Building Ai-Powered Business Models: Strategy To Scale
Published 4/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 52m | Size: 3.23 GB
Use AI & GenAI to redesign value, choose use cases, and scale responsibly with proven frameworks and tools.
What you'll learn
Distinguish traditional AI vs generative AI and select the right approach for a business problem.
Identify AI opportunities across the Business Model Canvas (value, customers, revenue, operations).
Scope and pitch AI use cases with the AI Canvas, including workflow fit, data needs, and KPIs.
Assess organizational readiness with the Five P model: Purpose, People, Process, Platform, Performance.
Plan data, tooling, and MLOps needs to deploy, monitor, and improve AI over time.
Write effective prompts and create repeatable prompt templates for common business workflows.
Requirements
There are no prerequisites for this course
Description
72% of global executives say AI will fundamentally transform their industry-yet many teams still struggle to explain what AI can (and can't) do, pick the right use cases, and move beyond "pilot mode."
And that gap is costly
• Nearly 3 out of 4 organizations have implemented AI in at least one function.
• But only a minority successfully scale AI into core operations and business models.
AI isn't just another tool to "add on." When done well, it reshapes how you create value, deliver experiences, and capture revenue-through personalization, automation, prediction, and entirely new AI-native offerings.
This course is designed to help you move past the hype and build AI-Powered Business Models with a clear, practical, business-first approach.
In this course, you'll learn how to
• Understand traditional AI vs generative AI in plain English (capabilities + limits)
• Rethink your business model using the Business Model Canvas (and where AI fits)
• Identify high-impact opportunities for automation, insight, and engagement
• Scope AI projects with the AI Canvas so stakeholders align early
• Assess readiness with the Five P Framework (Purpose, People, Process, Platform, Performance)
• Follow an adoption roadmap from pilot → internal capability → scale
• Prepare your foundation: data quality, infrastructure choices, MLOps, and change management
• Learn what's working across industries (retail/marketing, manufacturing/supply chain, finance, healthcare)
• Choose the right tools: cloud AI services, no/low-code platforms, open-source stacks, orchestration
• Use generative AI in real workflows with prompt engineering, prompt libraries, and risk controls
By the end, you'll know how to connect AI to measurable business outcomes, design AI-enabled value propositions, and build a roadmap your organization can actually execute-responsibly and sustainably.
Whether you're leading a team, launching a product, driving innovation, or simply future-proofing your career, this course will give you frameworks, examples, and practical steps you can apply immediately.
Who this course is for
Business leaders and managers exploring AI strategy
Entrepreneurs and founders designing AI-enabled products or services
Product managers and product owners building AI features
Innovation, digital transformation, and strategy teams
Marketing and retail professionals focused on personalization and automation
Operations, supply chain, and manufacturing leaders improving efficiency
Finance, banking, and insurance professionals working on risk, fraud, and automation
Consultants and analysts advising clients on AI adoption
Non-technical professionals who want a practical, business-first AI roadmap
Students (MB A/Business/Tech) looking to understand AI-powered business models
