How can you measure ROI on GenAI for your team? 🤔

Internal evaluations and intentionality. 

We've helped thousands of orgs put LLMs to work and ACTUALLY save time. On today's show, we're dishing the 7 steps you need to follow. 

What’s the best LLM for your team? 7 Steps to evaluate and create ROI for AI -- An Everyday AI chat with Jordan Wilson

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Topics Covered in This Episode:

1. Choosing the Right Large Language Model
2. Evaluating LLMs for Business ROI
3. Front-End AI Operating Systems Explained
4. Common Traps in AI Model Evaluation
5. Public Benchmarks for LLM Evaluation
6. Seven-Step LLM Evaluation Framework
7. Measuring Pre-GenAI Human Baselines
8. Building Realistic AI Test Datasets
9. Calculating ROI for GenAI Implementation
10. Monthly Retesting and AI Model Updates

Timestamps:

00:00 Choosing the Right AI Model

07:02 Adapting Workflows for AI Integration

10:58 "Gemini's Versatile Modes Overview"

14:30 Avoiding AI Shiny Object Syndrome

15:36 AI Evaluation for Reliability and Improvement

20:36 "Data Testing Guide Essentials"

25:15 Realistic and Messy Data Essentials

26:06 "Building Effective AI Workspaces"

31:08 AI Evaluation and ROI Calculation

34:11 Human Oversight in AI Testing

35:52 Evaluating GenAI Use Cases

39:00 "NotebookLM: AI-Powered Idea Organizer"

Keywords:

Large Language Model, LLM, generative AI, AI operating system, front end AI models, AI evaluation, model ROI, model evaluation steps, AI benchmarks, scientific benchmarks, API connection, enterprise AI, ChatGPT, Claude, Gemini, Copilot, team AI adoption, knowledge worker AI, operating system choice, productivity modes, connectors, deep research mode, agent mode, image generation, web search, Canvas mode, advanced voice mode, business process automation, workflow evaluation, change management, AI training, 

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Vibe coding is dead simple. Head to AI.Studio/build to create your first app. 

Vibe coding is dead simple. Head to AI.Studio/build to create your first app.