You don't need AI in your business (you need this instead)

AI Strategy Lab
Focus on Problem-First Approach

In this episode of the AI Strategy Lab, I advocate for halting the solution-first approach to AI and instead emphasizing the problem space. Through real-world examples and the introduction of my CLEAR framework, I guide you on how to effectively identify business problems, map the user journey, delve into root causes, evaluate solutions, and measure results to ensure efficiency and ROI.

Key Learnings:
The pitfalls of leading with AI tools.
A thorough breakdown of the CLEAR framework.
Essential questions to determine the problem and analyze the journey.
Framework for assessing solution options by complexity, ROI, risks, and rollout.
Setting measurable success metrics and fostering iterative improvement.
Critical questions to avoid haphazard AI integration.

Subscribe for deeper dives into each step of CLEAR, and learn how to apply these strategies in a business-centric manner.

Chapters
0:00 Introduction
0:35 Shiny Object Syndrome and the Solution-First Trap
1:12 Start with the Problem, Not Solutions
2:09 “AI is the Solution Looking for a Problem”
3:07 Beginning with Customer Experience; Defining the Problem (Steve Jobs)
3:58 Real-World Validation of AI Misapplication
4:38 Freelance Platforms and Solution-First Requests
5:20 Sales Proposal Automation Case Study
6:57 Bottom-Up Trap vs. Top-Down Fantasy
8:02 Unsupported MVPs and Vendor-Driven AI Missteps
9:45 Introducing the CLEAR Framework
12:13 C — Capturing the Real Problem
16:11 L — Learning the User Journey
19:18 E — Exploring Root Causes
22:50 A — Assessing Solution Options
27:01 R — Results and Iteration
29:28 4 Key Questions to Avoid Solution-First Trap
31:26 Wrap-Up and Next Steps

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