, Place / Build-Measure-Learn)
- Where Should I Do What: Online Collaboration Spaces vs. Onsite Idea Room
- What do I use for what: traditional, collaborative, and AI-powered tools (Office, Miro, ChatGPT)
- When Do I Do What: Strategy, Innovation, Transformation & Operations (StratOps)
- How to Get Started: Your Roadmap for the Next 80 Days
- Video: Strategy Pyramid Canvas
- Exercise: How do I align the data and AI strategy with the business strategy?
- A Look Back: Who, Where (with whom), and When for a Data and AI Strategy
- Insight: Presentation and Discussion of the Exercise Results (Stakeholder Analysis & Strategy Pyramid)
- Insight: Joint Exercise Using the Data & AI Training, Thinking & Transformation Canvas
- A Look Ahead to the Master Class: Courses 2, 3, and 4
The second part of the third webinar will take place on the same day.
Part 2 of the third webinar:
- A Look Back: Who, Where (with whom), and When for a Data and AI Strategy
- Insight: Presentation and Discussion of the Exercise Results (Stakeholder Analysis & Strategy Pyramid)
- Insight: Joint Exercise Using the Data & AI Training, Thinking & Transformation Canvas
- A Look Ahead to the Master Class: Courses 2, 3, and 4
1. Why does my company need a data and AI strategy?
- Why Data and AI Projects Fail Without a Strategy
- Why a Strategy Increases the Chances of Success
- Why Business, Data, and AI Strategies Go Hand in Hand
2. What is a (successful) data and AI strategy?
- What Is Strategy (Product and Process)?
- What kinds of (data and AI) strategies are there?
- What Kinds of Components Does a Data & AI Strategy Include?
3. How do I develop a data and AI strategy?
- How Does the Collaborative & AI-Driven Strategy Process Work?
- How does the combined strategy process work (agent-based AI workflows and human-in-the-lead workshops)?
- How do I structure and design an agile strategy process, from analysis to synthesis?
4. Who are the key stakeholders in a data and AI strategy?
- Who initiates and is responsible for a data and AI strategy?
- Who is affected by a data and AI strategy, and who should (and should not) be involved?
- What are my duties and responsibilities as a data and AI strategist, and what skills are important?
5. How do I get started with the strategy process?
- Which methodology is appropriate?
- When Do I Do What: Strategy, Innovation, Transformation & Operations (StratOps)
- How do I get started?
This course offers you a digital blended concept that has been developed for part-time learning. Thanks to a flexible mix of online seminars and self-study phases, you are sure to reach your goal. This is how you learn in this course:
Learning environment: In your online learning environment, you will find useful information, downloads and extra services for this training course after you have registered.
Self-study phases: Learn independently, at your own pace and whenever you want. Our courses offer you didactically high-quality learning material.
Live webinars: In regular online seminars, you will meet your trainers in person. You will receive answers to your questions, specific assistance and instructions on how to deepen your knowledge and apply the skills you have acquired in practical exercises.
Learning Community: A digital learning community will be available to you throughout the course. trainers with other participants and the trainers , and ask questions.
Certificate of Completion and Open Badge: As a graduate of the class, you’ll receive a certificate of completion and an open badge, which you can easily share on professional networks (such as LinkedIn), among other places.
- You know why your company needs a data and AI strategy
- You explain why business, data, and AI strategies go hand in hand
- You know what makes a successful data and AI strategy
- You can structure and design an agile strategy process
- You bring together the right people for the data and AI strategy and understand the tasks and responsibilities involved in the strategy process
- You 're launching the strategy process: Learn the first steps and methodologies
- You have the playbook at your fingertips : Strategy, Innovation, Transformation & Operations (StratOps)
- Anyone who wants to tackle data- and AI-driven transformation at the decision-making level and create real business value through it
- Anyone with a basic understanding of data and business, as well as an in-depth understanding of at least one of these two areas
- Anyone with (professional) experience working on data projects in companies
- Customized training courses
- Direct application in practice
- Efficient use of time and resources