Everyday AI Podcast – An AI and ChatGPT Podcast

Ep 852: Measuring AI ROI: Why you’re doing it wrong and the 7 Steps to fix it (Start Here Series Vol 11)

August 31, 2026

AI Summary

5 min read

In August 2025, a single study went viral claiming 95% of enterprise AI pilots delivered zero ROI. Nvidia stock dropped, Palantir fell nearly 9%, and headlines across the business press ran with the story. The problem, according to Jordan Wilson, host of the Everyday AI Podcast, is that the study was marketing disguised as research. It was based on 52 qualitative interviews with no quantitative data, and it measured P&L impact in under six months—a timeframe that makes no sense for any digital transformation. The company behind it was selling an agentic AI product. Meanwhile, larger quantitative studies tell a different story: the IDC found a $3.70 return for every dollar invested in AI, Wharton reported 74% of enterprises saw positive ROI on generative AI, and Deloitte found 84% of AI investors reported gains. Yet most companies still cannot prove AI is working for them. The reasons are behavioral, not technical.

Why the ROI Debate Is Still Happening

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What you'll learn

1 (00:00) **Episode Introduction & The Start Here Series** - Jordan Wilson introduces the Start Here series and frames the core problem: most companies cannot prove AI ROI.
2 (04:06) **The GDP Val Benchmark: AI vs. Expert Humans** - A key benchmark from OpenAI shows top AI models already outperform expert humans in blind evaluations.
3 (06:43) **The MIT "Study" That Misled the Market** - Jordan debunks a widely-cited MIT study that claimed 95% of AI pilots deliver zero ROI, calling it a piece of marketing.
4 (10:15) **The Real Problem: Workers Are Pocketing Productivity** - The reason many companies don't see AI ROI is that employees are using AI secretly and banking the time savings.
5 (15:04) **The Simple Formula for AI ROI** - Jordan provides a straightforward equation for calculating return on investment in AI.
6 (16:32) **Five Patterns of ROI Measurement Failure** - Jordan identifies the common reasons why individuals and departments fail to measure AI ROI.
7 (20:08) **The BASE Rule: Baseline Assessment of Standard Execution** - Jordan introduces a crucial first step before any AI implementation: establishing a human baseline.

+ Full timestamped outline available in the app

Guests on this episode

Jordan Wilson

Show Notes

Why can't most companies show their ROI on GenAI?

Because their implementation is backwards.

If you're using the same digital transformation playbook that you used for the social media and cloud eras, you're in trouble.

On this 'Start Here Series' episode, we break down what your company is doing wrong and the 7 Step process to properly calculate ROI on your AI efforts.

Measuring AI ROI: Why you’re doing it wrong and the 7 Steps to fix it -- An Everyday AI Chat with Jordan Wilson

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Topics Covered in This Episode:

Proving and Measuring AI ROI in Companies
OpenAI’s GDP Benchmark: AI vs Experts
Debunking MIT’s Viral Zero ROI Study
Quantitative AI ROI Data from Business Studies
Invisible Productivity: AI Savings Pocketed by Workers
Limitations of Pre-AI Job Roles and Metrics
ROI Calculation: Time Saved and Cost Reduction
Five Main Reasons AI ROI Isn’t Measured
Seven-Step AI ROI Measurement Blueprint
Importance of Ongoing AI Model Retesting
AI ROI: Training, Education, and Implementation Gaps

Timestamps:

00:00 "AI ROI: Fixing the Debate"

04:50 "AI ROI Debate is Pointless"

08:03 AI Implementation Yields Positive ROI

12:13 AI Reshaping Work Structures

15:08 AI ROI Challenges

20:11 "Baseline Assessment Before AI Implementation"

23:49 "AI Operating System Discussion"

24:35 "Standardized Testing for AI Models"

28:26 "Rethink AI ROI Urgency"

31:37 "Everyday AI: Subscribe & Explore"

Keywords:

measuring AI ROI, AI return on investment, generative AI ROI, GenAI ROI measurement, ROI on artificial intelligence, AI productivity, time saved with AI, cost reductio