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AI Product Strategy: From Concept to Market

Master the shift from AI experimentation to market-ready products with a framework designed for the modern leader. This course strips away the hype to focus on building sustainable business models, navigating technical complexity, and securing user trust. Move beyond the "cool demo" and gain the strategic roadmap needed to launch and scale AI-native solutions.

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2 students 1 lectures 2m Advanced English
AR
Created by Abhinav Rastogi · Chief Product Manager AI/ML, Automation, IoT, Robotics, Gen AI. Business Consulting
AI Product Strategy: From Concept to Market
$49.99
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  • 1 on-demand lectures
  • 2m total content
  • Mobile & tablet access
  • Full lifetime access
  • Bookmark any lecture
  • Certificate of completion

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What You'll Learn

By the end of this program, participants will transition from "AI-curious" to "AI-strategic," equipped with the following competencies:
The AI Opportunity Audit: Learn how to evaluate if a problem is best solved by traditional logic or if it truly requires a machine learning approach.
Defining "Intelligence Logic": Master the framework for designing proprietary AI engines that scale market reach and provide unique competitive moats.
The Technical Bridge: Gain the vocabulary to lead engineering teams through discussions on model selection, data ingestion, and the trade-offs of fine-tuning vs. RAG (Retrieval-Augmented Generation).
Monetization & Unit Economics: Understand the "cost of inference" and how to price AI products effectively to ensure long-term profitability.
High-Security Product Design: Learn to integrate data invisibility and advanced encryption concepts into the product roadmap to build institutional-grade trust.
GTM Strategy for AI: Develop a launch plan that addresses user "AI anxiety," focusing on transparency, ethical data use, and rapid feedback loops.

Course Content

1 sections · 1 lectures · 2m total

Module 1: Introduction
1 lectures · 2m
Basics about AI Product Strategy
Free Preview
2m

Requirements

  • This course is designed for strategic impact, focusing on the "Product" and "Business" layers of Artificial Intelligence. To get the most out of the sessions, participants should meet the following criteria:
  • Professional Foundation: At least 3–5 years of experience in product management, project leadership, or business operations.
  • Strategic Mindset: A basic understanding of traditional SaaS business models and software development lifecycles (SDLC).
  • Conceptual AI Awareness: Familiarity with what AI can do (e.g., Generative AI, recommendation engines) is required, but no coding experience or data science degree is necessary.
  • A "Problem-First" Outlook: A willingness to deconstruct hyped technology to find the underlying user pain points.

Course Description

The Playbook for Leading in the Machine Learning Era
The world doesn't need more "AI features"—it needs AI products that solve real problems and scale. Most leaders are caught between the hype of LLMs and the technical complexity of implementation. This course is designed to bridge that gap, turning high-level concepts into market-ready strategies.

Why This Matters Now
We are moving past the "experimentation" phase of AI. For managers and upcoming leaders, the challenge is no longer just "What is AI?" but "How do we build a sustainable business around it?" This one-day intensive (or multi-session workshop) focuses on the "Product" in AI Product Management.

What You’ll Master
The Opportunity Framework: How to distinguish between a "cool demo" and a viable market opportunity.

Intelligence Logic: Designing the core value proposition—moving from raw data to actionable insights.

Navigating the Technical Moat: Understanding enough about RAG, fine-tuning, and model selection to lead engineers without needing to code.

The Go-to-Market (GTM) Engine: Pricing AI products, managing the high cost of inference, and building user trust through transparency.

Security & Data Ethics: Practical frameworks for data privacy and "invisibility" in encryption to protect your most valuable asset: your users' data.

Who Is This For?
Current Managers: Who need to lead cross-functional teams (Dev, Data, Marketing) through an AI transition.

Aspiring Product Leaders: Who want to move beyond traditional SaaS into deep-tech product management.

Founders & Entrepreneurs: Building the next generation of AI-native startups.

The Delivery: Human-First, Tech-Second
We skip the academic jargon. You’ll get real-world case studies, hands-on strategy templates, and a "No-Fluff" guide to AI unit economics. By the end of this course, you won’t just talk about AI—you’ll have a roadmap to launch it.

"Strategy is about making choices. In AI, the most important choice is knowing what not to build."

Your Instructor

AR
Abhinav Rastogi
Chief Product Manager AI/ML, Automation, IoT, Robotics, Gen AI. Business Consulting