PageSourceSearch

https://business-ai-benchmark.github.io/

html business-ai-benchmark.github.io collected 2026-10-03 08:44:36 UTC 2,721 bytes, 34 lines download raw bytes

1<!doctype html>
2<html lang="en">
3  <head>
4    <!-- Google tag (gtag.js) -->
vendor: 68 bytes, lines 4-5
4
5    <script async src="https://www.googletagmanager.com/gtag/js?id=
5G-1ESS0W4FS3
vendor: 16 bytes, lines 5-6
5"></script>
6    
6<script>
7      
vendor: 146 bytes, lines 7-11
7window.dataLayer = window.dataLayer || [];
8      function gtag(){dataLayer.push(arguments);}
9      gtag('js', new Date());
10
11      gtag('config', '
11G-1ESS0W4FS3
vendor: 8 bytes, lines 11-12
11');
12    
12</script>
12
13    <meta charset="UTF-8" />
14    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
15    <meta property="og:type" content="website" />
16    <meta property="og:url" content="https://business-ai-benchmark.github.io/" />
17    <meta property="og:title" content="Benchmarking AI on Knowledge Work and the Implications for Business Education and White-Collar Labor" />
18    <meta property="og:description" content="BusinessCaseBench: frontier AI on 615 business school case questions across 18 disciplines—linking LLM performance to O*NET occupations, MBA case method pedagogy, and white-collar labor implications. Wharton, Harvard, CMU." />
19    <meta property="og:image" content="/images/meta/cover.png" />
20    <meta name="description" content="BusinessCaseBench benchmarks frontier AI on realistic business case knowledge work: 615 questions from 238 cases across 18 disciplines, with implications for business school education and white-collar labor." />
21    <meta name="keywords" content="BusinessCaseBench, knowledge work, economically valuable, analytical reasoning, business education, benchmark, artificial intelligence, large language models, LLM benchmark, business school cases, case method, MBA, white-collar labor, O*NET, Harvard Business School, Harvard Business Impact, Wharton, Carnegie Mellon University, CMU, SD-Bench, MAI-DxO, medical superintelligence, NEJM case challenges, business case studies, AI evaluation, GPT, Claude, Gemini" />
22    <title>Benchmarking AI on Knowledge Work and the Implications for Business Education and White-Collar Labor</title>
23    <link rel="icon" type="image/png" href="/favicon-256.png" />
24    <link rel="preconnect" href="https://fonts.googleapis.com">
25    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
26    <link href="https://fonts.googleapis.com/css2?family=Cormorant+Garamond:ital,wght@0,300;0,400;0,500;0,600;0,700;1,400&family=Lora:ital,wght@0,400;0,500;0,600;0,700;1,400&display=swap" rel="stylesheet">
27    <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css" rel="stylesheet">
28    
28<script type="module" crossorigin src="/assets/index-CcPDWEoU.js"></script>
28
29    <link rel="stylesheet" crossorigin href="/assets/index-ATWEohVO.css">
30  </head>
31  <body class="bg-slate-50 text-slate-900 font-serif">
32    <div id="root"></div>
33  </body>
34</html>

Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.