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AI Research
Backups on an AI-built product are almost always missing, because backups were never a feature — nobody thought to ask AI to build them. This article unpacks three common misconceptions, explains why the database and uploaded files need separate backups, gives four minimum standards, and explains why it only counts as a backup once you've tested restoring it.
AI Research
A product built with AI tools is usually feature-complete but empty on the defense side, because nobody told it to lock the doors. This article uses plain-language scenarios to explain what happens with three landmines — permissions, keys, and input validation — with a five-minute three-question self-check and the order to fix them in.
AI Research
A product built with Cursor, Claude Code, or Lovable can demo well, but when it's time to hand it to real customers, you don't know what's still missing. This article lists five things most commonly missing — security, backups, monitoring, deployment, error handling — one question to ask yourself for each, a 10-minute self-check, and the order to fix them in.
AI Research
Memory makes AI understand you better the more you use it, but ungoverned memory leaves your company more exposed. Using actual provisions from Taiwan's PDPA, the GDPR, and the EU AI Act, this article lays out a practical AI memory governance framework: tiering, retention and forgetting, PII compliance, and audit.
AI Research
Singapore and the UAE have ordered banks to retire SMS OTP on a deadline while India and Taiwan accelerate the transition, even as SIM swap fraud losses climb. This article uses each market's timeline and hard data on FIDO/passkeys to map out this authentication paradigm shift and a pragmatic upgrade path.
AI Research
Most companies treat producing an AI usage policy as governance done, yet 81% of organizations remain in the first two maturity stages. This article offers a five-level maturity model and a seven-element scorecard, aligned to NIST AI RMF and ISO/IEC 42001, to help you self-assess, see the gaps, and find the upgrade path.
AI Research
When enterprises pick an AI framework, the open-source-versus-commercial debate too often runs on impression and is settled by seniority rather than evidence. Using verifiable 2026 market data, this article offers an actionable weighted scorecard—six dimensions, weights, a 1-to-5 scoring method and decision thresholds—to turn selection into a repeatable, auditable decision.
AI Research
Many companies get excited about "proactive AI" but can't tell it apart from the reactive AI they already run—or work out whether it pays. This article takes a business-decision view, using real market data and cases: which tasks are worth making proactive, how to set the benefit threshold, and the checklist to clear before handing over control.
AI Research
When rolling AI out beyond a successful pilot, the bottleneck is usually people, not technology: McKinsey finds 88% of organizations use AI, yet only about one-third scale it enterprise-wide. Drawing on McKinsey, BCG, Prosci, and Gartner data plus the Moderna case, this playbook covers stakeholder mapping, four sources of resistance, ADKAR-paced communication, champion programs, and tying adoption to KPIs and workflows.
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