How to do AI analysis you can actually trust (audio)
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How do I know the numbers AI gives me are actually right?
Treat AI analysis like a junior analyst's first draft: make it show the code or SQL it ran, re-run the key figures a second time, and check a few numbers you already know by heart. Tools that execute code on your actual file hallucinate far less than chat answers from memory, and asking twice catches most fabrications. A final human pass on anything going to investors is non-negotiable.
Go deeper
18 resources.
How to do AI analysis you can actually trust (Spotify)
Spotify version for founders who live in podcasts.
Listen on Spotify open.spotify.com →LLMs and Agents Are Overhyped, with Dr. Andriy Burkov (SDS 867)
A respected ML author's antidote to blind trust in AI analysis.
Open superdatascience.com →How to do AI analysis you can actually trust
2,000+ hours of testing distilled into verification techniques for ChatGPT, Claude, and Gemini.
Open lennysnewsletter.com →Why ChatGPT and Claude Give You Different Answers Every Time You Analyze Feedback
Explains non-determinism: why even temperature zero runs differ, and what to do about it.
Open chattermill.com →How to Prevent AI Hallucinations: 3 Hidden Threats When AI Analyzes Your Data
Concrete failure cases like '40% growth' that was actually 14%, and the guardrails.
Open databox.com →On Accuracy When LLMs Analyze Real-World Data
A clear-eyed look at where LLM analysis of real datasets goes wrong.
Open verbagpt.com →What Are AI Hallucinations?
The plain-language primer to share with your team on why AI invents things.
Open ibm.com →LLM Hallucination Statistics 2026
Aggregated hallucination-rate data so you calibrate trust per task type.
Open sqmagazine.co.uk →Which AI Hallucinates Least? Benchmark Rates Data
Current model-by-model hallucination benchmarks to inform your tool choice.
Open suprmind.ai →Beyond Fine-Tuning: Strategies for Mitigating Hallucinations in LLMs for Data Analytics
The research grounding for why code execution and grounding beat raw chat answers.
Open arxiv.org →Solving the Very-Real Problem of AI Hallucination
Practical mitigation patterns including cross-model disagreement checks.
Open knostic.ai →Ethan Mollick: testing ChatGPT and Claude on a brutally hard Excel file
Models the exact behavior you should copy: spot checks even when output looks perfect.
Open x.com →Julius AI Review: Is It Worth It for Data Analysts?
Documents where a dedicated AI analyst tool hallucinates plausible numbers on complex stats.
Open letdataspeak.com →"My AI is Lying to Me": user-reported LLM hallucinations
Peer-reviewed evidence of real users' hallucination encounters, patterns worth knowing.
Open ncbi.nlm.nih.gov →6 steps in fact-checking AI-generated content
A simple checklist you can turn into a team habit.
Open techtarget.com →Why Learning SQL Beats Relying on AI: Understanding Data Still Matters
The verification argument: if you can't verify generated analysis, you can't use it.
Open learnsql.com →LLM Hallucination: What It Is and How to Prevent It in Production
Production-grade prevention patterns once AI analysis becomes routine at your startup.
Open alicelabs.ai →Terms in this answer
More in Data Analysis
- Why let AI analyze my data instead of learning Excel formulas or SQL? 18 →
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- What can AI-in-spreadsheets (Claude in Excel, Gemini in Sheets) actually do? 20 →
- Which AI tool should I use for data analysis: ChatGPT, Claude, Gemini, or a dedicated tool? 18 →
- Can AI write SQL for me and query my database in plain English? 18 →
- Is it safe to put my company's data into AI tools? 18 →
- How do I build dashboards and charts with AI, without a BI tool or a data team? 18 →
- How do I analyze customer feedback, reviews, and support tickets at scale with AI? 18 →
- Which metrics should my startup track, and how can AI help me stay on top of them? 18 →
- Can AI clean up my messy data: duplicates, formats, and half-filled columns? 18 →
- Do I still need to hire a data analyst, or can AI cover it for now? 16 →
- How do founders use AI for financial modeling and forecasting? 18 →
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The same ground, over in Grow & market, our Starting Up track.
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