What is Real Problem AI?

Real Problem AI is a curated directory of 200+ real problems worth building an AI startup around. Each problem is scored honestly on severity, AI feasibility, market signal, and competition gap. We're for builders looking for what to build, not for ethics debates about AI.

What is the difference between Real Problem AI and AI ethics or AI risks indexes?

Real Problem AI catalogues problems AI can solve — productive, commercial opportunities for builders. AI ethics indexes catalogue problems with AI itself (bias, environmental cost, copyright, consciousness). Different intent, different audience: founders and indie hackers vs researchers and policy folks.

What should I build with AI in 2026?

Look for problems with high severity (it costs people hours, sleep, or revenue every week), high AI feasibility (LLMs, vision or voice are great at this today), strong market signal (Reddit threads + willingness to pay), and a clear competition gap (incumbents miss the same obvious thing). Real Problem AI scores 200+ such problems for you on those four axes.

Where do Real Problem AI's startup ideas come from?

From three sources, scanned each cycle: 1) Reddit threads where people describe a real friction in their own words, 2) podcasts and talks of founders young builders trust (Nikhil Kamath, Aman Gupta, Ankur Warikoo, Raj Shamani, Andrej Karpathy, Greg Isenberg), and 3) a continuous 1,000+ source scan covering forums, app store reviews, regulator filings, and field interviews.

Is Real Problem AI free?

Yes. Browsing every problem, opening every score breakdown, raising your hand on a co-founder match, and the founder vault are all free. There is no paywall.

How is each problem scored?

Four axes, each 1-10, weighted: Problem Severity (30%), AI Feasibility (25%), Market Signal (25%), Competition Gap (20%). Weighted average is the Opportunity Score on each card. Only problems clearing 7.0+ make the live list.

Why is deepfake grandparent fraud the fastest-growing scam, and banks have no answer?

AI voice clones from a 3-second TikTok now defeat both family trust and bank voice biometrics. Reported losses are climbing in 2026. Banks reimburse selectively.

Category: FinTech · Trend: GenMedia · Opportunity score: 9.3 / 10

What is the “Why is deepfake grandparent fraud the fastest-growing scam, and banks have no answer?” problem in 2026?

AI voice clones from a 3-second TikTok now defeat both family trust and bank voice biometrics. Reported losses are climbing in 2026. Banks reimburse selectively.

Who has this problem?

Adults aged 60+ and their families, plus banks under regulatory scrutiny for failing-to-prevent fraud.

Evidence this problem is real

“Mum nearly wired $11k after a call in my exact voice asking for bail money. She only stopped because the wire instructions felt wrong.”

Sourced from FTC consumer fraud reports 2026, FBI IC3 advisories, NYT and BBC May 2026 investigations into synthetic-voice scams.

Existing players in this space

Pindrop — Enterprise-only
Veriff / Onfido — ID, not voice provenance
Bank fraud reimbursement — Reactive, capped, slow

What existing players are missing

A family-grade voice-fraud shield: shared duress codes, cryptographic callbacks for any wire above a threshold, telco-integrated voiceprint warnings, and a one-tap report-to-bank flow that triggers a hold.

How Real Problem AI scores this opportunity

Aggregate score: 9.3 / 10. Four-axis rubric:

Problem severity: 10 / 10
AI feasibility today: 8 / 10
Market signal: 10 / 10
Competition gap: 9 / 10

How to build a solution: stack hints

Cross-vendor voice-clone detection
Household-key duress codes
STIR/SHAKEN integration
Wire-hold trigger integration with major banks