Octopus Energy's AI email assistant Arlo scored higher satisfaction than human replies
76% customer satisfaction for AI replies vs 72% for comparable human replies, on ~8,000 emails a week (4% of UK customer emails).
A searchable directory of real-world AI agent use cases. Every entry links to its evidence, says who reported the result, and lists the caveats.
35 of 35 use cases
76% customer satisfaction for AI replies vs 72% for comparable human replies, on ~8,000 emails a week (4% of UK customer emails).
More than a thousand pull requests merged each week are fully agent-produced and human-reviewed.
Work that took about 30 minutes per ad now takes about 30 seconds; the plugin can make up to 100 ad variations at once.
1,500+ merged AI-generated PRs; 1,000 merged PRs took three months at first and about ten days later on.
Amazon expects over $10B in annualized incremental sales; shoppers who used Rufus were 60% more likely to buy.
Over 100 digital employees in production by October 2025, later reported as 130+, each with a human supervisor.
72 security fixes upstreamed to open-source projects in six months, including projects as large as 4.5 million lines of code.
Aider's release notes report that Aider wrote up to 88% of the code in a release (v0.86.0, August 2025).
About 1.5M customer conversations handled by agents, with CSAT about the same as humans; support headcount went from ~9,000 to ~5,000.
Pilot started with plans for hundreds of instances; the CIO expects 3–4x developer output on routine code updates.
Used by 1,000+ finance teams within six months; Ramp claims 99% approval accuracy and 7x more out-of-policy spend caught.
A working OAuth 2.1 provider library for Cloudflare Workers, written mostly by Claude and reviewed by Cloudflare engineers.
#1 on the HackerOne US leaderboard, with 1,000+ reports in a few months and 130+ confirmed and fixed by program owners.
~3,500 test files migrated in 6 weeks; about 97% fully automated and the rest finished by hand.
One of three fully AI-generated submissions cleared the acceptance bar at the ICBINB workshop (scores 6, 7, 6).
The system's top hypothesis matched the Imperial team's unpublished finding about how bacteria spread resistance genes.
Average resolution time fell by more than 87%, with thousands of requests resolved per day (company claim).
Across 39 migrations, about 74% of code changes were LLM-generated; developers estimated a 50% cut in total migration time.
94% containment of common questions, 75% fewer HR support tickets since 2016, and a 40% cut in HR operating costs over four years.
Average resolution rate of 66–67% across about 6,000 customers, up from about 51% at launch.
More than 70% of the firm uses Lilli regularly, with millions of prompts answered (company figures).
Seven hours of mostly autonomous coding in one run. Rakuten reports 99.9% numerical accuracy versus the reference method.
Inbound SDR work went from about 10 people to 1 plus a part-time person; the agent costs about $5,000 a year to run (as reported).
Found a previously unknown, exploitable memory-safety bug in SQLite; developers patched it the same day, before any release.
Launched to charter customers including AMD, Canva, Siemens, and Zurich Insurance, aiming at the 20+ hours a week recruiters spend on admin.
70,000+ questions answered across 154 Slack channels, with an estimated 13,000 engineering hours saved.
Uber estimates a query that took about 10 minutes to write by hand now takes about 3 minutes; the limited release reached ~300 daily active users.
30,000 apps upgraded. Amazon estimates 4,500 developer-years saved and $260M a year from performance gains.
One of the largest generative AI rollouts in healthcare: 24,000+ physicians across ~40 hospitals and 600+ offices.
Rolled out to the firm's financial advisors in 2024; the firm cites about 30 minutes saved per client meeting (testimonial).
2.3M conversations in the first month, about two-thirds of all service chats, the work of roughly 700 full-time agents (company claim).
A voice agent ready for live testing in about two months, answering in 2.5 seconds or less, with 50x more testing capacity.
Cognition reports 8–12x engineering-time efficiency and over 20x cost savings on the data-class migrations.
Pinterest reports 35% faster task completion for SQL writing, and first-shot acceptance rising from 20% to over 40%.
About 3,500 lawyers asked around 40,000 questions during the trial, followed by a firm-wide rollout across 43 offices.
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