AI Strategy & Implementation & Agile Methods

Course overview

AI Strategy & Implementation Module 1: Design Thinking with AI Introduction to Design Thinking as an innovation framework for AI managers: user-centeredness, prototyping & collaboration Application of the Design Thinking process in six phases: Understanding, Observing, Defining, Ideation, Prototyping, Testing AI-supported methods for user research: GPT prompts for persona development, empathy maps, user journey mapping Development of user-centered solutions with AI support: ChatGPT, DALL·E, Claude, Perplexity & Gemini in the design process Practical mini-challenges & main challenge: Development of an AI product advisor for e-commerce or a personal use case Business Model Canvas & Lean Canvas: Structuring ideas into marketable concepts Prototyping formats: Storyboards, wireframes, click-dummies, fake ads, explanatory videos & AI-generated scenarios Testing & iteration: Feedback methods such as think-aloud, peer tandems, "I like / I wish / What if" Promotion of growth mindset & creative team culture: empathy, openness, error-friendliness & co-creation Tools & platforms for AI-supported design: Uizard, Landing.so, WIX, Midjourney, ElevenLabs, Sora Module 2 Agile Methods with AI Status quo & challenges in AI projects (uncertainty, data quality, interdisciplinary teams) Introduction to agile principles & frameworks (Agile Manifesto, Scrum, Kanban, Design Thinking) Lean Startup & MVP development (hypotheses, A/B testing, iterative learning) Introduction to Scrum, detailed Scrum events, backlog management, writing user stories, Scrum tools User story mapping & prioritization (customer journey, MoSCoW, WSJF, planning poker) Roles & processes in agile project management (Product Owner, Scrum Master, UX Designer, Developer) Tools & methods for agile management (Jira, Trello, etc.) Moderation & workshop design (Liberating Structures, systemic questions, Devils Facilitation Playground) AI & agility - synergies & specifics (explainable AI, ML-Ops, data drift, ethical reflection) Module 3: AI Strategy & Implementation AI in the company: defining potentials, technologies & challenges / effective prompting frameworks AI readiness & company analysis: capturing AI maturity / questionnaire for use case identification / GAP & SWOT analysis for AI projects / trends in AI usage and benchmarking Project implementation & ROI determination: project brief and business case development / ROI calculation for AI investments / vendor selection & make-or-buy decisions Change management in AI projects: understanding human reactions to change / elements for successful change strategies / shaping sustainable change in AI implementation / stakeholder management and communication strategies AI ethics & governance: defining ethics & governance in the AI context / law, compliance, bias, fairness, transparency & security / the governance toolbox for responsible AI use / defining organizational structures and responsibilities Module 4: AI Agents and Automation Basics & types of AI age…

Upcoming dates

• 2026-09-27T22:00:00.000Z · 2026-10-24T22:00:00.000Z · Berlin · Blended Learning
• 2026-09-27T22:00:00.000Z · 2026-10-24T22:00:00.000Z · Rostock · Blended Learning
• 2026-09-27T22:00:00.000Z · 2026-10-24T22:00:00.000Z · Düsseldorf · Blended Learning
• 2026-09-27T22:00:00.000Z · 2026-10-24T22:00:00.000Z · Düsseldorf · Blended Learning
• 2026-09-27T22:00:00.000Z · 2026-10-24T22:00:00.000Z · München · Blended Learning