EP 597: Do 95% of AI Pilots Fail? Why You Should Ignore MIT’s Viral New AI “Study”

You got duped.

The MIT ’95 % of AI pilots fail’ study has taken over the internet, and it’s one of the worst studies I’ve ever read. 

(And I’ve read thousands.) 

↳ So, what’s the truth?
↳ Is AI a bubble that’s about to pop? 
↳ Why is this study rubbish? 
↳ And how does it impact you? 

Join us and we’ll dish it all.

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Topics Covered in This Episode:

1. MIT AI Study Claims 95% Failure Rate
2. Breakdown of MIT Study Methodology
3. Impact of Viral MIT AI Study Headlines
4. Flaws in MIT Study ROI Measurement
5. Comparison With Reputable AI ROI Studies
6. MIT Study’s Biased Participant Selection
7. Nanda Project Marketing in MIT Report
8. Five Major Red Flags in MIT AI Research
9. Business Implications of Flawed AI Pilots Data
10. How Media Sensationalizes AI Study Results
    
    

Timestamps:
00:00 "MIT AI Study Critique"

04:16 AI Investments Trigger Stock Market Decline

06:37 "Host's Background Overview"

10:58 Flawed AI Study Critique

13:28 MIT Study Highlights AI Implementation Challenges

18:58 AI Work Trends & ROI Insights

20:17 "Crossing the Gen AI Divide"

23:25 Flawed Study with Misleading Claims

29:34 "Uncritical Reposting Spurs Fake Study"

30:30 "Read Studies, Not Summaries"

Keywords:
MIT AI study, 95% AI pilot failure, enterprise AI pilots, generative AI ROI, AI pilot success rate, AI project failure, state of AI in business, gen AI divide, MIT Media Lab, AI investment, AI implementation challenges, AI return on investment, AI research methodology, AI study critique, AI marketing, Nanda project, AI vendor solutions, agentic web, MCP protocol, A2A protocol, Fortune article, AI media coverage, stock market impact, NVIDIA stock drop, Palantir, ARM stock, qualitative AI data, AI structured interviews, AI industry surveys, IDC AI research, Snowflake ESG report, McKinsey AI analysis, Microsoft Work Trend Index, Boston Consulting Group AI study, AI adoption rates, enterprise AI transformation, sample size in AI studies, research limitations, AI productivity impact, AI workflow automation, AI business decisions, AI bubble, AI reporting in media, AI pilot timeline, enterprise AI tools, AI agent capabilities, AI autonomy, custom AI solutions, AI study bias, marketing disguised as research, sensationalized AI studies.

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